I recently attended an IT vendor customer forum where there were some bold claims made related to the ROI for Business Analytics applications. The vendor cited research from Nucleus Research that stated for every $1 invested in implementing Business Analytics projects there would be a $10.66 return (Analytics pays back 10 dot 66 for every dollar spent). This research begs the question: what is the single most important requirement for companies to realize a successful Business Analytics project? I argue that it is access to clean data. Further, I argue that a higher ROI is realized by investing in data quality projects at the transactional system level.
The logic is similar to that of the value of compound interest that I learned about in my late teens (and wish that I had listened to). This logic states that if you diligently invest a small percentage of your total net earnings every month, and you also reinvest the interest (earnings) from your investment, you will realize addition interest on your reinvested interest, and so on and so on – realizing significant incremental compound earnings – and early retirement!
There is a parallel analogy related to how we traditionally calculate total ROI for transactional system data quality-oriented projects (i.e., ERP, CRM, SCM, etc.). It is here where you need to widen your ROI aperture to capture the total positive impact on the business.
For example, you may have identified a 50% ROI for every $1 spent cleaning data (and keeping data clean) at the transactional level, attributed to things like lower business process interruption (and happier customers). However, you probably didn’t factor in a portion of the downstream ROI created from business benefits realized through downstream Business Analytics applications that rely on your good, clean transactional system data:
Information oriented applications
Data Marts and OLAP cubes that integrate data from disparate systems to create a single view of household truth;
Intelligence oriented applications
Business Rules Management that automates business processes and enables escalation pathways that require manual intervention; and
Insight oriented applications
Data Mining applications that provide for predictive analytics and the discovery of new trends.
IBM states that ERP suites typically account for 30% of EDW data – and the remainder coming from other operational systems like CRM, HCM, SCM and other sources (external and internal alike).
So, the next time you’re calculating the ROI for a $1 investment to move your ERP data quality a bit closer to your dreams of six sigma (Data and Information Governance at Johnson-Johnson) look beyond the $0.50 ROI calculation benefits that you will realize from your improved transactional business processes; remember to factor in – and make a claim for – a chunk of the $10.66 ROI associated with the compound value your data quality initiative provided to those downstream Business Analytics applications.
Finally, with 70% of CIOs rating investments in Business Analytics applications as # 1 or 2 on their priority list (2012 Gartner CIO Agenda Survey results), someone needs to tell them that there is likely a transactional data quality initiative on their critical path to success.