Strategy plan
ETHNICAL CASE STUDY – Asking the Right Question COMPANY PROFILE EthniCal is privately owned family-run e-commerce business based in Orange County, California. It sells ethnic garments from around the world to US-based customers through a web-based portal. Ethnical was started in 1985 by a couple who began the company as a mail-order catalog selling high-end ethnic clothes to immigrant families. As they expanded the business to include garments across Asian and African countries, they discovered that customers would buy clothes from many different communities, not just their own. They were able to expand their customer base significantly beyond immigrant families, and by the late 1990s were generating ~$25MM in annual revenues through the national mail order business and five retail locations in Los Angeles, Irvine, Riverside, San Diego and Santa Barbara. In 2005, the founder’s son Sam graduated from college and joined the company. The mail order catalog business continued with the owners still focused heavily on their retail locations. Due to cost pressures of operating the stores, the retail locations were closed down in 2012 and the company launched an e-commerce portal to become purely internet-based. Sam took over as CEO of EthniCal in 2013. Operating the e-commerce business with a leaner staff, Sam was able to maintain ~$25MM in revenues in 2012 with improved profitability. He built up a small marketing team and launched acquisition campaigns and loyalty programs in 2013 which raised annual revenues to $30MM. Sam developed a strategy to increase annual revenues to $100+MM in 5 years by expanding the products to include jewelry and high-end handicrafts of different ethnic communities. His goal is to raise funding to initiate this expansion in 2017. However in 2016, Ethnical faced sudden and unexpected competition from the launch of a US e-commerce site from BC2K, a British internet retail business with similar offerings. Ethnical knew that BC2K would launch with aggressively discounted pricing, so they increased the loyalty program incentives to ensure their customer base would not defect. Despite the increased spend on retention tactics, EthniCal sales were impacted significantly by BC2K’s competition with 2016 revenues dropping to $19MM. Sam concluded that their retention efforts were not aggressive enough and directed the head of Marketing, Sherin, to make any changes needed to their loyalty program. Sherin recruits you as an Analytics expert on a short-term engagement to evaluate their retention activities, with potential for the role to be converted to full-time. Initial Framing of Problem to Solve You start work EthniCal office on January 5th, 2017 where you meet with Sherin and Sam and are immediately impressed. The office culture is informal and intense at the same time. Sam is charismatic and outgoing – passionate about the company, and very knowledgeable about the marketplace and customers. Sherin is thoughtful and precise – while relatively new to the business of ethnic apparel, she is an experienced e-commerce professional who is applying her well-honed skills to a new market environment. Sam and Sherin communicate well with each other, build off each other’s ideas and clearly have a high degree of mutual trust and respect. In this initial conversation, Sam and Sherin make their expectations clear to you and give the opportunity to ask any questions. As you get into more detailed questions about the company history and current competitive environment, you notice that Sherin withdraws while Sam does more of the talking. He is passionate about the loyalty program and has come to realize that the incentives needed to be more attractive to customers to retain them against BC2K’s competition. He outlines his strategy to turn around performance in 2017 through a combination of activities: Scaling back on customer acquisition efforts to ensure focus and higher investment on building loyalty and retention Partnering with loyalty programs for ethnic restaurants and major online ethnic grocery businesses to provide joint offers to “win back” lost customers and retain others Offering deeper discounts to returning customers for EthniCal products As the meeting concludes, Sam and Sherin articulate their objective to optimize EthniCal’s customer retention strategy and tactics to win back the business lost to BC2K and turn around their revenue performance. In your first project you must conduct an evaluation of the current loyalty program, identify gaps and new opportunities, and recommend a new approach and incremental investments needed as soon as possible. How much investment should be shifted from acquisition to retention? Which partnerships will be most beneficial to loyalty? What are the maximum levels of discount that can be offered in the loyalty program? Sam looks at the clock and wraps up the discussion so that he can get ahead of traffic for a meeting with a potential loyalty program partner. He asks you to confirm that you have understood the scope of the project so that you can move ahead on their request. YOUR TASK Starting from the objective stated to you, use the problem definition framework to determine if the question needs to be re-defined. What is the right question that EthniCal leadership should be asking?
Strategy plan
ETHNICAL CASE STUDY – Diagnosing the Problem APPROACH With the newly defined problem statement, you now need to conduct a root cause analysis to understand why competition from BC2K’s new portal has eroded EthniCal sales, and therefore how to respond. Is the CEO’s strong gut intuition correct that the issue has been caused by defection of Ethnical’s existing customers to BC2K? What other causes are there? What data is available to determine the root cause? This exercise should be approached in two steps: Step1: construct an issue tree which breaks down the issue (erosion of Ethnical revenues) into all possible drivers. If defection of existing customers is one explanation, what are some others? Step 2: for each driver, identify the data you will need to confirm or rule out that factor as a possible cause. The company’s CEO and Head of Marketing currently receive a set of KPI’s to track sales trends and portal activity, which are shared with you. Is this sufficient to answer the questions, or do you need additional data? AVAILABLE DATA There is currently no analytics function at EthniCal and the only information is available from some basic KPI reporting that is done through their IT function. The IT team is largely focused on optimizing the user experience for web portal and mobile apps, and one person on the Ux team spends a portion of their time creating reports for the CEO and Head of Marketing. The available data exists in siloes and it is inefficient and difficult to work with. Reporting is done by Jeff on the IT team, who is capable but spends most of his time doing manual work to clean up and organize the different datasets. The categories of data are: User activity on web portal and mobile app E-mail campaign delivery, open rates and click-throughs to web portal Customer transaction logs Loyalty program registrations and offer redemptions While the information is rich and potentially insightful, there are some significant obstacles: Datasets cannot be linked so there is no way to create a 360-degree view of the customer to connect interactions and behavior KPIs are provided separately through the different systems/vendors in different formats, requiring manual effort and cutting/pasting to create one overall report for management Customer transaction data is managed by a vendor who provides some basic information on customer counts and sales totals, but charges a very high premium (tens of thousands of dollars) for raw data extracts and ad-hoc analyses The one dataset that is easily accessible is from the loyalty program, where the CEO’s attention has driven investments to store and access the data with the best technology. Customer-level data from the loyalty program can be easily pulled and explored, but is under-utilized. REQUEST DENIED After constructing your issue tree and reviewing the available data, you are concerned that it does not give you the information needed to diagnose the root cause of declining revenue. You approach the CEO (Sam) and Head of Marketing (Sherin) with a request to fund ad-hoc analyses of the customer transaction data. In particular, you want to see how customer lifetime value has changed after competitor entry, and confirm that the sales decline is due to loss of existing customers as Sam believes. The vendor has estimated these analyses will cost $25K but you believe it is essential to solve the problem. Sam is polite but firm in his answer. “We don’t need to spend all that money just to be told something we already know. I would rather spend it on retaining more customers. We know the losses are coming from an issue with loyalty. Please focus on analyzing the loyalty program data to help us understand how to improve retention!” YOUR TASK Develop an issue tree to show the possible causes of the sales decline Leverage the information in the KPI report as best you can to diagnose the issue
Strategy plan
ETHNICAL CASE STUDY – Decision Processes and Vision Based on your compelling analytic findings and recommendations, EthniCal leadership was convinced to refocus their efforts from loyalty to acquisition in the face of strong competition from BC2K. Results were immediately evident after the new acquisition strategy was put in place, and EthniCal has been successful in driving a growth trend within just a few months. Their revenues have now nearly recovered to the earlier level of $30MM and are on a path to exceed their goals. EthniCal’s data-driven turnaround has impressed their investors, and the CEO Sam was successful in raising funds for their expansion into high-end handicrafts and art. With the funding, he plans to put in place a new set of functions and expand the company to a staff of ~100 within the next two years. Through this major expansion, he is keen to ensure that the company retains it’s core values and closeness to the customer. He is also now a stronger advocate of analytics, although he is still learning how to balance analytic findings with his own judgment and intuition. Sam has extended you a full-time offer to lead an analytics function with EthniCal. The function will sit within Marketing to be close to the business lines, reporting into the Head of Marketing, Sherin. Before accepting the offer, you have a conversation with Sam and Sherin to propose that the analytics function should report directly to Sam to support decision-making across the organization. You explain that it is not a “condition” for your acceptance, but that you are proposing it with the sincere belief that it will drive a much greater impact this way. Both Sam and Sherin are very ambivalent about your proposal. They see clear value in analytics for Marketing, and are less clear about how decision-making in other functions could benefit the organization. With this uncertainty they are worried that the impact of analytics would be diluted if the function is spread too thin. However, they want to bring you on board and are willing to give you a chance to make your case with more substance. They would like to see a high-level business case for how analytics can drive value beyond Marketing within the expanded EthniCal organization, and will make their decision accordingly. THE NEW ETHNICAL ORGANIZATION With the funding to expand the organization, the CEO Sam announces the formalization of the following new functions in addition to analytics: Talent Acquisition and Retention: this function will sit within Human Resources and will be responsible for the design and implementation of strategies for employee hiring and retention as EthniCal expands it’s staff. Revenue Management and Demand Forecasting: this function will sit within Finance and will work closely with Marketing on strategies for revenue optimization through pricing and demand optimization. Shipping and Logistics: this function will sit within Supply Chain and is responsible to optimize the fulfilment and delivery of merchandise to EthniCal’s customers. It will also implement more rigorous methods for inventory management across EthniCal’s nationally-distributed warehouses. Partnerships: this function will sit within Legal and will be responsible for due diligence on suppliers/partners in other countries to ensure full compliance of their local practices with US laws and regulations. Their work will involve extensive reviews of financial reports, filings and public domain content about the suppliers/partners. Data Management: this function will sit within IT and will revamp EthniCal’s infrastructure to ensure fast, efficient data feeds to support new and existing functions so that access to information is no longer a barrier. YOUR TASKS Part I (Day 3 Morning) For each of the new functions, list out the decisions that are necessary to successfully carry out their responsibilities Identify potential opportunities for analytics to guide decisions in each area Prioritizing according to business relevance and impact to identify a recommended set of areas that the new analytics function will support in addition to Marketing [Note: the Data Management function is a partner whose role is to configure information for reporting and analysis. They will set up the data streams and data integration needed for Analytics to effectively support the other functions.] Part II (Day 3 Afternoon) Taking the decision processes from Part I, combined with the planned support of Marketing, develop an overall vision of analytic maturity for EthniCal to present to Sam and Sherin. What are the functions that Analytics will support? What is the business value that this will deliver? At full maturity, what level of analytic rigor will be applied (i.e. descriptive, predictive, prescriptive) in each area? At full maturity, what level of scale will be achieved in each area? Will analytics be responsible for all support on a project-by-project basis, or will there be automation and development of analytic products for end users? The main competitor BC2K will compete in all areas but with a traditional, intuition-driven approach. What are the specific attributes of competitive advantage that this enterprise analytical approach will provide?
