Predictive analytics ouedi final version 11 3-13 2
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Predictive analytics ouedi final version 11 3-13 2
- 1. www.ouedi.org Predictive Analytics “Seeing Around Corners” By Dean Whittaker, CEcD
- 3. www.ouedi.org • Not recession but transformation: Edie W 3
- 4. Linear Thinking in a Cyclical World www.ouedi.org Event Time
- 5. Exponential Rate of Change www.ouedi.org 5
- 7. Evolution of Decision-Making www.ouedi.org PA Bus. Intel. Data Warehouse Data Predictive Analytics
- 8. BIG Data www.ouedi.org • What is it? • Why should you care?
- 9. Data, Data, Who’s Got the Data? www.ouedi.org • Got to have it! • Who’s got it? • How good is it?
- 10. Big Data in Economic Development www.ouedi.org • Zoomprospector.com • Sizeup.com
- 11. Business Intelligence www.ouedi.org • Predicting Corporate Behavior – Behavior linked to history – Accuracy is a function of data available – Rational Behavior? – Cyclical?
- 12. Predictive Analytics www.ouedi.org • What is it that you would benefit from knowing ahead of time? • Is there data that is plausibly correlated to that which you wish to predict?
- 13. Correlated Vs. Causal www.ouedi.org • Is it Causal? – Relationship in which one variable causes another • Or is it correlated? – Relationship of two variables and the degree to which they vary together • Correlation does not imply causation
- 14. What is Predictive Analytics? www.ouedi.org • Predictive analytics encompasses a variety of statistical techniques from modeling, machine learning, data mining, and game theory that analyze current and historical facts to make predictions about future events.
- 15. Predicting Corporate Behavior www.ouedi.org • Key Drivers – Change • • • • • • Leadership Ownership New Product/Service Merger/Acquisition Changes in Sales Changes in Employment 15
- 16. www.ouedi.org (C) Whittaker Associates, Inc. 2013 16
- 17. The Story of Sir Walter www.ouedi.org The evolution of Sir Walter from a simple database into a web-based lead tracking system
- 18. The Story of Sir Walter www.ouedi.org
- 19. The Story of Sir Walter (cont.) www.ouedi.org
- 20. The Story of Sir Walter (cont.) www.ouedi.org
- 21. The Story of Sir Walter (cont.) www.ouedi.org
- 22. The Story of Sir Walter (cont.) www.ouedi.org
- 23. The Story of Sir Walter (cont.) www.ouedi.org
- 24. The Story of Sir Walter (cont.) www.ouedi.org
- 25. Walter Test Data www.ouedi.org Company Re cent IPO No Red Hat, Inc. Intellicom, Yes Inc. 54 0 No N o N 17 24. Yes N/ Yes N/ No 84 0 No 57 N/ No o Chimerix, Yes Inc. .2 N o Fuentek, No Cicero, LLC M Sa Em Real Estate &A les p. Requirement Growt Growth h% % No Inc. o No 17 8.6 N 0.0 N o MCNC 4 A 11 A .3 N
- 27. Exercise I www.ouedi.org • Business at Risk – An Early Warning System – Identify five “leading” factors in their business environment and five within the company that would indicate a company is at risk of closing or laying off a significant number of employees. – Weigh each of the factors by their relative importance in being predictive.
- 28. What is Predictive Analytics? www.ouedi.org • Predictive analytics is a process by which those who have are compared to those who might to predict those who will. 28
- 29. Building a Predictive Model www.ouedi.org •DIY •11 Ants Analytics Model Builder •Tableau Software •RapidMiner •R and Rattle
- 31. Building a Predictive Model www.ouedi.org • 11 Ants Analytics Analyzer
- 32. Three Types of Predictions www.ouedi.org • Numbers – job growth • Categories – behavior • Propensity – probability to occur
- 37. Exercise II www.ouedi.org • Build a Community Economic Barometer – Identify five “real time” factors that could be measured to create a real time view of the local economy. – Identify five “leading” indicators that would forecast future economic performance.
- 38. Economic Barometer www.ouedi.org • Measuring the Economy – Usage of Resources • • • • • Electricity Gas People Raw materials Transportation – Movement of goods and people
- 39. Disruptive Economic Development www.ouedi.org Disruptive Economic Development
- 40. Putting It All Together www.ouedi.org • 1. Gain an understanding of the strategic use of Predictive Analytics to make smarter business decisions. • 2. See an example of a data mining and analytics model used to predict corporate behavior. • 3. Learn how an algorithm and social media are used in a predictive model to identify business opportunities.
- 41. Take Away? www.ouedi.org • What stuck? • What is useful? • Now what?
