Decision analytics: More than BI and Web Analytics


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Analytics is an overused term. This webinar shows how BI, web analytics, data mining and predictive analytics all have a role but all need a focus on decisions - especially operational decisions - to maximize their value. Webinar recording available here:

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  • Analytics means putting all your data, not just your web data, to work improving the way your web site works. It means using your historical data not for reporting but for predicting and driving new and more effective behavior across the company. It means putting all your data to work improving decision-making.This webinar will show you the range of meanings of analytics, contrast some of the common meanings and show how Decision Management and a focus on operational decisions can focus your analytic efforts for maximum value.
  • Fixed reports assemble a repeatable set of data to present a set of information.Fixed reports are typically generated and delivered on a regular schedule – daily, weekly or monthly for instance.Although a report, even a fixed report, could inform the reader, many are poorly designed and simply deliver large volumes of data with little or no information. For instance, a report that simply lists all the purchases made at a store on a given day would be full of data but of little or no value to anyone.Most fixed reports are either required for compliance purposes or they are a poor solution to a business problem. If, for instance, our problem is deciding which products are selling well enough to justify an additional supply and which are selling poorly enough to be discounted for clearance then a report of sales will enable us to answer the question. Trawling through all the data in a sales report, however, is a very poor solution as it requires a store manager to spend a long time reviewing the data and information in the report to derive the relevant (and useful) insight buried within it.
  • Dashboards are a collection of reports, visualizations and other elements designed to give rapid access to critical information.They are often compared to the dashboard of an automobile or airplane.In general a dashboard is better compared to the instrument cluster of an automobile as it only reports on status, it does not allow changes to be made.Dashboards generally use a graphical metaphor that will be familiar to a user – such as a process flow or map – to organize the information displayed.Key Performance Indicators or KPIs and other measures are common topics of dashboards and Enterprise Performance Management is a term often used to describe the use of dashboards in this way.
  • OLAP (Online Analytical Processing)is designed to rapidly answer complex queries against dataBefore OLAP tools can be used to analyze data a multi-dimensional data model is specified by a designer. These dimensions – date, location, value for instance – can be used in the analysisThis essentially “de-normalizes” the data in a way that allows certain kinds of analysis to be conducted very rapidly. For instance, the way sales vary by date and by location can rapidly be seen without having to run slow database queries.In addition many summary results and possible aggregations are pre-calculated and stored for faster access. For instance, date dimensions are often pre-aggregated into weeks, months, years, fiscal reporting periods etc. so that these roll-ups can be examined easily.OLAP tools allow managers and knowledge workers to navigate through data and pick out information
  • Visualizations help you see information content that would otherwise stay hidden in data. Unlike a report, visualizations do not rely on rows, columns and numbers to display information.Visualizations use graphic design and visual clues to bring out the meaning – the information – within the data.Visualizations rely on the human ability to rapidly see and understand patterns to help a user understand the information content of data.More and more new visualization techniques are being developed and productized all the time and what follows are just some examples.For more information about this topic, see the section on Visualization in the Bibliography provided in the Attachments tab.
  • Descriptive analytics can be used to categorize customers into different categories – to find the relationships between customers - which can be useful in setting strategies and targeting treatment. But this analysis must be delivered not just to your analysts, also to your systems. Analysis is generally done offline, but the results can be used in automated decisions – such as offering a given product to a specific customer – often by developing rules that embody the analytics.For instance a decision tree can be created where each branch, each end node, identifies the segment for a particular member.Data mining can also create rules with less effort and with a quicker time to market in certain circumstances
  • Predictive analytics often rank-order individuals. For example, rank-order members by their likelihood of renewing – the higher the score, the more “completers” for every “non-completer”. The risk or opportunity is assessed in the context of a single customer or transaction and these models are not an overall pattern, even if they are predictive. Models are called by a business rules engine to “score” an individual or transaction, often in real time, though the analysis is done offline.These models are often represented by a scorecard where each characteristic of a member adds to the score and where the total score can then be returned.