Strategy plan
Introducing the course – building analytics as a strategic capability  Defining objectives for success of your company  Finding competitive advantage opportunities through analytics  Communicating the value and engaging the organization  Learning and adapting to drive ultimate success Case studies and group exercises E – Commerce Professional Sports Groups 1, 3, 5, 7, 9 Groups 2, 4, 6, 8, 10 Background on case studies  Fictionalized versions of actual business situations  Key information will be shared, but not everything  some light research on company types will be useful  Purpose of cases is to provide some context for the application of tools and frameworks First, let’s define Business Analytics Deriving actionable insights from available data/information to guide business decisions There are different kinds or levels of Business Analytics Descriptive Analytics – What happened? Diagnostic Analytics – Why did it happen? Predictive Analytics – What might happen? Prescriptive Analytics – How can I make it happen? Evolution of Business Analytics Specialized Consultative Transformative Strategy Statistics Strategy Statistics Strategy Statistics Technology+ interactive, collaborative, efficient+ problem – solving focusTechnical rigor Setting sales targets Optimizing resource allocation Diagnosing business performance Finding new opportunities Actionable customer insights Analytic products “Democratization” Single version of the truth Single source of the truth Leaders who successfully compete on analytics Billy Beane Gary Loveman A. G. Lafley Rich Fairbank Barry BerachaHow many were practitioners? What do they have in common? • Background? • Industry? • Appreciation for analytics • Approach to building analytics into a strategic capability An Analytics Culture is critical to creating a competitive advantage COMPONENTS OF AN ANALYTICS CULTURE Behaviors • Integration of information management and business analytics into strategy • Promotion of analytics best practices, collaborative use of data across company lines • Planned investments in analytics technology, new talent and training • Pressure from senior management to become more data – driven and analytical Values • Data is treated as a core asset • Analytics is a top – down mandate driven by executives Decision – Making Norms • Analytical insights guide future strategy • Data analysis outweighs management experience when addressing key business issues • Organizational openness to new ideas and approaches that challenge current practices Outcomes • Analytics changes the way business is conducted • Analytics causes a power shift in the organization THE ANALYTICS MANDATE, MIT SLOAN MANAGEMENT REVIEW, May 2014 Analytics Virtuous Cycle Building analytics into a strategic capability Ask the right question Find the best solution through analytics Rally the organization to act Optimize by learning and adapting IMPACT! Define the problem Structure the problem Engage stakeholders Lead adaptivelyAnalytic Maturity Capabilities needed The challenge: most companies don’t make it all the way! Ask the right question Find the best solution through analytics Rally the organization to act Optimize by learning and adaptingTechnical breakthrough Do technical achievements automatically lead to impact and success? Why isn’t technical capability everything? A different example ….. Why isn’t technical capability everything? Another example ….. The Imitation Game Clip 1: 14:46 – 16:25 Clip 2: 1:20:21 – 1:21:31 http://digitalcampus.swankmp.net/columbia301179/watch?token=70c7e5 9861bc9d5cdbcd7f1f16e4945a5e0161fa01c8f428bc73815e3882d713 http://digitalcampus.swankmp.net/columbia301179/watch?token=70c7 e59861bc9d5cdbcd7f1f16e4945a5e0161fa01c8f428bc73815e3882d713 In summary: strong strategic skills are needed to drive impact Before doing any analyses: • Are we asking the right question? • Have we considered all possible ways to answer it? Which is the best approach? After the analyses: • Do we have a clear recommendation and a narrative to support it? • How should the organization take this into action? • What are the uncertainties and how will we respond? McKinsey Framework What are the insights of these quotes? “If I had only one hour to save the world, I would spend fifty – five minutes defining the problem, and only five minutes finding the solution.” Albert Einstein What is the insight of this quote? “If I had only one hour to save the world, I would spend fifty – five minutes defining the problem, and only five minutes finding the solution.” Albert Einstein If the problem is defined correctly, it will point us to the solution Importance of framing What problem are you trying to solve? https://www.youtube.com/watch?v=ui442IDw16o Defining the problem Framework to define the problem WHAT are you setting out to do? WHY are you taking this on? What is the real problem? WILL your approach address the problem? Is it the best/easiest/fastest way to solve it? “Chunking up” and “Chunking down” to find the right level Write in space Build a special pen to write in space Build a special pen with pressurized cartridges to write in space HOW? WHY? https://litemind.com/problem – definition/ Another example …. from a true story Situation: too many RAF planes being shot down in WW II Solution: • Analyze plans that returned from attacks • Find areas most likely to be hit, and reinforce • Reduce likelihood that planes will be shot down Framework to define the problem WHAT are you setting out to do? • Reinforce sections that were hit consistently on returning planes WHY are you taking this on? What is the real problem? • Need to reduce number of planes shot down WILL your approach address the problem? Is it the best/easiest/fastest way to solve it? • No! Since these are surviving planes: need to reinforce areas that were not hit! http://www.motherjones.com/kevin – drum/2010/09/counterintuitive – world Building competitive advantage: Moneyball Clip 1: 5:39 – 7:20 Clip 2: 9:57 – 11:48 Clip 3: 19:22 – 21:26 http://digitalcampus.swankmp.net/columbia301179/watch?to ken=2d4aee3d03a3236ac3b01e70e524f46d9d3cdec75cdc98 b182fdb91c3577dbe8 http://digitalcampus.swankmp.net/columbia301179/watch ?token=2d4aee3d03a3236ac3b01e70e524f46d9d3cdec75 cdc98b182fdb91c3577dbe8 http://digitalcampus.swankmp.net/columbia301179/watc h?token=2d4aee3d03a3236ac3b01e70e524f46d9d3cdec7 5cdc98b182fdb91c3577dbe8 Redefining the problem in Moneyball Recruit in – demand players Score the most runs Win the most games ? Other teams were solving the problem of how to recruit in – demand players However: data showed that in – demand players did not guarantee the most runs The A’s solved a different problem: how to cost – effectively recruit players who would score the most runs Are we solving the right problem? • Define success clearly and tangibly • List the sequence of problems to be solved for success • Which problem is most tightly connected to success? Which ones are not? Building competitive advantage: Enigma 1:23:56 – 1:25:37 http://digitalcampus.swankmp.net/columbia301179/watch?t oken=70c7e59861bc9d5cdbcd7f1f16e4945a5e0161fa01c8f 428bc73815e3882d713 Redefining the problem in The Imitation Game Break the Enigma code Stop the necessary number of attacks Win the war ? Initial focus was to solve the problem: how to break the Enigma code consistently However: stopping every attack would give away that they could break the code – giving away their advantage The team solved a different problem: how to selectively stop the minimum number of attacks needed to win the war SMART Framework Characteristics of good problem statement • S pecific • M easurable • A ction – oriented • R elevant (to the problem) • T ime – bound The Oilco refinery is suffering from poor profitability despite a strong market niche position Should the Oilco refinery improve its deteriorating position? Can the Oilco refinery be managed differently to increase profitability? Too generalNot disputableStatement of fact What opportunities exist for Oilco to improve profitability by $ 40 million per year through overhead rationalization, operational improvements, or restructuring non – core assets? McKinsey & Company The challenge: leaping before they look • Ingrained assumptions • Conventional wisdom • Urgency to act • …….. Small Group Exercise (1 hour) • Review case study information packs for assigned industry • Define problem to be solved • Identify one representative to read out Small Group Exercise – Readout • 3 – 5 minutes per team • No slides necessary • Explain to the class briefly: • What did you start with? • How did you approach problem definition? • What is your view of what the real problem is? Structuring and Solving the Problem Value of Issue Tree 1. Break down a problem into manageable parts – Problems that are complex and difficult are easier to solve by breaking them down into issues and sub – issues 2. Enable solving the larger problem by solving the right component parts – Prioritization focuses on the issues and sub – issues that drive the greatest impact and contribute most to solving the larger problem. Use 80/20 rule. 3. Align the team on nature of the problem and path to the solution(s) – Provides a shared understanding of the issues that comprise the problem. 