What are the Top Reasons for Measuring ROI?
By Clinton Jones on October 28, 2015
Ok, maybe this question has a few obvious answers – but sometimes when we start thinking about measuring ROI, it feels like we’re not reaching the right results, so we abandon the idea in favor of something else.
ROI analysis, when done appropriately, is considered a powerful way to evaluate an organization’s investment and make informed decisions on future investments.
In the past, ROI was widely used as a financial term and defined as a concept based on the rigorous and quantifiable analysis of financial returns and costs that would flow from an investment. Today ROI is widely recognized for proper financial management in both the private and public sectors.
ROI analysis and calculations used without careful consideration have resulted in mixed approaches prone to inaccuracy and bias.
Though the formula for ROI is relatively straightforward (Gain – Cost)/Cost, the way the costs and the gains are calculated can be manipulated to result in a gain that is higher than it should be, or a lower cost and vice versa. The objectives of the person making the calculation, and the quality of the inputs will determine the end result.
The go no-go decision
The most common reason behind an ROI calculation is a justification for an investment. The justification is typically a prerequisite from those requesting the investment in order to justify the purchase, effort or expense. When resources are scarce, an ROI calculation is often a fall-back to seriously and critically evaluate the need for the investment.
Sometimes the request for an ROI justification will kill an idea that may have merit. When opponents have reservations about the investment being trivial or ill considered, the justification may be at risk.
However, ROI doesn’t always have to fall under the financial umbrella, even though ROI metrics like time savings, business confidence and data quality can ultimately have a financial cost attribute.
Getting “bang for your buck”
Traditional ROI requires defining a yield, timeline and degree of confidence about the predictive model. The best ROI calculations represent transparent metrics and carry a degree of accountability or consequence.
In other words, if you believe that automating a process will yield productivity or time savings, then you need to describe the throughput of that process in terms of activities, documents etc. and define what the source of those metrics will be.
There are many potential ROI metrics to consider for automation initiatives, but here a few that I plan to cover in future posts:
- Throughput volumes
- Quality, Accuracy and Precision Improvement
- Timeliness of decision bound actions
- Costs that could be averted
- Confidence in the end-to-end process
About the author
Clinton Jones is a Director for Finance Solutions Management at Winshuttle where he has worked since 2009. He is internationally experienced having worked on finance technologies and business process with a particular focus on integrated business solutions in Europe, the Middle East, Africa and North America. Clinton serves as a technical consultant on technology and quality management as it relates to data and process management and governance for finance organizations globally. Prior to Winshuttle he served as a Technical Quality Manager at SAP and with Microsoft in their Global Foundation Services group.
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