  • Models make predictions but predictions alone will not help much – you must ACT based on those predictions.When you are thinking about smarter systems, taking action means having the system take action in a way that uses the predictions you made. You need to make a decision based on those predictions and this means combining the models with rules about how and when to act.Let’s take our retention example from earlier. Knowing that a customer is a retention risk is interesting, acting appropriately and in time to prevent them leaving is usefulGrovel index story
  • Time is accuracy, accuracy is moneyThe delays caused by manual creation of models, calculated attributes, mapping to production systems, testing in production and all the other tasks involved in getting a model into production degrade the effectiveness, the accuracy of the model. Less accuracy means less money.It’s important to think about how long a model will take to get into production and consider that when building it – if changing the model makes it a little more accurate but much harder to implement, is that going to be worthwhile?Again, let’s consider our retention example. An analyst may find that including up to the minute call data makes the prediction of retention risk much more precise. But if it takes a week to implement a model that includes that data and only a day to implement one that does not the operational effect may be small or even negative.
  • Remember – decisions are where the business, analytics and IT all come together
  • Once deployed analytics cannot be a “black box”, we must understand analytic performanceObviously you need a 'hold out sample' or business as usual random group to compare to.You need to understand what's working and what's the next challenge – which segments are being retained, for instanceYou must understand operational negation.You need to track input variables, scores, decisions or actions taken (classic example is in collections where a strategy may dictate a 'do nothing' strategy, but the collections manager overrides the decision and puts the accounts into a calling queue) and operational data that fed the decisionBoth analysts and business users must think about what they can do to improve decision making, which is the foundation of adaptive controlIn our retention example I need to have some customers I don’t attempt to retain or that I don’t spend any money retaining. I have to capture what the call center representative ACTUALLY offered and what was actually accepted (if anything), not just what SHOULD have been offered and I have to be able to show the results to my business users in terms they understand.
  • At its heart a decision is a choice, a selection of a course of action. A decision is arrived at after consideration and it ends uncertainty or dispute about something.Decisions are made only after considering various facts or pieces of information about the situation and participants.Decisions select from alternatives, typically to find the one most profitable or appropriate for an organization.Decisions result in an action being taken, not just knowledge being added to what’s knownThe basic decision making process is simple. Data is gathered on which to base the decision. Some analysis of this data is performed and rules derived from company policy, regulations, best practices and experience is applied. A course of action, a selection from the possible options, is then made so that it can be acted on. When considering decisions in operational business processes, the way the decision is made is often constrained such that it can be described and automated effectively in many, even most, cases.
  • How many decisions are involved in sending a letter to a some customers?One view says a couple of decisionsWhat to put in the letter and who receives itA more complete view says that you have also made a decision for each customer to receive or not receive the letter. If you sent a letter to 10,000 customers, you just made 10,000 micro decisionsAdding a new option to your IVR system means deciding that everyone who calls will hear the option. changing your website means deciding that every visitor will see something new…Many strategic decisions can only be implemented if many supporting micro decisions are also made.
  • All these pieces contribute to ever-more sophisticated decision services that support your business processes.Decision Services externalize and manage the decisions production processes and systems needBusiness rules allow business users to collaborate in the declarative definition of decisionsAnalytics can create better more data-driven business rulesAnd ultimately additional predictive analyticsAdaptive control allows test and learn to become part of a continuous improvement loop
  • It is often helpful to walk through one example here. Let’s take some interaction with a customer – say making a retention offer – and see how it might work.Initially we have different channels and our approach to retention is probably different in each. The first step, then, is to take control of the decision so we can make it consistently across channels. We should also use rules to describe it so that the decision can be automated correctly and managed by business staff, not IT. However not all customers are the same so we should analyze them and segment them so we can retain them differently depending on what is going to work. Segmenting based only on the data we have is interesting but it would be more useful if we could also use predictions as to their risk of leaving, lifetime value of them etc as part of our decision. Back to the data, then, to build predictive insights. Applying adaptive control to continually improve the outcomes and we end up with an optimized decision.As we work our way through the class we will revisit this and discuss.