4. Provide insight into missing issues and sub – issues – Make each level of the issue tree MECE. Problem Issue 4Issue 1 Sub – issue Sub – issue Issue 2 Sub – issue Sub – issue Issue 3 Sub – issue Sub – issue Issue 5 Sub – issue Sub – issue How could you reduce your expenditure each month? Buy fewer items Food Clothing Travel Entertainment Share costs of items (e.g., split rent with roommate, car pool)same quantity of items Buy lower – quality items Buy items at discount/on sale The challenge: tendency to do things the way they are already done • “Herd mentality” – follow same direction as competitors, without exploring other paths • Try to get ahead by brute force – drain on resources Advantage comes solving problems by working smarter“We cannot solve our problems with the same thinking we used when we created them.” Albert Einstein Issue Tree approach to finding new solutions Problem Solution 1 Solution 2 Solution 3 Everyone is doing this …. Not practical to implement This could work! Let’s explore further ….. Solutions must be M utually E xclusive and C ollectively E xhaustive (MECE) Solving the problem for the Oakland A’s Issue Tree approach for the Oakland A’s Recruit players who can score the most runs Compete for top players Raise more funding Use analytics to find undervalued players Everyone is doing this …. Not practical to implement This could work! Let’s explore further ….. Solving the problem for Enigma Clip 1: 9:38 – 10:20 Clip 2: 20:51 – 21:55 http://digitalcampus.swankmp.net/columbia301179/watch?to ken=70c7e59861bc9d5cdbcd7f1f16e4945a5e0161fa01c8f428 bc73815e3882d713 http://digitalcampus.swankmp.net/columbia301179/watch?tok en=70c7e59861bc9d5cdbcd7f1f16e4945a5e0161fa01c8f428b c73815e3882d713 Issue Tree approach for breaking Enigma Break the Enigma Code Break the code with linguists Break the code as a mathematical puzzle Build a machine to defeat a machine Not effective Not fast enough This is the only way to solve the problem Benefits of problem structuring • Uncovers new, undiscovered ways to solve problems • Helps with “root cause analysis” to understand what might be causing a problem in the marketplace • Helps make the best use of all available data and expertise What is the relevance of what we covered today? • Exercises were based on true – life success stories • Activities took you through the “anatomy” of success in each case • We’ll continue tomorrow on drivers of impact Game – Changing Analytics What’s different in the highlights of these two seasons? Golden State Warriors 2009 Golden State Warriors 2016 https://www.youtube.com/watch?v=uRep6XaVNhI 0:00 – 0:31 https://www.youtube.com/watch?v=PsjjzJUEVSU 0:00 – 1:00 Data – driven strategy around the 3 – point shot What is the narrative? Why move to more 3 – point shots? Was this data actually shared with the team? Analytics drove impact! Wins New 3 – Point Strategy Valuation: $0.3B Valuation: $1.9B What we learned today • Competitive advantage starts with defining the problem correctly – too often this is not done the right way • It requires objectivity and a comprehensive approach to finding solutions – don’t just try to outdo competitors at their own game • Finding a solution is not enough to drive impact – creating buy – in and testing/learning/adapting is necessary for success Tomorrow we will go through the next steps of transformation Ask the right question Find the best solution through analytics Rally the organization to act Optimize by learning and adapting IMPACT!We are HERE
Strategy plan
For today: • 2 – page, single spaced Org Readiness Assessment due by end of day for your assigned company in case exercises • Describe the baseline using information in case backgrounders, and any additional light research on the capabilities of such companies • Connection between today’s content and other courses (Org Context, Change) • This course focuses on applications for strategic leadership • Some material to be refreshed prior to case study applications On the journey to transformative analytics …. Ask the right question Find the best solution through analytics Rally the organization to act Optimize by learning and adapting IMPACT!We are HERE A typical situation You have a breakthrough insight It should have been welcomed and adopted …… …. but was not Why might this happen? Individual exercise List 3 – 4 reasons why valuable analytic insights might not be acted upon by the organization Possible barriers to analytic adoption • Awareness: no clear path to the decision – makers • Context: recommendations did not consider all factors (i.e. data does not always tell the full story) • Black – box: the intuitive basis for recommendations is not clear • Communication: results not understood by decision makers • Accountability: roles and responsibilities for taking action are not defined • “Paralysis”: belief that analysis must be perfect to make a decision How to address these barriers • Create awareness: org models and operating processes • Full context: cross – functional dialogue, active listening • Create transparency: communicate clearly with a “narrative” • Create accountability: use role/responsibility frameworks to develop an action plan • Create a “fit for purpose” mindset: what level of precision is needed? Achieving Business Outcomes from Analytics “Working at the front and back ends of the value chain is a particular challenge for most analytics functions because the nature of these tasks differs significantly from the technological jobs for which these individuals have largely been trained” Economist Intelligence Unit, 2016 Analytics as a competitive advantage The ability to make organizational decisions in a timely manner can be a genuine competitive advantage. • Strategy can be implemented sooner • Free up time spent seeking, processing, and communicating even more data • The decision makers don’t need to wait for more information. Quality, speed, and execution of decision making define top – performing organizations, especially for critical operating decisions that require consistency and speed https://www.eremedia.com/tlnt/want – a – competitive – advantage – get – your – team – to – make – faster – decisions – 2/ Evolution of how analytics is practiced From static …… ….. to dynamic and interactive Overview of Big Data Analytics Top – down decision – making: does it work? https://www.youtube.com/watch?v=TpBcwGOvO80 https://www.youtube.com/watch?v=ugN5aD5p2NU Example: baseball – the Oakland A’s Today we will review approaches to engage the organization • Organizational models with pros and cons • Techniques for effective dialogue • Communication of technical results • Frameworks for accountability Organizational Models and Constructs for Analytics How does the org model impact analytic maturity? • Aligns to different types of decision – making cultures • Drives speed/scale of adoption and sustained use of analytics • Drives efficiency and innovation Embed vs. centralize the analytics team? That is the question “The structure of analytics in large organizations can take many forms — from having a gazillion analytics micro – teams embedded in each function or BU, to completely centralized analytics at the corporate level. What is the right strategy? What should your organization do?” http://www.forbes.com/sites/piyankajain/2013/02/15/to – centralize – analytics – or – not/#91b9d3270483 Organizational Models Distributed • Analysts scattered across the organization in different functions and business units with little coordination Functional • Analysts located in the functions where the most analytical activity takes place, e.g. marketing or the supply chain CoE /Federated • Central group coordinates the activities of analysts who are organized within business units and functional groups Centralized • Central group serves the diverse needs of all business units and functions, and sets the analytical direction of the organization Individual exercise Take 5 minutes to think about the pros and cons of functional, federated and centralized models Group exercise List the pros and cons of functional, federated and centralized models with respect to: • Ownership • Objectivity • Agility • Efficiency • Big picture (vs. siloes) Stakeholders • Individuals or groups who are impacted by, or can impact, the work or its outcomes • Understand their stake in the work, and how they are important to the work • Context and critical input • Source of funds or resources • Can impact success or failure by action or inaction • Understand what they require from the success or failure of the work’s execution or outcomes • Personal gain • Organizational gain Stakeholder Types Upward – Influence of senior management, especially sponsor, over the activity Downward – Influence of team members to achieve the objectives and outcomes of the activity Outward – Stakeholders outside the entity, e.g. users, regulators, public Parallel – Peers of the program lead within the organization Culture will drive the importance and focus on different stakeholder types Refresher from Applied Analytics in an Org Context Prioritization of Stakeholders Prioritize importance of stakeholders at a given point in time based on • Input – expertise and feedback is needed • Influence – authority to permanently change or stop the project • Proximity – degree of involvement of the stakeholder in the project • Urgency – importance of the work or its outcomes to the stakeholder and their preparedness to act to achieve these outcomesRefresher from Applied Analytics in an Org Context Understand your stakeholders Empathy – where are they coming from? What motivates them? Refresher from Applied Analytics in an Org Context Small Group Exercise (1 hour) • Review case study information packs for assigned industry • Develop a stakeholder engagement plan to review your recommendations • Identify one representative to read out Communication strategies Analytics adoption by the Sonoma Stompers http://www.nytimes.com/2016/04/24/opinion/sunday/what – happens – when – baseball – stats – nerds – run – a – pro – team.html?_r=0 https://hbr.org/2016/05/what – a – minor – league – moneyball – reveals – about – predictive – analytics ) Big takeaways from their experience Effectively communicating insights is as important as finding them! • They were rigorous around every aspect of their analyses, except selling them. • Lindbergh and Miller behaved as if their evidence — or, more accurately, their presentation of the evidence — was obvious or self – explanatory. It wasn’t. Recognize, remember and respect what is not being measured • … as the season wore on, what wasn’t being measured — self – motivation, team chemistry, manager/player compliance with statistical insight — assumed greater importance. Predictive analytics create organizational winners and losers, not just insights Memorable quote on the importance of narrative We sold our story as something imposing — “data analytics” — and we made it about us. We should have sold it as providing them information, and made it about the team. That would have fit into their view of the sport — that we were trying to give them the same resources major – league players like Miguel Cabrera and Clayton Kershaw get. With other sabermetricians , more data wins arguments. In the dugout, a good story does. Sam Miller, Sonoma Stompers (2016) http://www.nytimes.com/2016/04/24/opinion/sunday/what – happens – when – baseball – stats – nerds – run – a – pro – team.html?