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The true cost of being data driven

19th May 2021

Author Alex Waleczek

What’s your Total Cost of Ownership for Analytics…? And what about your Total Cost of Impact?

When working on a larger project to purchase something for an organisation, you will likely have considered the Total Cost of Ownership (TCO) as part of the decision process. TCO acknowledges the fact that the initial purchase is only part of the cost you will have to pay over the coming years and going with the vendor that has the cheapest upfront costs might not be the best choice considering direct (cost to scale, maintenance agreements, etc.) and indirect (training, effort of administration, etc.) costs.

While a very sensible approach, you will have to make some solid assumptions to get an accurate comparison, and no matter what vendor you go with, they will ensure you that their platform has the lowest TCO for your situation.

For Analytics platforms in particular, I think there is an additional metric to think about: the Total Cost of Impact (TCI)!


Total Cost of Impact

The TCI is a concept more than an actual measure, the problem being that it is impossible to quantify in advance and probably not even retrospectively. At the core of this concept is the acknowledgment that being data-driven means two things:

  1. You have data that can provide insights to base decisions on
  2. You take those decisions and act upon them

Being ‘data-driven’ is a trait that fits very well in our connected world that is largely dictated by data and algorithms, but unfortunately the planning often ends after the ‘data’ part. It’s not enough to just simply discover new insights. The value of these insights is only truly unlocked once you act upon them, which often requires change.

This change may involve small adjustments, for example the KPI you are using, or a big shift in the direction of the business; either way, these changes will come at a cost.


But…we have always done it this way!

The impact of data is usually small when the data confirms our assumptions. If we “know” a fact to be true and the data supports this, we see the value in analytics. If the data contradicts our assumptions (or even worse, the assumptions of our bosses), we often question the data rather than our beliefs.

This is often the point at which the “it has always been this way” attitude kicks in. It represents the reluctance of people and businesses to do things differently. Having said that, I have never heard anybody say it exactly like this. Instead, this mindset comes through much more subtly.

People in the business will say something like, “We know that product X does particularly well in the first two weeks in November.” And before you know it, this becomes gospel throughout the company.

Others might not dare to even propose new ideas because they are afraid. I know of businesses where just the idea of an interactive exec dashboard that would free up hours of time and give daily instead of weekly updates was initially dismissed because “the execs want it in PowerPoint”.

When you want to become data-driven, you’ll need a good platform to work with the data and generate insights, but the best platform won’t make you data-driven unless you act on these insights and accept the cost of change.

As I said at the start, it’s likely impossible to put an actual price tag on it. It will be indirect costs for doing things differently or for being a bit more inefficient in the short term to gain productivity in the long run. You will likely also have direct costs, for example for hiring new people or restructuring the business, or you might need to forfeit revenue to set yourself up for long-term success.

A case in point: Netflix famously dropped their DVD sales business which made up 97% of their revenue to focus on rentals instead. The main reason was Amazon, who at the time was also about to sell DVDs, which would have crushed Netflix in the market.

Keep these aspects in mind when starting your journey to be data-driven. Be aware that becoming data-driven doesn’t just mean buying a fancy analytics platform; it means shifting a culture to be open and supportive. A good analytics platform is only a tool to get there.


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Alex Waleczek is Davanti’s Practice Lead – Analytics. 

In his role he is responsible for all things data. Having worked as a consultant with Tableau in the analytics space in New Zealand for the last six years, he is very familiar with the problems companies face when trying to make sense of their data and how to solve them to bring our clients closer to their clients. When he is not working on Tableau for Davanti, he is blogging privately about all things data and hiking New Zealand. You can get in touch with him via our contact form, LinkedIn or Twitter.

Alex Waleczek