How to avoid calculating an ROI for your analytics project

There is an embarrassment of options for justifying the investment in an analytics solution, yet so few ROI models exhibit the correct combination of Kevlar and Teflon needed to survive the Dragon’s Den/Shark Tank experience. But people still invest in business intelligence, data warehouse and analytics solutions. So how are they funded?

Perhaps some of the reasoning is to be found in the McKinsey article, Do or die questions boards should ask about technology.

It reaffirms our experience at Mariner where an analytics project tags along as a line-item within a larger initiative that enjoys sufficient ROI to be approved. Often those investments are related to improving the customer experience where analytics can play a familiar role.

Exhibit 1 in a much earlier study on how companies make good decisions  offers some additional advice on the types of strategic investment you can align your project to,  with “expansion into new services, products or geographies” and “organizational change for other reasons” being the top two.

An ROI calculation is probably de rigueur for submittal during an annual planning process, but the report also advises 70% of decisions are made outside of the annual planning process. Possibly this is where an ROI might not be required. However the report’s first recommendation snaps you back to ROI expectations by advising creation of a ‘detailed financial model’ and a risk assessment, per my earlier post, be part of any decision making process.

In addition to the inspiration from those two reports, you can also appeal to a visionary within the organization who has enough discretionary budgets to allow you side-step the ROI process and just get on with delivering something unique.

With tools like Tableau and Power Pivot you can create analytic solutions in a few weeks, often combining data that has never been combined before. Showing what is possible with the data you already have and being able to share that information with others recruits advocates. Not always, but often there is a role reversal. The conversation shifts from, “Why do I want this?” to “Now we are going to do this other thing I have been thinking about.” Some call this moment the “sharing of Ahas” and coincides with the optimal cycle of locking up and liberating data.

If all those options fail you, then wait for the end of the fiscal and pounce on any unspent budgets. I suggest you look at exhibit 2 of how companies make good decisions to evaluate your chances.


Peter Darragh

Peter Darragh

Vice President of Delivery at Mariner
In his business development capacity Peter helps executives evaluate the impact digital investments can have on their business models and operations. In his delivery role, he manages the teams that apply their data integration, analytics, process automation and machine learning expertise to make our customers digital masters.

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