This is smart Analytics!

This is Smart Analytics WalMart finding out what sells in a hurricane Netflix finding out what movies a customer might want to watch An investor finding out anomalies exist in the stock market in order to make a profit to his/her customers Amazon personalizing and customizing websites Sprint finding out that a customer might want to drop its service before the customer even knows it Finding the best route for a packet in a network

It helps Answers Key Questions What movies (or books) customers would like to watch (or read)? What movies to order from studio and how many? Who are our best customers? When is there a flu epidemic in region in the country? Which customers are most likely not to have an accident? When a customer is likely to jump ship & go to a competitor? When should we tell a customer to quit gambling? What is the one item you want to have in your store in case of a hurricane? What is the best criteria that predicts success when hiring a new Ph.D. student to become a faculty member? What is the one thing that will improve a lawyer’s chance to win a case? What are some questions one can answer with a loyalty card? What is the number one reason for the success of baseball player? Why should you always defer to the 2nd half to get the ball in college football?

Strategic factors for the use of Smart Analytics More difficult to find and sustain competitive advantages (geographical barriers gone, product differentiation reduced, etc.) Becomes increasingly more important to execute on strategy and become operationally excellent particularly in serving customers Many more business are now data-driven (virtual companies) Speed of change and risk in marketplace Evidence of success by other companies (Monkey see .. Monkey do)

Smart Analytics to the Rescue

But really what is this Smart Analytics? Well academicians will say that Smart Analytics is the process of collecting and analyzing data in order to make better business decisions, develop better products and serve the customers better.

Smart Analytics is: It is providing the right information at the right time to enable managers to make informed business decisions It fact-based rather than gut based decision making

You might be asking though Haven’t we always done made decisions based on data?

The answer is: Yes and no! Yes, we are deploying process analytics to manage some of our manufacturing facilities Yes, we are using basic data analytics in marketing No, we have not used it as a strategic weapon

Let me show you what I mean MONEYBALL

So in Baseball we have always used stats to manage the game RBI HR Fielding errors per game Batting averages vs. right or left handers But what was missed is the one measure that was most correlated with winning b-games

So what we have to do is identify the key performance measures that directly affect our strategic objectives, track them and identify those factors that affect them using statistics and other quantitative techniques

But why NOW?

Why is analytics becoming more important now? Much more operational data is being created and captured because of the use of technology (structured) Enterprise software ERP CRM SCM Much more unstructured data is being captured and stored (social media data) Facebook Twitter Much more unstructured data being captured Web transactions Smart objects

Data Overload

Data Storage Terminology

How Smart Analytics works!

Strategic use of Analytics Strategic Employee Questions Strategic Product Questions Strategic Financial Questions Strategic Customer Questions

Strategic Employee Questions Who are the most productive salespeople, employee? Who have the right skills for the next key product line? Which employees have the strongest customer relationships? Which managers have the highest retention rates? What do they do? Which hires work out the best (faculty)? What is our retention rate? Why do people leave? What is the cost of turnover? Why do people join the organization?

Strategic Product Questions What are our most/least profitable products? What are our production costs & how can we lower them? What is our quality level & how can we improve that (Fed Ex)? What is our cycle time & how can we lower it? What are the sources of product innovation? What impacts the demand of our product?

Strategic Financial Questions How accurate are the financial forecasts? How much financial data is used to answer business decisions? What items are affecting our margins the most (Wal-Mart)?

Strategic Customer Questions Who are the most/least profitable customers? Who are the most/least satisfied customers? What is fastest/slowest customer segment? What type of ads bring most customers? What is our customer experience like & how can we improve it? What is the cost of customer acquisition? What are the reasons for losing customer? What are the costs of customer transactions?

Has this technique been successful elsewhere? Revenue Management (airlines, hotels) Logistics (UPS) Customer turnover (Sprint) Customer service (Hannah Casino) Pricing (insurance) Trading (financial institution) Product selection (pharmaceutical companies) Employee performance (baseball)

Dangers in Analytics Privacy Security Drawing decisions on incomplete data Drawing decisions on inaccurate data Using only data that supports our gut decisions Drawing the wrong conclusion from the data Stock prices example

Analytic Tools Data mining Statistical analysis Predictive analysis Correlation Regression Forecasting Process Modeling Optimization Simulation

What it takes to succeed using this technique? Your (Top brass) support and commitment and desire to implement findings Collecting the right data (historical perspective) Developing a Data Warehouse (all data in one place Having a staff to analyze the data Managers that understand the business & embrace managing by the numbers

Managing using Analytics The success of analytics can only be measured in terms of how well they help the firm achieve their strategic objectives So a managers role is to: Identify business goals Find the matrices that are correlated with achieving the business goals Collect the data necessary to measure performance towards goals Analyze the data Establish weights for the each matrix element Draw conclusion based on the information generated

Where do we go from here?