Data Driven Decision Making …

There are many considerations when developing Data driven decision making (DDDM), and one of the most critical is an understanding of the difference between data and information.

I’m not a big fan of the term “Data driven decision making” as what really drives timely decisions is information. Data is raw, uninterpreted facts, while information is the result of organizing, processing, and interpreting data. Figuratively speaking, data is a stack of lumber; what you make of it can range from your dream home to a bonfire. Data is collected; information is constructed.

DDDM is nothing new but it doesn’t always come easy for small to mid-sized organizations. Standard accounting software may be limited in its capabilities, and even more robust ERP systems can lack the built-in capacity to dig into the nuances of a specific industry, organization, or situation.

In developing real time information, key performance indicators (KPIs), or other DDDM metrics, the first step is to determine what information the user needs and how they are going to use it. Data collection comes next. While the finance and accounting function can play a critical role in the process, it must be a collaborative effort with the users (e.g., sales, marketing, operations, etc.). Not all data needed may naturally flow through the accounting system and will need to be sourced appropriately.

The problem with not having an organized process in place to develop and create actionable information is that those needing the information are likely to come up their own out of desperation, risking both inconsistency and inaccuracy. I once consulted with an organization in which four or five people needed the same information for planning and decision purposes; lacking an organized system or oversight, they each developed their own Excel based models – no two of which came up with the same results. We’ve seen many similar situations.

A few things to consider in developing a useful DDDM system:
  • First determine what information (not merely data) is needed and how it will be used. This should involve the expected end users, accounting & finance, and other relevant parties. Do not depend solely on the accounting function.
  • Use your ERP/accounting software to the extent you can before considering third-party add-ons or other options. We encounter many situations in which elaborate work-arounds were developed without considering – or even been being aware of – built-in tools that were already available.
  • Avoid what I call “Excel-eration”, the stampeding development of uncontrolled Excel workarounds by needy users. Excel models shouldn’t – and probably can’t – be entirely avoided, but be sure it’s the best option and not just the most expedient.
  • If you are considering industry-specific accounting and ERP systems that promote DDDM tools specific to your industry, don’t dive in without checking the water. See how many installations they currently have; be wary if it’s only a few hundred or less. Ask to chat with current users. Your industry may be too small a niche to warrant a large user base and the support that goes with it. We’ve seen several companies drawn by industry-specific promises that weren’t kept due to inadequate support levels.

Real time information and Data driven decision making are critical to successful operations, and even more so in this era where quick pivots can be life savers. Be sure of what you are building; bonfires are nice, but go for the dream home.

About the Author

Brent Morrison is the Founding Principal at Morrison. To get in touch with Brent, please find contact information for Morrison here.


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