_r=1 For example: “In the season’s final weeks, we changed course, focusing less on data and more on story. When we started using our closer in tight spots as early as the fifth inning — instead of the ninth, as every other team does — we kept our message as simple as could be: The game is on the line, so let’s take the bad pitcher out and put the good one in. Who could argue with that? We still used reams of charts and graphs to make these decisions, but those stayed between me and Ben.” Sam Miller, Sonoma Stompers (2016) http://www.nytimes.com/2016/04/24/opinion/sunday/what – happens – when – baseball – stats – nerds – run – a – pro – team.html?_r=1 Start with audience in mind and your purpose Who are the consumers of information? What do they already know? What are you trying to convey? What is the goal? Are you informing, gaining alignment, seeking a decision? Barbara Minto Pyramid Principle In the introduction, you prime your audience with the solution. Begin with the situation . Introduce the complication — which inevitably gives rise to a number of questions — then finally the answer . This is the top of your pyramid: Pyramid Principle Example Jeff Bezos Example 2016 Letter to shareholders • Culture is enduring, and Amazon has a unique culture that values experimentation • The risk is high but so is the payoff • What are the drivers of Amazon growth? • Prime, Marketplace and AWS are three big offerings Data visualization Why is this important? Our brains are wired for pattern recognition and pattern matching. Hans Rosling Beware the pitfalls of data visualization People trust visual images. Make sure it’s the right picture. Avoid misrepresentation. Decide what information you need and how to present it Which information is the most important? What is most important to measure? What are the best metrics for what you are trying to convey? Create structure and flow to the presentation Hans Rosling data visualization Understand Content and Purpose Is the content conceptual or data – driven? CONCEPTUAL DATA – DRIVEN FOCUS IDEAS STATISTICS GOALS SIMPLIFY, TEACH INFORM, ENLIGHTEN “ Here’s how our “ Here are our revenues organization is structured” for the past two years.” Is the purpose declarative or exploratory? DECLARATIVE EXPLORATORY FOCUS DOCUMENTING, DESIGNING PROTOTYPING, ITERATING, INTERACTING, AUTOMATING GOALS AFFIRM CONFIRM “ Here is our budget by “ Let’s see if marketing investments department.” contributed to rising profits” DISCOVER “ What would we see if we visualized customer purchases by gender, location, and amount?” Berinato , S.(2016). Visualizations that Really Work. Harvard Business Review , 94, 92 – 101. Visualization Framework Conceptual Data DrivenDeclaratory Exploratory Principles of Graphical Excellence • Well designed presentation of data • Communication of complex ideas with clarity, precision and efficiency • Gives viewer the greatest number of ideas in the shortest time and smallest space • Almost always multivariate • Tells the truth about the data E. Tufte , The Visual Display of Quantitative Information Source of 1854 London Cholera Epidemic ACA vs AHCA – What is the story? NY Times March 8, 2017 What is the story? NY Times March 8, 2017 Small Group Exercise (1 hour) groups • Prepare to present your insights and recommendations to the specified audience • Develop a clear, compelling narrative to communicate your findings and recommended actions • Identify one or more presenters to read out Adaptive Leadership Adaptive leadership is needed for success in the marketplace Ask the right question Find the best solution through analytics Rally the organization to act Optimize by learning and adapting IMPACT!We are HERE What is adaptive leadership and what is it not? “The leader of a company needs to have a decision tree in their head – if this happens, we go this way, but if it winds up like that, we go this other way” “I think that the minute you have a backup plan, you’ve admitted that you’re not going to succeed” Sean Parker on why Mark Zuckerberg was successful with Facebook Elizabeth Holmes on her leadership philosophy for the success of Theranos Adaptive leadership in action … or not Small initial investments to resolve uncertainties Big investments without testing assumptions Shortest lifetime from IPO to bankruptcy Adaptive leadership through the Lean Startup framework Lean Startup practices for adaptive leadership 1. Eliminate uncertainty 2. Work smarter, not harder 3. Develop an MVP (minimum viable product) 4. Validated learning http://theleanstartup.com/principles MVP A minimum viable product is “that product which has just those features and no more that allows you to ship a product that early adopters see and, at least some of whom resonate with, pay you money for, and start to give you feedback on”. Examples of MVP • Explainer Video MVP – short video that explains what your product does and why people should buy it. Dropbox • Landing page MVP – quickly communicate the value of your offering, diffuse objections, and call the visitor to action. • Wizard of Oz MVP – front that looks like a real working product, but you manually carry out product functions. Zappos • Concierge MVP – manual service that consists of the same steps people would go through with your product. Food on the Table • Piecemeal MVP – hybrid of Wizard of Oz and Concierge. 3 Tiny Habits • Crowdfunding MVP • Single Featured MVP – start with simple feature. Dropbox and Google http://scalemybusiness.com/the – ultimate – guide – to – minimum – viable – products/ Small Group Exercise (30 min) groups • Develop an adaptive plan around your recommendation • What could go wrong? • How can this be tested on small scale? • If wrong, what corrective action can be taken? (contingencies) Congratulations! Ask the right question Find the best solution through analytics Rally the organization to act Optimize by learning and adapting IMPACT! Define the problem Structure the problem Engage stakeholders Lead adaptivelyAnalytic Maturity Capabilities needed We are HERE Today’s assignment • Complete a 2 – page org readiness assessment for your assigned company • Integrate pre – session readings with content from Days 1 & 2 • Upload into Canvas by 11:59PM tonight Analytics Readiness StatSlice 2013 White Paper
Strategy plan
Today’s objective You have now: • Assessed the analytic readiness of your org • Defined a vision for future capability What is the path to get there? Building analytic capability involves evolution on several dimensions • People and culture • Processes • Technology Five Elements of Analytics Transformation Analytics Transformation Roadmap StatSlice 2013 White Paper A roadmap is needed to map the path for this evolution GOALPeople/ Culture Processes Technology Year 1 Year 2 Year 3 [Milestones] [Milestones] [Milestones] [Milestones] [Milestones] [Milestones] [Milestones] [Milestones] [Milestones] Roadmap Post – Session Assignment • Following this session, you will individually complete a 4 – page strategic and tactical plan with details of how your organization will execute the roadmap Evolution of people and culture Building analytic capability – people “ So now you’ve got the data available in some data warehouse configuration, and then the question is, how do I access it? How do I input it in decisions? How do I utilize that data effectively? That’s where people are now. They say, ‘Let’s go hire a data scientist or some statisticians. Let’s go hire some data engineers.’ And they find out everybody else is trying to hire the same people.” Hal Varian (Chief Economist, Google) Importance of analytical talent Internal expertise is needed to drive competitive advantage, i.e. less benefit if analytics is fully outsourced Source: MIT Sloan Management Review “The Talent Dividend” Levels of analytic maturity S. Ransbotham , D. Kiron, and P.K. Prentice, “Beyond the Hype: The Hard Work Behind Analytics Success,” MIT Sloan Management Review , March 2016 Analytically mature companies apply basic through advanced methodologies Source: MIT Sloan Management Review “The Talent Dividend” Building capability requires complementary strategies for recruiting and training Source: MIT Sloan Management Review “The Talent Dividend” Role types within analytics http://blog.hackerrank.com/the – biggest – misconception – about – data – scientists/ Role types within analytics: specific skills Business Analyst: Business analysts’ strengths lie in their business acumen . They can communicate well with both the data scientist and C – suite to help drive data – driven decisions faster. They typically work across sales and marketing teams to make data – driven decisions. Data Scientist: Data science is largely rooted in statistics, data modeling, analytics and algorithms. Data mining (the most in – demand skill on LinkedIn) is a subset of data science as the means to the end of extracting value from data using techniques, like pattern recognition, algorithm design and clustering, to better predict future behavior. Data Engineer: While data scientists dig into the research and visualization of data, data engineers ensure the data is powered and flows correctly through the pipeline. They’re typically software engineers who can engineer a strong foundation for data scientists or analysts to think critically about the data. http://blog.hackerrank.com/the – biggest – misconception – about – data – scientists/ Modern Data Scientist Data Scientist Profile http://www.kdnuggets.com/2014/09/hiring – data – scientist – what – to – look – for.html Data Science Teams How does Data Science differ from Statistics? Evolution of analytical culture STAGE 1: OVERRELIANCE ON MANAGERIAL JUDGMENT SUCH AS INTUITION AND INSTINCTS STAGE 2: SILOED USE OF ANALYTICS IN A FEW DEPARTMENTS STAGE 3: EXPANDING USE OF ANALYTICS IN SEVERAL DEPARTMENTS, NOTED BY AN INCREASING AMOUNT OF COLLABORATION STAGE 4: SCALING DECISION MAKING THROUGHOUT ALL RANKS OF THE ORGANIZATION IN AN INTEGRATED, HOLISTIC APPROACH STAGE 5: CONTINUOUS IMPROVEMENT BUILT ON AN EVOLVING CULTURE The Evolution of Decision – Making: How Leading Organizations Are Adopting A Data – Driven Culture (Harvard Business Review) Analytical culture in mature organizations The Evolution of Decision – Making: How Leading Organizations Are Adopting A Data – Driven Culture (Harvard Business Review) For discussion • How should talent acquisition and cultural change advance in parallel? • Is it possible to skip any stages in cultural change in the journey towards maturity? Evolution of analytical processes Building Capability – Processes How does analytics guide decision – making across the organization? Value initially demonstrated through ad – hoc projects Analytics conducted as planned, scheduled projects Analytics conducted as iterative, closed – loop processes Analytics focused on operations and optimizing existing processes Analytics applied to strategic questions and to explore new ideas Treating Predictive/Prescriptive models as high – value organizational assets For maximum value, the models must be: • Deployed across the organization • Embedded into business processes • Continuously monitored and optimized over time Setting up an iterative, closed – loop analytic process Business Manager Data ScientistData Engineer http://www.slideshare.net/TheMarketingDistillery/building – an – analytics – culture – a – best – practices – guide – 20502011Source: “Building an Analytics Culture”, SAS Conclusions Paper Business Analyst Ensuring collaboration across roles http://www.slideshare.net/TheMarketingDistillery/building – an – analytics – culture – a – best – practices – guide – 20502011Source: “Building an Analytics Culture”, SAS Conclusions Paper• Analytic processes are highly iterative • Roles do not work sequentially – they must collaborate closely • Skills, processes and culture must support effective collaboration Requirements for team effectiveness • Clarity of roles and responsibilities in the analytic process • Clarity of end – to – end steps in process through construction of analytic workflows • Effective communication across roles through a common business – oriented vocabulary RACI framework for role clarity http://racichart.org/the – raci – model/ RACI exercise for analytic process Assign R,A,C or I designations to each role in each step of the process Domain Expert Makes decision Evaluates process and ROI Data exploration Data visualization Report generation Exploratory Analysis Descriptive Segmentation Predictive modelingModel validation Model deployment Model monitoring Data preparation Clarity of end – to – end process steps • Analytic process typically involves detailed sub – steps driven by specific team members • If knowledge is not shared with others, high risk of process disruption if team member leaves • “Best practice” considered to be documentation However: documentation alone does not guarantee smooth transitions or reproducibility Analytically mature organizations set up analytic workflows for each process Benefits of building analytic workflows • Transparency on the details of every step in process to all stakeholders • Repeatability and efficiency of overall process • Reproducibility Examples of platforms for creating reproducible workflows • Enable live connections to source databases • Embed and integrate different tools and programming languages • Enable process automation Evolution of technology Big Data in Startups • Use big data for product and service innovation • Work on tools, not just applications • Give responsibility to data scientists • Contribute to the commons – open source • Impatient! • Take advantage of free stuff • Experimentation on large scale • Foster close collaboration Big Data in Large Companies • The existing technology infrastructure meets the organizational needs and are mission critical. • Changes to systems require processes, budgets, project management, pilots, departmental deployments, full security audits, etc. • Cautious about having young startups handle critical parts of their infrastructure. • Reluctant to move their data to the cloud, at least the public one. • Big Data success is not about implementing one piece of technology, e.g. Hadoop. It requires integration of technologies, people and processes . Analytics Technology Ecosystem Wang, Y., et al., Big data analytics: Understanding its capabilities and potential bene fi ts for healthcare organizations, Technol. Forecast. Soc. Change (2016), http://dx.doi.org/10.1016/j.techfore.2015.12.019 Analytics Stack and Capabilities Data Scientists and analysts Developers and engineersBusiness users and consumers Technologies for Big Data Technology Definition Hadoop Open – source software for processing big data across multiple parallel servers MapReduce Architectural framework on which Hadoop is based Scripting languages Programming languages that work well with big data (e.g. Python, Pig, Hive) Machine learning Software for rapidly finding the model that best fits a data set Visual analytics Display of analytical results in visual or graphic format Natural language processing Software for analyzing text – frequencies, meanings, etc. In – memory analytics Processing big data in computer memory for greater speed From Thomas H. Davenport, Big Data @ Work , 2014.Take 5 minutes and map the technologies to the layers in the stack. Big Data Landscape http://mattturck.com/2016/02/01/big – data – landscape/Trend is for innovation to move from left to right Interactivity and Visualization Capabilities From static …… ….. to dynamic and interactive
Strategy plan
YOUR TASK Starting from the objective stated to you, use the problem definition framework to determine if the question needs to be re-defined. What is the right question that EthniCal leadership should be asking? Leadership’s question: how to optimize customer retention (through loyalty program, even scaling back on customer acquisition efforts) Question needs to be redefined How can we increase our revenue What’s the objective that we achieve: Ultimate goal: How EthniCal could increase its revenue. More specifically: How to increase our competitiveness to create our sustainable advantage so as to constantly increase our revenue? Reasons why the question needs to be re-defined: Though retention strategy may help Sam to achieve the goal and increase revenue, it is limited. Even we win back the customers, with the price competition, our total revenue may still decrease. There are many different ways to increase the revenue, instead of choosing to directly compete against the BC2K. Failure to grasp the essence of problem The key to this problem is to improving the performance of EthniCal company. There is no point in fighting against our competitor if we are damaging ourselves in a considerable extent. Therefore, all of our strategies should serve one goal — improving our performance. Solutions: Increase product quality, develop different group of customers   Seek low cost suppliers to reduce the cost of goods to increase profit margin Instead of maintaining the current customer base or winning back the lost customers, focus on new customer base like high-end handicrafts This exercise should be approached in two steps:Step1: construct an issue tree which breaks down the issue (erosion of Ethnical revenues) into all possible drivers. If defection of existing customers is one explanation, what are some others? Step 2: for each driver, identify the data you will need to confirm or rule out that factor as a possible cause. The company’s CEO and Head of Marketing currently receive a set of KPI’s to track sales trends and portal activity, which are shared with you. Is this sufficient to answer the questions, or do you need additional data? YOUR TASK• Develop an issue tree to show the possible causes of the sales decline• Leverage the information in the KPI report as best you can to diagnose the issue Possible causes of the sales decline: Losing existing customers Can’t attract new customers Information in the report: EthniCal Cumulative Unique Customers: the increase of Cumulative Unique Customers is decreasing year by year, it means that the ability to attract new customers is decreasing Loyalty Program Offer Redemptions: Analyst told to andrew that Actually we are doing excellent job, our redemption rate is 97% percent. There is only tiny space we can improve. So we should focus on customer acquisition instead of customer retention Andrew thinks we still have space to improve the L program. Because the first-time loyalty program registrations have sharply declined in 2016 and He has many good ideas to improve customs retention. Analysis Compare to the loyalty program, decline in new consumer has big influence on the decrease of our company.   Analysis: Besides, the decline of the growth of loyal customers is not because of the loyalty program is bad but because we are losing new customers 35% decline in new consumer acquisition, which caused the actual decrease in first time registration for the loyalty program. So we have to acquire more customers first, once we achieve that, we still want him to keep this good record of loyalty program, to convert those new customers to loyal customers. Then andrew asked how they can assure that the customer acquisition can do well, because he can assure that he can do better in the customer retention Then the analyst said that they will do a regional test first to test their strategies to see if attracting new customers can turn over the revenue, just give them a chance to test it. Andrew agree the analyst to set some Pilot to test our strategy to increase our revenue and told analyst to talk to sherin and sam. 3/17   YOUR TASK Develop a stakeholder engagement plan for the people listed above, to make them aware of your findings and recommendations. Your plan should address the following: ·      Understanding each stakeholder. Where are they coming from, what motivates them? ·      How are they likely to respond to your findings and recommendations? What opportunities will they see, or what obstacles might they create? ·      What are the pros and cons of your being “embedded” within the Customer Retention function? ·      What is your priority of engaging stakeholders based on the criteria discussed in class? Is there an order in which you should share your results with them? Are these all 1:1 discussions, larger meetings or some combination of 1:1 and group conversations? The output from this exercise should be a plan describing the sequence of meetings, stakeholders in each, your objectives for each meeting and the strategy you will take in each discussion. Prioritize importance of stakeholders at a given point in time based on • Input – expertise and feedback is needed • Influence– authority to permanently change or stop the project • Proximity – degree of involvement of the stakeholder in the project • Urgency – importance of the work or its outcomes to the stakeholder and their preparedness to act to achieve these outcomes We ranked the stakeholders according to their degree of resistance, we determined that we should persuade Customer Acquisition Lead (Brian) first, because our recommendations of attracting new customers matches his needs for more budgets and resources for customer acquisition, so he and me are natural alliance. However, since Brian just joined Ethnical recently, he doesn’t have much authority in this organization. Then Brian and me will move to Sherin as she is experienced in using data and analytics, she is more willing to understand my analysis and recommendations if I give her solid evidence. After we convinced Sherin, Brain, Sherin and me will come to Sam. All sam care is to increase revenue, make the company successful. And Sam respects and trusts Sherin greatly. With Sherin’s support, we believe that we can reduce Sam’s resistance and persuade him that the declining new customers is the key issue, put our effort in customer acquisition program is the necessary way to save our business. Finally, we will come to Andrew. He might be the toughest guy so I need to find as much as alliance first. Tell him that his team already did a good job, what we are doing is not challenge his position and deny his performance. We still need his contribution to maintain our existence customers. However, the margin benefits loyalty program can bring is low, therefore, we will not give more budget to him, and provide more resource, start to put more effort in customer acquisition. Pros: As a part of retention team, I am able to get thorough understanding about the retention strategy and overall situation, which has helped us to persuade Andrew that retention team already did their best. As long as the team keep the performance, we will keep the existence customers.   Cons: we can not get our leaders’ support. Our whole team is in favor of retention strategy, giving us little internal support. 2. Brian: Reports to the Head of Marketing, Sherin. He is concerned that the resourcing decisions on acquisition vs. retention are always made on the basis of opinions and not facts. He need more support on new customer acquisition. Sherin: Focus on analysis. Sherin is very experience in analytics. By showing her our detailed analysis, we are persuade her easily. Sam: Focus on result. We can visualize the benefit of our analysis to persuade him that we can indeed increase the revenue of the firm, thus helping Sam to raise more funds for expansion plan. ·       Plan your communication to each group as a simple and engaging narrative of your findings and recommendations, using the Pyramid Principle if it is helpful ·       What is the best way to share your actual results? Are there creative ways to visualize or tell the story instead of using standard charts? ·       Be clear about your recommendations and the roles/responsibilities of the stakeholders you are speaking with Situation: with new competitor getting into the market, we are losing revenue by 37% from last year. Complication: our strategy now is focus on customer retention. However, retention is not the best way to turn over the current situation, because our offer redemption rate is 97% last year, besides, there’s only small difference between the growth of first-time loyalty program registration and the growth of new customers in 2016, which means that most of the new customers joined the loyalty program, that is pretty good. In the meantime, our new customer growth rate is decreased by 35% from last year. Question: what is best way to increase our revenue? Retention or acquisition? Answer: as marginal benefit of loyalty program is small, we should now focus on customer acquisition. In terms of visualization, Except for the standard chart that is hard to get the main point, we will also use conceptual line without numbers for revenue, because we only need to show the decreasing trend of revenue. For the decrease of new customer growth rate which is 35%, we will put this number very hugely and colored it red on the slides to catch the stakeholders’ attention and show the seriousness to lose so many new customers and it’s more illustrative. ·       Talent Acquisition and Retention: this function will sit within Human Resources and will be responsible for the design and implementation of strategies for employee hiring and retention as EthniCal expands it’s staff. Need to hire right talents that fit with our organizational value. We think that the talent acquistion are the most important thing we should do first. ·       Revenue Management and Demand Forecasting: this function will sit within Finance and will work closely with Marketing on strategies for revenue optimization through pricing and demand optimization. Decide the price which can bring the largest profits based on our supply and demand ·       Shipping and Logistics: this function will sit within Supply Chain and is responsible to optimize the fulfilment and delivery of merchandise to EthniCal’s customers. It will also implement more rigorous methods for inventory management across EthniCal’s nationally-distributed warehouses. Need to find ·       Partnerships: this function will sit within Legal and will be responsible for due diligence on suppliers/partners in other countries to ensure full compliance of their local practices with US laws and regulations. Their work will involve extensive reviews of financial reports, filings and public domain content about the suppliers/partners. Evaluate different suppliers/partners based on ·       Data Management: this function will sit within IT and will revamp EthniCal’s infrastructure to ensure fast, efficient data feeds to support new and existing functions so that access to information is no longer a barrier. Cleaning, processing the data to assist future analysis. Build metrics and KPIs to enhance understanding of the overall situation. First, Talent Acquisition and Retention, because Data management as a fudemantal department that support our analysis, Part I (Day 3 Morning) ·       For each of the new functions, list out the decisions that are necessary to successfully carry out their responsibilities ·       Identify potential opportunities for analytics to guide decisions in each area ·       Prioritizing according to business relevance and impact to identify a recommended set of areas that the new analytics function will support in addition to Marketing [Note: the Data Management function is a partner whose role is to configure information for reporting and analysis. They will set up the data streams and data integration needed for Analytics to effectively support the other functions.] Two main reasons: HR serves as the foundation of the daily operation of our firm. Without a normally-operating HR department, we can hardly ensure the operational efficiency of all the other departments. 2. Since we are a very young firm, we are not equipped with sufficient number of qualified employees. Especially, right now in our IT team, we only have people who are skilled in website optimization, we still people expert in other fields The reason why we think this function is our first priority is that without talents, we will be constrained. The firm currently does not have any analyst who can help to conduct analysis, let alone to say a whole analytics team. We need to hire more talents first to ensure we can progress into next step. Talent Acquisition and Retention employee hiring Quantify the specific attributes that the position demands and embed them into the models. Decide whether or not to hire the candidate based on the degree of match generated by the model. employee retention Quantify the performance of employees by the key indicators of their job. For example, for sales team, their main performance indicators include new customers acquired, monthly sales and number of sales attempts. Our approach here is building a model consisting of these factors to generate a numeric figure showing how well the specific employee is doing. presentation • Develop a 15–minute  presentation with 6 slides to summarize • Current state • Vision • Evolution of people/culture， “ processes，“ technology • Overall roadmap • Share presentation responsibilities across team Anallytics will support all functions as mentioned earlier. From talents acquisition to hire right people that fit with organizational value, to determine the right price to optimize our revenue and profits, and as well as optimize our supply chain to increase our margin. Analytics will help us in many aspects.  At full maturity, we will at prescriptive level of analytics. However, that does not mean we do not need descriptive and predictive analytics. All of these three levels are interconnected. we want to move into prescriptive stage, we have to excel in descriptive and predictive first to ensure our solution is not biased. We have to enhance our understanding first by using descriptive analytics, then to make our prediction using predictive analytics. And finally using prescriptive analytics to formulate the solution. At the maturity stage, though we can rely on analytics for automation and product development for end user, we will still combine our experience and knowledge when making decisions. Sometimes analytics even though can offer us the optimal result, we have to make sure such solution is compatible with our organizational value to stay close with our consumers. So instead of completely relying on analytics, we will use a hybrid system that combines our personal experience, organizational value and analytics to make the best decision and continuously improve our business performance. So lastly, competitive advantage. By using analytics, first of all, we will increase our efficiency of decision making. A mature level analytics will significantly reduce our workload when balancing every side of ideas, hence help to choose the best answer quickly. Also, reduce the risk of making poor judgement. Math never lies, but intuition will.  We will use analytics to avoid risky investment, and ensure our performance stays at high level.