  • Begin!Identify your decisionsHidden decisions, transactional decisions, customer decisionsDecisions buried in complex processesDecisions that are the difference between two processesConsiderWho takes them nowWhat drives changes in themAssess Change ReadinessConsider Organizational changeAdopt decisioning technologyAdopt business rules approach and technologyInvestigate data mining and predictive analyticsThink about adaptive control
  • Decision Management Solutions can help youFind the right decisions to apply business rules, analyticsImplement a decision management blueprintDefine a strategy for business rule or analytic adoptionYou are welcome to email me directly, james at decision management or you can go to decision management / learn more. There you’ll find links to contact me, check out the blog and find more resources for learning about Decision Management.
  • Decision analytics: More than BI and Web Analytics

    1. 1. Decision Analytics More than BI and web analytics<br />James Taylor,<br />CEO<br />
    2. 2. Your presenter<br />CEO of Decision Management Solutions<br />We work with clients to improve their business by applying analytics and analytictechnology to automate and improve decisions<br />Spent the last 8 years developing the concept of Decision Management<br />20 years experience in all aspects of software including time in FICO, PeopleSoft R&D, Ernst & Young<br />2<br />©2010 Decision Management Solutions<br />
    3. 3. The world of analytics<br />Challenges in Business Intelligence<br />Limitations of Web Analytics<br />Problems with Advanced<br />Analytics<br />The Decision Management Solution<br />Wrap Up<br />
    4. 4. ©2010 Decision Management Solutions<br />4<br />The one slide you need<br />Analytics is an overused term<br />More than just reports, dashboards, web analytics<br />Data mining, predictive analytics have potential<br />All these kinds of analytics have challenges<br />Analytics must focus on decisions, especially operational decisions to add value<br />Decision Management is a framework to put analytics to work<br />That let's you “begin with the decision in mind”<br />
    5. 5. The world of analytics<br />
    6. 6. The term analytics is overused<br />Reports of all kinds<br />Dashboards<br />Online Analytical Processing or OLAP<br />Data Visualization<br />Web analytics<br />Data mining and predictive analytics<br />6<br />©2010 Decision Management Solutions<br />
    7. 7. Reports<br />Repeatable set of data as information.<br />Delivered on a schedule or on-demand<br />Fixed or interactive<br />7<br />©2010 Decision Management Solutions<br />
    8. 8. Dashboards<br />Collection of elements in a portal or page<br />Designed for rapid information access<br />Often compared to a car or plane dashboard<br />Really just an instrument cluster<br />KPIs are common topics <br />Increasingly real-time<br />8<br />©2010 Decision Management Solutions<br />
    9. 9. Online Analytical Processing (OLAP)<br />Designed to rapidly answer complex queries<br />A multi-dimensional data model is specified<br />Dimensions can be used in the analysis<br />“De-normalizes” data<br />Results and aggregations are often pre-calculated for speed<br />9<br />©2010 Decision Management Solutions<br />
    10. 10. Visualizations<br />Help you see hidden information patterns<br />Use graphic design, visual clues to show meaning<br />Rely on human ability to understand patterns<br />10<br />©2010 Decision Management Solutions<br />
    11. 11. ©2010 Decision Management Solutions<br />11<br />Web analytics<br />Collect, analyze and report on internet data <br />Understand and optimize websites<br />Understand impact of offline activities<br />Market research <br />
    12. 12. Advanced analytics<br />Descriptive Analytics<br />Classify or categorize individuals or entities<br />Examples:<br />Decision tree<br />Cluster model<br />Segmentation<br />“Data Mining”<br />Predictive Analytics<br />Predict future behavior of individual<br />Examples<br />Credit or risk score<br />Neural network<br />Additive scorecard<br />12<br />©2010 Decision Management Solutions<br />
    13. 13. Analytics simplify data to amplify its meaning.<br />“<br />”<br />13<br />©2010 Decision Management Solutions<br />
