Companies are investing millions in digital transformation. A successful digital transformation delivers the intended business objectives. These business objectives include new business models, better customer service, process optimization, productivity and efficiency improvement.
You would want to monitor whether the business objectives are realized. You also want to understand how the implemented changes align and support the objectives so you could refine and adapt. Let’s explore what to monitor.
- Business objectives
A successful transformation is shaped by the business value it delivers. The expected value defines the type of technology to be implemented, scope of change, and the extent of investment.
The capabilities needed to offer digital services online are different from those necessary for mechanizing warehouse operations.
In order to measure the realization of business objectives, define specific outcomes. For instance, new revenue to be delivered, or savings from mechanization. Ensure there is a way to monitor the outcomes with accuracy.
- Supporting drivers
Transformation introduces extensive changes including modification to processes and job roles, and integration of new technology to legacy applications. These changes are linked, so it would be beneficial to identify the linkages and monitor them.
For instance, transforming a food wholesaler’s warehouse operations via the implementation of a warehouse management application promises higher efficiency. The business value is not the number of processes mechanized. The real value is the gain from eliminating errors and duplicate order entries, as well as providing sales reps with up-to-date inventory information to avoid backorders.
The main business objectives for the transformation are labour savings and enhanced customer satisfaction. Sample supporting drivers are order picking accuracy, stock-out frequency, and backorder rate.
The supporting metrics are leading indicators. Monitoring them helps to shed light on the effectiveness of the changes implemented.
- Essential operational metrics
With a new operating model, it is an opportune time to leverage the deployed technology to capture as much useful data as possible. This takes forethought on information you need to make better business decisions.
For the food wholesaler, a good approach is to identify business intelligence that would help to improve operations. As the wholesaler sells to restaurants and caterers, sound analytics on customer purchase patterns and fulfillment expectations would be helpful. Based on this, the wholesaler identifies data the application ought to capture. For instance, data on order frequency, volume, and delivery schedule would be useful for pricing and purchasing decisions.
Having the data readily available for predictive and prescriptive analytics is a competitive advantage.
- Return on investment
A business case is often created to compare investment alternatives and justify the investment. It would be good to be able to report on the actual return.
In developing the business case, many assumptions are made. The possibility of the final solution delivering fully what was expected is low. Hence, the results and data captured in the above three areas would help tremendously with performance reporting.
The information helps to assess the post-implementation state and offers insight on where opportunities are for future changes. You have the data to validate return on investment.
Digital transformation is a disruptive but worthy undertaking. However, it is critical to put in place a measurement mechanism to monitor results, quantify improvements, and gather intelligence for proactive business management.