Strategy plan
White Paper Series Developing a Business Analytics Roadmap A Guide to Assessing Your Organization and Building a Roadmap to Analytics Success March 2013 Business Analytics Strategy    1 A Guide to Assessing Your Organization and Building a Roadmap to Analytics Success Executive Summary Over the last few years IT industry analysts have pointed out that business intelligence is at or near the top of priority lists for many CIOs. Executives want it because they believe it will have a positive impact on business results. The concept of business analytics as a component of business intelligence has recently come front and center. Technology and constantly improving people skills have resulted in many categories of business analytics that are changing the way businesses l ook at critical performance indicators in their company. No matter how you personally view it, there needs to be business and technology strategies in place to help govern, assess, and build successful business analytics roadmap s. If you are not sure h ow to proceed, you are not alone. It is not an easy task to design and implement a successful analytics -driven enterprise. Creating a well thought -out roadmap to bridge the gap between information and analytics can be daunting. The challenge lies in acc essing your data and turning it into a tool for competitive advantage. The purpose of this white paper is to assist you in accomplishing this goal by providing valuable insight on:  The benefits of business analytics  Categories and types of business analy tics  Performing an analytics readiness assessment of the current state of your organization –including technology, business, and data  Building a transformational roadmap with recommendations and a plan to get you to your desired objectives What Is Strategy? The term “strategy” is frequently used in business and technology , yet do we really know what it means? For all of the work that people put into strategy statements, strategic roadmaps, corporate strategies, architecture strategies, innovation strategies, and so on, do you ever wonder if these effort s produce meaningful results ? Here’s the perfect definition . A stra tegy is a written plan to figure out the best way to get from here to there. Short and sweet. No matter what situation you find yourself in, the notion of getting from where you are to where you want to be is pretty simple. You start learning that concept as a child and it involve s the following :  Where you are now ?  Where you want to end up ?  What stands between the first two questions?  How do I approach the challenge ?  What course of action should I undertake (roadma p)? Because we work and live in a time where data is growing constantly , the se simple questions become amazingly complex very quickly. Creating successful strategies requires focus , homework, effort, assessment, and analysis. Business Analytics Strategy    2 Objectives and B enefits of Business Analytics Companies are looking for ways to gain advantage s. One proven way to get an advantage is through optimizing metrics for various areas of the business including: ● Return on Investment ● Revenue ● Profitability ● Cash Flow ● Productivi ty ● Long -term Planning ● Other metrics specific to your organization So how do analytics help? Analytics help you measure the performance of the various business areas outlined above. They give you the ability to establish a benchmark to determine what is good and what is bad. Proper analytics then help you monitor these metrics on an ongoing basis and help you troubleshoot bad performance to identify a root cause. Business Analytics Strategy    3 The value from key insights comes from the improvements of business processes broug ht to light by the analysis. If properly executed, analytics have the ability to deliver better business decisions and outcomes and deliver tremendous benefits, including: ● Improved analysis to predict and profile ROI and its impacts for proposed business initiatives ● Improved understanding of customers and their habits, especially buying and searching characteristics ● Creation of a rapid, fact -based culture to make decisions and reduce guesswork, especially when making strategi c product and revenue decision s ● Identification and optimization of the most profitable activities and elimination of m oney -losing business activities ● Identification and optimization of the true drivers of financial pe rformance and cost efficiencies ● Improved respon se to customer needs a nd trends High -Level Categories of Analytics Categorizing business analytics is not a precise science by any means. It is a topic of debate on social media sites and blogs where analytics gurus voice their professional opinions. For the purposes of this discussion, three major categories of analytics will be outlined. These types of analytics — operational , tactical and strategic — all have their roles in helping improve corporate decision making. Operational Analytics . This analytics type tends to assist in “business as usual” situation s where basic corporate metrics are reported and visualized. It is typically related to mature transactional systems. The organization is typically dealing with reporting of the “here and now” metrics for the busine ss. It has sub -categories (all sub -categories are discussed in more detail in Appendix A) that include topics like monitoring analytics and event -driven analytics . In some organizations, operational analytics results give you recommendations so that you can decide what to do with the information. The next level of analytics can even act on those recommendations automatically. Some industry experts view that a s part of operational analytics; others place it more in the tactical analytics arena. Tactical Analytics. This analytics view is usually longer term and focuses more on analytics to assist management in tackling problems , often including fairly simple predictive models based on past historical performance. One way to think of it is the ability to find out key metric “outliers” that do not have a big impact on your business strategy; they are more localized issues. The results of these outliers can be addressed by either human or machine -based business rules. Business Analytics Strategy    4 For example, your analytics system di scovers an anomaly in sales, maybe in a region or with a specific product. The organization now investig ates a one -time only situation — oftentimes a situation that is not repeatable. You now identify the cause and find the solution. Strategic Analytic s. This type business analytics can play a vital role in helping a company make dramatic decisions affecting the strategic direction of the organization. More complex systems and disciplines are needed in order for strategic analytics to become a key par t of the company’s decision making. Strategic analytics also has sub -categories (all sub -categories are discussed in more detail in Appendix A) that include things like predictive analytics, drill -down analytics, subject -matter analytics, ad -hoc analytics and comparative analytics. Within these categories, there are additional classifications that can be made and are fairly widespread in their use. Some of these sub -categories may appear within more than one of the three major analytics categories. You will find a description of these analytic types in Appendix A. Understanding the types of analytics can be helpful in improving the overall value of your business analytics platform. Review them as part of your overall needs assessment and in buildi ng your analytics roadmap. Business Analytics Strategy    5 Analytics Readiness Assessment Analytics projects typically require a significant investment and should not be undertaken lightly. Without proper planning , the risk of failure is high. The first part of your plan is assessing y our organization’s readiness for analytics. During this exercise you are typically asking questions and searching for information to ascertain the truth about the state of your organization in various areas related to analytics. An Assessment of Analytic s Readiness Capabilities Using the discipline shown in the diagram above, start with a carefully developed assessment of the analytics capabilities and sophistication within your company. The various components of this assessment are outline d next. IT Readiness Do you have the right technical team ? Analytics projects often require different skill sets, especially with some of the new tools and technologies that are available. Drill down and make sure you have the right people in your IT team to b ring analytics successfully to your organization . Do you have the right leadership in place ? Building analytics systems can sometimes be as much ar t as science. When you start combining business, IT, data , and corporate strategy issues all on the same p roject, you need clear and experienced leadership. Does IT have the proper data governance practices in place ? One of the main causes for analytics failure is the lack of data clarity in the source systems. Specifically , many source systems do not have properly designed data models that can be easily interpreted by downstream systems. Make sure your IT organization understands the state of its source systems. Business Analytics Strategy    6 Business Readiness Have you identified your needs ? Business managers who are the real drive rs of these projects need to clearly document why they need a properly -designed analytics system and where their current pain exists that is preventing them from proper business analysis. Do you have the right analysts ? Often overlooked until the end, a good team of business analysts is critical early in the project. Do you know what’s already in place ? Carefully document the business processes and rules currently in place and which of those are supported by any type of analytics system, even if it’s ju st exported reports to Excel. Is the business ready for analytics ? Successful analytics implementation often requires accompanying business process changes to take advantage of new insight . Management must get used to making data -driven decisions as op posed to those driven by “gut feel ing .” Technology Readiness Have you identified the right tools and technology ? Depending on the objectives, new tools and technolog ies exist, especially in the visualization area. Write up an assessment of your technol ogy inventory as part of the assessment process , and indicate the need for further technology evaluations as part of the final roadmap . Th e assessment should also outline the compatibility of these tools with what is currently used in the organization. I t is often best to align any new tools with existing platforms in order to reduce any barrier to implementation. Are i nfrastructure and security in place? Analytics systems require significant infrastructure capabilities including sophisticated security, increased network traffic, and additional data storage and data crunching capabilities. Underestimating the need in this area could cause roadblocks and derail your roadmap implementation. Do we have the right implementation partner identified? In almo st all cases, it is a good idea to bring in outside partners and consultants to help with specific pieces, or perhaps the entire project. If partners are needed, do you have some go -to resources in mind? Data Readiness Are the s ource systems mature? A common cause of analytics failure is relying on source systems that are in a constant state of flux. Source system frequent changes will cause downstream rework and potential failures. Make sure you take into account the state of your source systems in your analytics roadmap plan. Do you have sufficient data coverage ? A major roadblock to successfully implementing analytics is the lack of data elements required for providing comprehensive metrics. Don’t fool yourself; this is a problem in most organiz ations. Make sure you understand the gap between what is available from your source systems , and what is required by business and design your metrics to take this into account. Business Analytics Strategy    7 What are the d ata quality risks ? What data quality issues are there? If th ere’s a problem in this area, it will always show up at some point. If