    14. 14. HighIncome<br />High income,low-moderate education<br />*<br />Moderate-high educationlow-moderate income<br />*<br />Low-moderateincome, young<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />Education<br />*<br />*<br />High<br />*<br />*<br />*<br />*<br />Moderate education,low income, middle-aged<br />*<br />*<br />*<br />*<br />*<br />Age<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />High<br />Low education,low income<br />Descriptive analytics <br />14<br />©2010 Decision Management Solutions<br />
    15. 15. Predictive analytics<br />15<br />©2010 Decision Management Solutions<br />
    16. 16. Predictive analytics turn uncertainty into usable probability.<br />“<br />”<br />16<br />©2010 Decision Management Solutions<br />
    17. 17. Challenges in Business Intelligence<br />
    18. 18. Knowing is not enough<br />©2010 Decision Management Solutions<br />18<br />Those who know first, win<br />Those who ACT first, win<br />Provided they act intelligently<br />
    19. 19. Is the value of BI …<br />19<br />Software?<br />Web Analytics<br />ETL<br />MDM<br />Reporting<br />OLAP<br />©2010 Decision Management Solutions<br />
    20. 20. Is the value of BI …<br />20<br />Timely and reliable data?<br />Such as reports, dashboards etc<br />©2010 Decision Management Solutions<br />
    21. 21. No. The value is of BI is <br />21<br />Intelligence about your business,<br />That enables better decisions<br />such as individualized customer interactions across multiple channels, targeted offers, fraud detection… <br />©2010 Decision Management Solutions<br />
    22. 22. Limitations of Web Analytics<br />
    23. 23. ©2010 Decision Management Solutions<br />23<br />Some typical web analytics questions<br />How much traffic is coming to our website?<br />I want a conversion rate<br />I want a path analysis for our visitors<br />I want to the list of top exit pages on our website<br />How many web leads did we get this month?<br />What are the click-through rates for promotions?<br />Thanks to AvinashKaushik at Occam’s Razor<br />
    24. 24. ©2010 Decision Management Solutions<br />24<br />Instead you need business questions<br />According to Avinash , business questions:<br />Are open-ended and at a much higher level<br />Require you to go outside your current systems and sources to look for data and to measure success<br />Rarely include columns and rows for your data<br />
    25. 25. ©2010 Decision Management Solutions<br />25<br />How can I improve revenue by 15 percent in the next three months from our website? <br />What are the most influential buckets of content on our website? <br />Do fully featured trials or Flash demos work better on the website? <br />What is the effect of our website on our offline sales?<br />What offers should I make to which visitors to boost revenue?<br />What content should I display to which visitor to maximize conversion?<br />Which visitors should get demos and which should get trials?<br />What cross-sell offer should I make to minimize cannibalization<br />But you need actionable questions<br />
    26. 26. Problems with Advanced Analytics<br />
    27. 27. HighIncome<br />High income,low-moderate education<br />*<br />Moderate-high educationlow-moderate income<br />*<br />Low-moderateincome, young<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />Education<br />*<br />*<br />High<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />Age<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />*<br />Moderate education,low income, middle-aged<br />*<br />*<br />High<br />Low education,low income<br />?<br />Analytic insights must drive action<br />27<br />©2010 Decision Management Solutions<br />
    28. 28. ©2010 Decision Management Solutions<br />28<br />Latency in decisions costs you<br />Business event<br />Decision latency<br />Action taken<br />
    29. 29. So time to deploy models matters<br />29<br />©2010 Decision Management Solutions<br />
    30. 30. Operational decisions are at the center<br />30<br />©2010 Decision Management Solutions<br />
    31. 31. Monitoring and compliance are tricky<br />31<br />©2010 Decision Management Solutions<br />
    32. 32. Decision Management<br />
    33. 33. 33<br />Think differently about analytics<br />It’s not the data and reports and visualizations that matter<br />It’s the decisions your company is able to make because of them.<br />©2010 Decision Management Solutions<br />
    34. 34. “<br />Making information more readily available is important, but making better decisions based on information is what pays the bills.<br />”<br />34<br />©2010 Decision Management Solutions<br />
