Datability: Is it time for you to build on your own data?

"If the economy continues on a path that looks like a recession, consumers are going to tighten their belts even further. More and more of a consumer’s household income is now going to simply servicing current debt. The credit crisis will guarantee that this will go on for awhile longer given the bad debts on many lenders books".

Source: www.mybudget360.com

So, with all this spiraling debt, how come our inflation figures aren't even higher? According to this interesting site, the US Government is looking at inflation as something more long term, something that doesn't want to too heavily weigh Food, Energy and Health Care costs. Not only that, but there is an interesting discussion on how the Government calculations of "rent equivalent" valuation of housing stock, significantly underestimated how much the average person way paying out at the end of each month., i.e. they are underestimating the actual disposable income. 

 So what's my point?

(1) Information should be based upon data that you understand, that you have an informed understanding of, such as the nature of the "inflation figure" you are using;

(2) Using "big block" figures removes nuance, and nuance is the day to day stuff that gets you operational efficiency (of course nuanced data requires flexible reporting capability);

(3) By digging into your data and acquiring better data, or even better still by encouraging customers to exposure their data to you, or co-create data, you can come to a real estimation of risk (in this example mortgage payment risk).

(4) Nuance gives you the opportunity to re-segment and gain insight.

(5) New insight create the opportunity for new Interaction patterns.

At VoiceSage we have reason to work with quite a few companies on issues such as late payments on personal loans, on mortgages etc, and mostly these customers have very professional systems and organisations for addressing these issues. I just wonder how much nuance is being lost by taking "data" at face value, and how much more "nuance" might be able to add value.

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