Genesis of the FlowTracker concept
FlowTracker is an innovation over two decades in the making. Here is how the business problems came to our attention.
We first became aware of the business problem while working in Retail Banking finance. Our Wealth Management sales people we earning commissions based on a scale that rewarded them for "new money" sales... and there was no way to identify new money from internal transfers. Compounding the urgency of the issue was the growth in Mutual Funds sales, which were "cannibalizing" the bank's term deposit base to an unknown - but suspected to be very large - extent. We also realized that there were no really good metrics of lost business or "attrition" in retail banking.
Many bright people worked for a long time on the problem of product substitution measurement and never reached a truly satisfactory solution. As business priorities shifted, so did attention to the question of true metrics for retail bank business volume changes, but the underlying challenges remained unresolved.
The first prerequisite: databases that support Account and Product Analytics
The introduction of Management Information Systems that supported end-user analytics in banking was the beginning of a new age in analytics.
The time was the 80's and mass storage databases were really only starting to make inroads into the business management information space. What grew out of these new capabilities were new reporting paradigms: we could analyze information by branch location and by product right down to the account level for the first time.
These analyses had some false starts: compensation programs were aimed at account opening and closing activities and similarly misguided measures, largely because it was finally possible to micro manage to these metrics. Of course the result was that lots of accounts got opened without generating any real new business, and staff slowed account closing to a crawl, neither of which benefited customers or the bank.
What account based metrics did achieve, however, was the measurement of new and lost account volumes, as illustrated above. The limitation of these measures is that they don\'t identify whether we are dealing with new money, product substitutions or internal transfers between deposits and loans. Account analysis also offers little meaningful insight into account growth and reduction activity, since the source of the growth or reduction is unknown.
The second prerequisite: Customer Master Data (aka your CIF)
This enabled a substantial improvement in customer understanding and behavior analysis. The customer information systems added another dimension to measurement - customer - that could be layered on top of the knowledge gained from account and product analyses.
When the customer is the focal point of metrics, we can differentiate between new, ongoing and lost customers and superimpose those behaviors on the dimensions revealed by product and account analysis. For example, new customers are really a special case of product and account acquisition. Similarly lost customers are a special case of account and product attrition.
One major advantage of customer centric measurements is that when the customer is viewed in total, we can tell if their overall business volume is going up or down, because internal transfers among accounts cancel each other out. And of course, we know that when a customer is new or lost their business is certainly won or lost.
The third dimension: Patented Analysis of Business Flows
In both account and customer based analysis of portfolio changes the missing link has always been the problem of account and product substitution. When an account renews, for example, it is important for the bank too be able to tell that the new account is not a sale and the lost account is not attrition (as account analysis would indicate). It is also important not to overlook the fact that this event has taken place, even though no new business has been generated (a customer centric view would see no change).
What we need is an analytic method that can identify where changes we see in customer and account business come from and are going to. It is meaningful to know that customers are renewing - or not. It is meaningful to be able to "see" product substitutions apart from sales and attrition. It is also helpful to know whether significant behaviors like borrowing to invest or liquidating investments to pay down debt are happening in our customer relationships.
This "funding" dimension is the key to differentiating between "real" new and lost business and internal changes in our customer relationships. Both are important to understanding both the performance of the products, locations and people and the quality, nature and behavior of our customer base.
Putting it all together : FlowTracker
Combining the analysis of behavior in the account/product dimension, customer dimension and business flow dimension simultaneously is what FlowTracker is all about. The result is a set of "cells" of behavior that are identified specifically for each individual account in your database.
The power of the FlowTracker innovation lies in it's ability to subset observable changes in business volume into meaningful cells. You can identify all of the permutations and combinations of customer behavior that affect your portfolio, and reconcile completely and exactly to the portfolio at large.
This means that you can explicitly and reliably quantify the results of your marketing campaigns, sales activities, attrition/retention programs, product substitution and cannibalization, cross sales and fully understand the who, what when and where of customer events and behavior.