Optimising financial processes

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Data Driven Decision Making and the “Great Data Dichotomy”

Exploiting Data is CRITICAL to our business” is an assertion that is not going to shock anyone. It’s like saying “we are customer focused”, “process driven” or “kind to animals”. 

These are platitudes, even cliches.

Asked how CFOs are redefining the finance value proposition, the most common survey response is through Data Insights and Analytics.

What will enable finance to drive the greatest value-add to the enterprise? “Data Analytics” came a very close second to “Digitization”.

Taken from two current CFO surveys, which I share below, these priorities resonate clearly.

Thereafter, the narrative gets confused, with a focus on technologies rather than business objectives and target outcomes for data.

This is a common mistake. 

A costly mistake, in terms of poorly utilized effort and cash as well as in lost / delayed business opportunity.

The “Data challenge” is often described as an engineering problem, requiring armies of data specialists who should drive the data exploitation strategies.

Whilst there are parallels with engineering (you need to understand purpose, form and function and develop a blueprint), this analogy is wide of the mark.

Consider data like we think about cash. We have a treasury function to manage it but business leadership decides how to use it, and where/when it should be deployed.

If data-driven decision making is the goal, the biggest challenge is end-to-end process understanding because the CONTEXT of Data in business is PROCESS!

Near real time data insights enable “data driven decision making” which itself facilitates operational agility and speed of change in response to, or anticipation of, events.

Data driven decision making enhances resource allocation, business partnering and cross functional alignment.

The two reports based on surveys with CFOs, hot off the press, sharing perspectives and the future of the finance function hit my email yesterday, from Shared Services & Outsourcing Network (SSON) and IBM Institute for Business.

They diverged on some themes but were in agreement that data, analytics and insights, and thus data driven decision making, are key priorities.

BUT, they also reflect a common view that this is a technology issue that we have cracked, rather than a business process strategy that most are still wrestling with . . .

There are 5 BIG challenges to get us to data driven decision making and they are largely non-technical. They are business challenges

  1. Driving Performance Improvement – our confusion between lagging and leading KPIs, the latter being the real “Performance Drivers” ,
  2. Business Process Knowledge, Expertise & Best Practice – the fundamental need for any support for data driven decision making.
  3. Data context and complexity – identifying and relating the required instance of a data item to a specific business problem or question.
  4. Speed, Time to Value – how to shorten the lead time to business value.
  5. Cost & Effort to deliver – are we deploying our valuable resources in the right place?

The Great “Data Dichotomy” is alive and well, but with focus on these core business issues and a healthy application of “Pareto Principle” strategies, we can evolve to genuinely agile businesses.

You can access both reports here . . .  and here . . .

Thanks for reading . . .