- 42. Thank You! hank You! www.ouedi.org Dean Whittaker Whittaker Associates, Inc. 1121 Ottawa Beach Road, Suite 200 Holland, MI 49424 616-786-2500 www.whittakerassociates.com dean@whittakerassociates.com
Hinweis der Redaktion
- Thank you and welcome! It is a pleasure to be here today to share some thoughts with you about the use of predictive analytics and its application to economic development. So, let’s get acquainted: Please take five minutes to get to know someone in the room you do not currently know… I will ask you to introduce them so takes notes… Who they are; Where there from; and What they are most passionate about? Now, please help me understand why you are here…in this class? What we you like to in the next 90 minutes or so that would be useful to you about this topic?
- Our Learning objectives for today’s discussion are: Here’s what I had in mind: 1. Gain an understanding of the strategic use Predictive Analytics to make smarter business decisions. 2. See an example of a data mining and analytics model used to predict corporate behavior. 3. Learn how an algorithm and social media are used in a predictive model to identify business opportunities.
- Another observation along the way is that as a species, us humans tend to think in a linear fashion in a cyclical world. As a result we become inefficient in our allocation of resources and our risk taking. We either over estimate or under estimate…in our predictions. Some examples: The stock market…bear or bull doesn’t last forever but think and act like it does. The economic recession (or depression) doesn’t last forever, it just feels like it is going to and, again, we act accordingly. What examples do you see?
- I’ve been chasing a dream for a very long time…almost 40 years…before many of you were born. The dream is to be able to predict corporate behavior. Over those years I have developed an understanding of the process by which data becomes information and is transformed into knowledge and that knowledge is applied to an action resulting in more data. The interesting thing about this cycle is that it is accelerating because of advances in technology. One of those advances is predictive analytics.
- Why should we care about predicting the future? (reducing risk) How do we go about it in our everyday lives? (weather forecasting) What does this have to do with economic development? (nothing and everything) Data driven decision making is 6% more efficient that using intuition. So, what’s the big deal… If your company makes decision 6% more efficiently than you competition, you win.
- Big Data…what is it and why should you care? Well, how many of you watch NetFlix…or shop on Amazon or cheat on your income tax? Borrow money from a bank, get diagnosed for an illness, or find a partner on the Internet? We are all impacted by Big Data (and little data)
- So, who’s got the data besides the NSA? Where is it? The growth of data storage – 27% The growth of data centers – 17%
- Here are two examples of the use of Big Data in economic development. Others?
- As I said, predicting corporate behavior has been a quest of mine for a long time. We are now using a statistical package to look into a large database of corporate information. One of the things we have learned so far is that the best predictor of behavior is someone who has done it before… The hard part of predicting behavior is that it is not always rational… what we should do is sometimes not we do. Also, sometimes we make decisions on bad data…and sometimes we think in a linear fashion when we are just at the bottom or top of a cycle.
- Here’s an interesting question: What is ti that you would benefit from knowing ahead of time? Is there data that is plausible correlated to that which you wish to predict?
- The latest thinking is that with Big Data it may NOT be necessary to know the cause of something but it may be “good enough” to know that this is correlated to that. So, when we this happen, we can predict that that will follow.
- This is definition of predictive analytics from the fount of all wisdom, wikipedia. The important point here is that it is STATISTICAL, and uses machine learning (looking for patterns) data mining and game theory to analyze current and historical facts.
- The biggest driven of prediction is change… if there was no change…prediction would be easy…more of the same…weather tomorrow will be the same as today… Something has changed inside the company or within their business environment to cause them to take that next step. Changes in leadership, ownership, sales, employment and products are the major dynamics we follow.
- The Sales Funnel is dead… or seriously wounded…It was killed or wounded by predictive analytics…but don’t tell anyone. Predictive Analytics turns the sales process on its head. Why would you go through this process of advertising, promotion, trade shows, conferences, etc. if you know which companies are going to relocate or expand in you community in the next 12-18 months? There are 3 main steps in our research process: generation, research, and filtering. This process narrows down the universe of companies to the best leads.
- Sir Walter (originally WALT than Walter) was created 7 years ago to help us collaborate internally as we did our research to share that research with our clients. We wanted to complete the information cycle that I showed you early by allow us to see the outcome of our predictions. WALT became WALTER when we enhance the tool with mapping and tracking capability. We are now working on SIR WALTER by building into the application the use of social media and the predictive analytic process. Here’s an example of how we are applying “predictive analytics” to BRE and recruitment: It came out of a ready, fire, aim process sketched on a whiteboard at a company Christmas party. Two weeks later, Walt was born. It was hard coded which made creation fast by modification hard, expensive and time consume. Using data mining techniques I found that corporate behavior is driven by change. Something has happened inside the company or in their business environment to cause them to take a particular action. I learned this by backing up a company in time to the point at which a particular action was taken to see what events were happening prior to the decision to take a specific action. Once I learned what these key events were I began to build a database of corporate profiles containing these precipitating events and Walt (Whittaker Associates Lead Tracker) was born.
