Measuring the ROI of a Data Analysis Project? Read this FIRST!

Nov 19, 2018

When you invest in a piece of machinery, like a heating system, calculating your ROI is straightforward. You know the cost of the equipment itself and your past heating bills, and you can confidently estimate how much less you will pay over time based on the increased efficiency of the new unit.

But what about the cost of data analysis software? How do you figure out the ROI on something as intangible as software?

Whether your leadership team is a three-person group of partners or a ten-person C-suite, you’re going to have to explain the return you will get from investing in data analysis software solutions. The key is to know what you’re measuring up front BEFORE you invest. Believe it or not, we’ve actually seen some large companies get halfway through a build before asking the ROI question.

Considering the ROI of any new data analysis solution can save you money, time, and frustration. Even if you are already down the path of implementation, you can look at the ROI – and change course if you don’t like what you see.

5 Factors to Consider as Part of Your ROI Analysis

1) The breakdown of the costs
Review your costs in detail. Are there any mystery fees that you need to clarify? Make sure you know exactly what you will be paying and why. Don’t forget to include any recurring costs associated with keeping and maintaining the solution.

If you have already started paying for your new solution, how do your bills compare with the original proposal? Are you paying more than you anticipated?

2) The quality of the work done
When you’re evaluating options, picture yourself sitting down at your desk and opening this tool. Would it actually make your workday easier? How is it better than what you are using now?

If you’ve already begun implementation, try to gauge buy-in from the team. Are your people genuinely enthusiastic about the new direction, or are they putting on a positive face for the boss? Do people trust the reports that are generated, or are they still running parallel systems (sometimes months later!) to cope with errors and glitches?

3) The progress as you move through implementation
Talk to the company’s references. Find out how long it took other clients to get the system running properly. Were their questions taken seriously, or were they basically told that they had to fit their business around the software?

4) The cost savings
How is this solution going to save you money, especially on overhead? Will the new system eliminate any time-sucking manual processes and data entry, or does it just introduce more complexity? Can you see anyone’s To-Do List actually getting shorter as a result of transitioning to this software?

5) The vision of your company that it provides
Will this tool give you a clearer picture of your company? Will you get the information you need to make better, faster business decisions? Can the software help you identify any weak links that you can shore up to increase productivity and profits?

Lastly, there’s a myth that you need a big-name software firm to design these solutions for you. We don’t think that’s true. Not only are you paying a premium for all the prestigious branding, you could still be getting a poor-quality product that won’t save you time or money in the end. Frankly, sometimes, they’re trying to mold your needs into their ready built solutions.

I’ve seen far too many companies invest huge sums trying to salvage software solutions that shouldn’t be saved. Those sunk costs are dragging them down like an albatross. By figuring out the ROI of data analysis projects upfront AND working with a smaller firms (Like G7), companies get customized, streamlined solutions that actually work — without all the bloat of the big boys.