I thought I would start with a few questions for the reader to better position my thoughts. Just some food for thought!

• How many customers look back 12-24 months following implementation and measure their success?

• How many BI initiatives include the trust-factor and evaluate data confidence respective of the measures they supply to the business?

• If a single metric can only be calculated using 50% of the available transactions due to a lack of quality, would you consider that metric trustworthy?

• How many change management programs develop metrics to measure process acceptance / compliance as it relates to system adoption rates, and then apply these metrics following go-live?

My buddy, Stuart Barnes, wrote an excellent post on how organizations struggle with addressing data quality issues with their enterprise systems (ERP, EAM, GIS, etc.). Stuart’s post dovetails nicely into my beliefs on this topic. (See post here: http://bit.ly/29udSRd)

The independent research that Stuart references highlights the major causes of data quality issues in enterprise systems. The research states poor data quality is predominately caused by (1) data-entry errors by employees – 57.5% and (2) mixed-entry [lack of consistency] by different users - 44%.   Stuart points out that most of the blame for poor data quality unfairly lands on IT, but in reality it is due to the use of the system by the business. I couldn’t agree more and would add to Stuart’s point that, if you want to fix and overcome data quality, the business needs to own the process and ensure proper and consistent use of the system…not IT.

With over 25 years of experience implementing ERP and EAM systems, hands-on experience proves that implementation project success boils down to a rigorous change management program during implementation and an ongoing performance management program following.

Customers spend enormous amounts of resources and capital dollars implementing transformational projects justified by large anticipated returns on investment. However, the great majority of these transformations rarely achieve their intended ROI due to inadequate change management and performance management strategies. 

I have seen how client-side change management emphasis can be soft on the human and cultural impacts of implementation, then stop altogether shortly after the system goes live. Before long, it’s back to business as usual.  In my company, we strongly believe that an effective change management program is not only necessary to overcome the challenges associated with end-user acceptance, but it  also has a profound impact with respect to minimizing data quality issues.  However, no matter how effectively executed the change management program is, it will only tee-up the potential for total success because it does not fully address the long-term sustainment necessary to fully make the cultural transition. That is where Performance Management comes into play.

Performance Management should be viewed as the next link in the chain because it offers an ongoing process (following implementation) that focuses on objective achievement through the sustainment of performance goals and continuous improvement.

In order to sustain and/or improve the business, we need to measure performance by looking at the effectiveness of our improvement efforts (e.g. our transformational ERP project). As Stuart eludes, when we measure performance, we must factor in data quality. In doing so, we establish the transparency necessary to discern good data from bad, identify the source of bad data, and ensure the decisions we make are based upon trustworthy information. Having this kind of information at our fingertips is powerful because it allows organizations to identify where additional reinforcement is needed to ensure change sticks. The remainder of performance management can then focus on managing the responses to address those behavioral impediments and taking proactive actions through continuous improvement to extend performance. This is how my company, Cohesive Solutions, Inc. moves customers along the continuum to operational excellence.  

Hopefully the questions that I posed above have better context now.   I welcome your responses and your thoughts as well.

Want to learn more? Check out our blog post on How To Choose the Right KPIs for Your Organization!