- We moved from Walt, to Walter, and on to Sir Walter as the SAS (software as a service) Web App became increasing sophisticated (and expensive). In this version we added Google Maps with linked push pins, advanced search capability, linkedin relationship identification, and a few more from our wish list.
- Next, we are adding the ability to automatically update the event information for each company and notify us when this happens and to add the predictive analytic model to allow us to rank the company based upon the index number created by weighted matrix of events.
- By integrating Linkedin we created a path of our clients to contact the decision makes and build relationships through their existing Linkedin network. Linkedin is becoming the default social media platform for business.
- As I mentioned… Using data mining techniques we found that corporate behavior is driven by change. Something has happened inside the company or in their business environment to cause them to take a particular action. We learned this by backing up a company in time to the point at which a particular action was taken to see what events were happening prior to the decision to take a specific action. Once we learned what these key events were, we began to build a database of corporate profiles containing these precipitating events and Walt (Whittaker Associates Lead Tracker) was born. Next we are adding the ability to automatically update the event information for each company and notify us when this happens and to add the predictive analytic model to allow us to rank the company based upon the index number created by weighted matrix of events.
- The people tab and event tab brings together the most important information necessary for contact.
- This data was taken from the Walter. In reality it comes out as a CSV file which would be difficult to read in a slide so I have extracted a few categories for this discussion. As you can see, a recent IPO has a strong corralation with a real estate requirement…again not necessarily causal. So in your role as a data analyst for the private equity company, you may want to direct the agent of the property towards the pending IPO since the others have already taken action to meet their real estate requirement.
- To aid you in the exercise we are about to do. I would like you the think about the corporate life cycle of the companies with which or in which you work. Much as in nature, we are born, grown, mature and die. Companies do the same thing. To predict corporate behavior, take a look at what stage a company is in when calling on them as part of your BRE work. This same pattern holds true for products…Is their product or service past its prime?
- Ok, so now it’s your turn… I would like you to form 4-5 small groups and working together in your group create an “Early Warning System” for predicting when a company is both likely to grow and when they are at risk of moving or going out of business. You have 20 minutes. Let’s see what you’ve come up with…report out.
- Another way to look at predict analytics is by comparing data sets: Compare the events took place in those who have done what you want to predict with the events taking place in those who might do what you want to predict to predict those who most likely (probably will) do what you are predicting. Predictive analytics encompasses a variety of statistical techniques from modeling, machine learning, data mining, and game theory that analyze current and historical facts to make predictions about future events.
- As we discussed earlier, there is a growing short of analysis to interpret that every expanding volume of data. Do it yourself is an option for some organization. It entails a length process similar too but not the same software development projects. Have worked with a team of great Rudy programs using an agile approach I can attest to the adage: software projects always take twice as long and cost twice as much as you estimate. To address this issue, a few firms have begun developing tools to facilitate model building. 11 Ants Analytics, a New Zealand firm has built several types model including: Customer Churn, Retail Sales prediction, Propensity models using 11 machine learning algorithms that they have development. Tableua Software is a provides a visual data analytic tool to help their clients see and understand their data. Both of these companies offer trail versions of the products.
- The development of a Predictive analytic model has six key steps. First we need to understand the business we are in now and likely to be in in the future. Next we need to understand the data we have or will need prepare that data for modeling. Create and test the model using one or several algorithms and then deploy it within the organization.
- Here’s a software tool to help you build your predictive model: 11 Ants uses a machine learning program to analyze the data in your database to identify the patterns and create an algorithm that then is used in your predictive model.
- 11 Ants software allows us to create three types of models. Models that predict numbers Models that predict behavior Models that predict propensity – most likely to occur
- Here’s an example of predicting a number.
- Predicting a category… could be
- And the one I am most interested in propensity…probability to locate or expand their business.
- Here’s an example from their website of predicting sales…an number
- Let’s try an exercise…back to your small groups Your mission (should you accept it) is to create an economic barometer…to predict your local economy. What factors do we need to know? Real time…no lag. What factors we be leading indicators…correlated with future behavior…
- Here’s some the ideas other classes have put forth…
- Innovation in economic development is by definition disruptive. Here’s a five minute YouTube by Anatalio Ubalde in which he describes the coming disruptions in economic development.
- Finding competent people to implement a data analytics project is the greatest challenge in my opinion. I am very impressed with CUNY and their effort to address this short of talent that companies are facing. Data Scientist will be one of the fastest growing professions in the county for some time to come. It requires that unique set of skills…part engineer, part IT, and part business man.
- I hope you have found our time together beneficial. What are your take-aways? What are you going to do with what you learned today? If not you, who. If not now, when? Thank you.