    35. 35. ©2010 Decision Management Solutions<br />35<br />What is a decision?<br />Data is gathered, considered<br />A choice or selection is made<br />That results in a commitment to action<br />
    36. 36. ©2010 Decision Management Solutions<br />36<br />Different kinds of decisions<br />Type<br />Strategy<br />Tactics<br />Operations<br />Economic impact<br />Low<br />High<br />
    37. 37. “<br />Most discussions of decision making assume that only senior executives make decisions or that only senior executives’ decisions matter. This is a dangerous mistake<br />”<br />37<br />©2010 Decision Management Solutions<br />
    38. 38. ©2010 Decision Management Solutions<br />38<br />Micro decisions for customer-centricity<br />Make each decision for each customer<br />Don’t treat everyone the same, treat them uniquely<br />How many decisions are involved in sending a letter to 10,000 customers?<br />Just a few design decisions <br />Or 10,000 micro decisions - one per customer<br />
    39. 39. Blow up your home page<br />“<br />”<br />39<br />©2010 Decision Management Solutions<br />
    40. 40. Decision Management<br />An approach or business discipline for automating and improving decision-making<br />It improves day to day business results by<br />Supporting<br />Automating and<br />Improving operational decisions<br />It builds on existing enterprise applications to<br />put data to work<br />manage uncertainty<br />increase transparency<br />give the business control<br />40<br />©2010 Decision Management Solutions<br />
    41. 41. ©2010 Decision Management Solutions<br />41<br />Delivering Decision Management<br />3 stages to better operational decisions<br />Create a “closed loop” between operations and analytics to measure results and drive improvement<br />Design and build independent decision processes to replace decision points embedded in operational systems <br />Identify the decisions (usually about customers) that are most important to your operational success<br />
    42. 42. 5 principles of decision management<br />Little decisions add up so focus on operational decision making<br />The purpose of information is to decide so put your data and analytics to work<br />You cannot afford to lock up your logic so externalize it as business rules<br />No answer, no matter how good, is static so experiment, challenge, simulate, learn<br />Decision Making is a process so manage it<br />©2010 Decision Management Solutions<br />42<br />
    43. 43. Don’t start by focusing on the data<br />Better decision<br />Analytic insight<br />Derived information<br />Available data<br />43<br />©2010 Decision Management Solutions<br />
    44. 44. Start by focusing on the value<br />Better decision<br />Analytic insight<br />Analytic insight<br />Derived information<br />Derived information<br />Available data<br />Available data<br />44<br />©2010 Decision Management Solutions<br />
    45. 45. ©2010 Decision Management Solutions<br />45<br />Think decision services<br />ExternalData<br />Analytics<br />Web Data<br />HistoricalData<br />Ask a question about a customer<br />Decision Service<br />BusinessRules<br />Give an answer about a customer<br />DecisionAnalysis<br />
    46. 46. The evolution of a retention offer<br />http://www.f<br />Web<br />Call Center<br />Email<br />Mobile<br />Automate Decision<br />Apply rules<br />Close the Loop<br />Segment customers<br />Decision analysis<br />Predict risk, value<br />Optimize decision<br />46<br />©2010 Decision Management Solutions<br />
    47. 47. Wrap Up<br />
    48. 48. The one slide you need<br />Analytics is an overused term<br />More than just reports, dashboards, web analytics<br />Data mining, predictive analytics have potential<br />All these kinds of analytics have challenges<br />Analytics must focus on decisions, especially operational decisions to add value<br />Decision Management is a framework to put analytics to work<br />That let's you “begin with the decision in mind”<br />©2010 Decision Management Solutions<br />48<br />
    49. 49. Action Plan<br />©2010 Decision Management Solutions<br />49<br />
    50. 50. Decision Management Solutions<br />Decision Management Solutions can help you<br />Focus on the right decisions<br />Implement a blueprint<br />Define a strategy<br />For assistance, to find out more or if you have questions<br /><br />©2010 Decision Management Solutions<br />50<br />