If Data Projects Weather, Why Not Corporate Revenue?

Every fall Informatica sales leadership puts together its strategy for the following year.  The revenue target is typically a function of the number of sellers, the addressable market size and key accounts in a given territory, average spend and conversion rate given prior years’ experience, etc.  This straight forward math has not changed in probably decades, but it assumes that the underlying data are 100% correct. This data includes:

  • Number of accounts with a decision-making location in a territory
  • Related IT spend and prioritization
  • Organizational characteristics like legal ownership, industry code, credit score, annual report figures, etc.
  • Key contacts, roles and sentiment
  • Prior interaction (campaign response, etc.) and transaction (quotes, orders, payments, products, etc.) history with the firm

Every organization, no matter if it is a life insurer, a pharmaceutical manufacturer, a fashion retailer or a construction company knows this math and plans on getting somewhere above 85% achievement of the resulting target.  Office locations, support infrastructure spend, compensation and hiring plans are based on this and communicated.

data revenue
We Are Not Modeling the Global Climate Here

So why is it that when it is an open secret that the underlying data is far from perfect (accurate, current and useful) and corrupts outcomes, too few believe that fixing it has any revenue impact?  After all, we are not projecting the climate for the next hundred years here with a thousand plus variables.

If corporate hierarchies are incorrect, your spend projections based on incorrect territory targets, credit terms and discount strategy will be off.  If every client touch point does not have a complete picture of cross-departmental purchases and campaign responses, your customer acquisition cost will be too high as you will contact the wrong prospects with irrelevant offers.  If billing, tax or product codes are incorrect, your billing will be off.  This is a classic telecommunication example worth millions every month.  If your equipment location and configuration is wrong, maintenance schedules will be incorrect and every hour of production interruption will cost an industrial manufacturer of wood pellets or oil millions.

Also, if industry leaders enjoy an upsell ratio of 17%, and you experience 3%, data (assuming you have no formal upsell policy as it violates your independent middleman relationship) data will have a lot to do with it.

The challenge is not the fact that data can create revenue improvements but how much given the other factors: people and process.

Every industry laggard can identify a few FTEs who spend 25% of their time putting one-off data repositories together for some compliance, M&A customer or marketing analytics.  Organic revenue growth from net-new or previously unrealized revenue is what the focus of any data management initiative should be.  Don’t get me wrong; purposeful recruitment (people), comp plans and training (processes) are important as well.  Few people doubt that people and process drives revenue growth.  However, few believe data being fed into these processes has an impact.

This is a head scratcher for me. An IT manager at a US upstream oil firm once told me that it would be ludicrous to think data has a revenue impact.  They just fixed data because it is important so his consumers would know where all the wells are and which ones made a good profit.  Isn’t that assuming data drives production revenue? (Rhetorical question)

A CFO at a smaller retail bank said during a call that his account managers know their clients’ needs and history. There is nothing more good data can add in terms of value.  And this happened after twenty other folks at his bank including his own team delivered more than ten use cases, of which three were based on revenue.

Hard cost (materials and FTE) reduction is easy, cost avoidance a leap of faith to a degree but revenue is not any less concrete; otherwise, why not just throw the dice and see how the revenue will look like next year without a central customer database?  Let every department have each account executive get their own data, structure it the way they want and put it on paper and make hard copies for distribution to HQ.  This is not about paper versus electronic but the inability to reconcile data from many sources on paper, which is a step above electronic.

Have you ever heard of any organization move back to the Fifties and compete today?  That would be a fun exercise.  Thoughts, suggestions – I would be glad to hear them?

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