possible, t ry to identify issues earl y in the assessment . It will save time -wasting and morale -busting efforts down the line. The assessment effort should provide some clear delivera bles. Below are several important ones that should be considered. Deliverable Description Project Charter Describe the overall project, its objectives, deliverables, timeline, team members, organization structure, sponsoring executives, and so on. Bas eline Documentation Collection of materials accumulated before and during the assessment project, including project management notes, presentations, proposals and other baselines. Meeting s Inventory Document all meetings, interviews, and working sessions (with agendas, participants and roles, venue and equipment, baseline materials used, and meeting outcomes) . Assessment Report Final presentation that provides the results of the assessment activities. The report includes conclusions and recommended next steps. Development Proposal Proposal for the recommended solution with development plans and time lines. If the project is big enough, it might be broken down into multiple phases , and a development plan will be developed for each phase. Business Analytics Strategy    8 Build a Tran sformational Analytics Roadmap Any company that wants to reach the important and significant benefits of an analytics strategy needs to have a detailed plan defined that is best suited for their goals and situation. The roadmap will have multiple mileston es and will require diligent work and digging to uncover the objectives, obstacles , and steps to put the end result of the analysis on the roadmap document. What Makes an Effective Roadmap? Comprehensive Review Covers the various aspects of the busine ss For a roadmap to be successful it must address the analytics need s of the various aspects of the business. Make sure all the areas have representation in the roadmap to get a comprehensive picture early on. Properly identifies risk and outlines mitiga tion plans There are risks involved in most business ventures and implementing analytics is not an exception to the rule. Make sure that your analytics roadmap take s into account the major risks and roadblocks to successful implementation , and outline s steps that could help you avoid those pitfalls. Tied to Business Goals Properly identifies business goals If not done correctly, t his can be a fatal project flaw . Believe it or not, some projects proceed without the priorities and goals clearly defined. B uild your roadmap to include these important principles , and make sure everyone is in agreement. Business Analytics Strategy    9 Ties the analytics to business goals The IT department can sometimes have an overp owering impact on these projects. T he business benefits, surprisingly, can begin to take a back seat. We hear the horror stories all the time. Make sure the business teams are clear and concise in their needs and all involved understand the goals and deliverables . Achieves consensus amongst business owners If scope is not clear ly understood and documented, it will expand. This scope creep is a common problem , and it impacts not only the originally desired results, but it can be a morale and budget killer. Clear Understanding of Existing State Current state properly outlined A key part of developing a clear roadmap for success is to understand exactly where you are now. This exercise should include an outline of the existing production systems as well as high – level data flows. Missed opportunities identified Missed opportuniti es often provide support for analytics in terms of estimating return on investment. Identifying those potentials is helpful in making the case for building the roadmap. Existing challenges uncovered Your roadmap should document challenges your business ow ners are facing and roadblocks that prevent them from making proper decisions. These challenges provide support for the investment required for building the roadmap. Properly Prioritized Implementation Phases All required phases identified A successful r oadmap should divide the implementation into logical phases in order to reduce implementation risk. Phases should be around three months in duration. Taking on all the metrics and goals at the same time or in large chunks is very risky pri marily because business users l ose interest if they are not engaged on an ongoing basis. Prioritized in proper order of importance to business Prioritize your roadmap phases in order of importance to your business so that you reap the most benefits from your analytics ea rly in your roadmap and provide justification for additional phases. Strong early success provides the critical mass and positive impression about analytics which leads to stronger business adoption. Proper estimates provided Although it is not possible t o provide exact estimates at the stage of developing the roadmap, you should attempt to come up with ballpark numbers. There are many techniques that can be used to aid in this exercise. Make sure you are consistent and c omprehensive in your estimates in order to give management a good picture of the scope of the roadmap. Business Analytics Strategy    10 Summary W hen designing and implementing your analytics system , it is often most effective to start small. Start with some projects that are less complex but of relatively high value. Focus on early wins for the users and the analyst s. One good way to do this is with prototypes, often called “proof of concept,” to show those early successes. Company directions and strategy change. Technology improves and changes. The strategy needs to be communicated, discussed, negotiated, and then implemented, in an ongoing manner. The roadmap is a living document that needs to be kept up to date and includes a library of documents that go with it to support the project over the long term and th e projects that follow. What you will discover is a path that shows ongoing maturity, inter -relationships to multiple disciplines within the company, and many critical questions and answers. Does it sound complex? Yes, business analytics can be complex , especially if you don’t have a roadmap and a strategy. But, if executed well, analytics systems can have enormous positive impact on your organization. Business Analytics Strategy    11 Appendix A Understanding these types of analytics is helpful in improving the overall value of your business analytics platform. Review them as part of your overall needs assessment and in building your analytics roadmap. Monitoring Analytics. This type of analytics is all about answering questions, for example: What happened? Why did it happen? What do I know? It is a widely -broadcast view of key metrics that are happening right at the moment. It’s a fairly straight forward “push” data platform where data is visualized to the right people. Predictive Analytics. This type of analytics uses s tatistical techniques to predict outcomes. It can help answer questions like: What is likely to happen in the future? What is likely correct about customer behaviors? What do the forecasts show based on historical relevance? Drill -down Analytics. This t ype of analytics focuses on business users who want to move through a hierarchy of data structures as a method of exploring data and finding key metrics, including ROI and other measures of profitability. It often uses visualizations with OLAP or Pivot Tab le style technologies to view the business from the top level all the way down. Many dashboard tools now provide a near – infinite amount of drill -down capability if the analytics architecture has been done correctly. Correlation Analytics. This type of a nalytics tends to be heavy -du ty number crunching focusing on more machine -driven analyses using platforms like data mining. Comparative Analytics. This type of analytics takes high volumes of past data and compares it over time to see key similarities or differences in data patterns. What has changed recently? Is there outside industry data available where I can compare my metrics against industry standards and benchmarks? Real -Time Analytics. What is happening right at this moment? What are the analy tics I could use right now to make a difference in the business? I see the issue/problem/concern but what can I do right now to affect it? Subject Matter Analytics. This type of analytics gets very specific within a business discipline and allows you to immerse deeply into specific types of information, e.g. sales, cash flow, credit, fraud, marketing, and pricing. Business Analytics Strategy    12 Ad -hoc Analytics. Ad -hoc analysis is designed to answer a single, specific business question. The product of ad -hoc analysis is typically a statistical model, analytic s report, or other type of data summary. Ad -hoc analytics can be used to drill deeper to get details about accounts, transactions, or records. The process often involves the use of dashboards, OLAP models, and other tools by pow er business users. Operational Reporting. Operational reporting supports the detailed day -to-day activities of the corporation at the transaction level. It is typically used by the front -line operations personnel. Very short -term, detailed decisions are made from operational reports. Business Analytics Strategy    13 About StatSlice StatSlice is a strategic data services consulting firm headquartered in Dallas, Texas, specializing in data warehousing , business intelligence , and business analytics. Strategic data services include the skills, processes, technologies, applications, and practices used to support business intelligence and corporate decision -making. StatSlice has a highly dedicated consulting organization with a reputation for excellent customer service and measurable succe ss in implementation. They promote an environment of resourcefulness, innovation, and creativity without sacrificing measurable results. They continually stay on the cutting edge of the latest business intelligence and analytics challenges and principles , and as a result , they are a “go -to” team for your most challenging projects. For More Information For more information about StatSlice Systems services, call (214) 206 -9290 or email us at [email protected] . Please visit us at http://www.statslice.com © 2013 StatSlice Systems. All rights reserved. This white paper is for informational purposes only. StatSlice makes no warr anties, express or implied, in this document.
Strategy plan
Final Paper – Strategic Plan Your Strategic Plan is a 4-page single-spaced document that should roadmap an effective plan to identify important milestones to build analytic capabilities for the organization. Your roadmap can be represented in many ways, but should address: Comprehensive Review of the business and migration plans Explain how the plan is tied to the business goals and supported by stakeholders Clearly explains the existing state, missed opportunities and existing challenges Explains how to prioritize implementation phases, including estimates, order of operations and required phases.  Rubric for Scoring Articulation of how analytics will drive competitive advantage, and business value of building analytic capability (20 points total) Does the vision aspire for more? (5 points) Is it relevant and compelling? (5 points) Does it provide benefit to the overall enterprise (vs. specific siloes)? (10 points) Development of business case for change through analytics (25 points total) Is it clear on the benefit to each part of the organization? (10 points) Does it prioritize across functions, and what is the rationale? (10 points) Does it explain the downside if analytics are not used effectively? (5 points) Shaping of the implementation strategy: is it comprehensive and realistic? (30 points) Does it clearly define stages in building capability through people/culture, processes and technology? (15 points) Is the staging realistic and practical? What is the rationale for the specific objectives at each stage? (15 points)  Risks and obstacles to implementation: what are potential weaknesses of the implementation plan? What could go wrong? (25 points) 4 Steps to Becoming a Data-Driven Organization https://www.youtube.com/watch?v=GTH70zYrO4I 5 Steps to Readiness Assessment for Big Data http://www.b-eye-network.com/view/16762