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According to latest Forrester Research report, satisfaction with BPM software is rapidly declining.
More and more companies are dissatisfied with the results delivered by the business process management (BPM) software they have implemented. In just the past two years the number of satisfied companies had dropped from 60% to 30% according to polling of over 3 600 business and technology decision-makers surveyed in 2015 and 2017.
It is no surprise that at the same time as satisfaction with BPM is hitting an all-time low the Process Analytics Market is snowballing and is now expected to be worth 1,421.7 Million USD by 2023. This growth is driven by ever-increasing awareness of the necessity for analyzing and understanding business processes.
BPM systems used to be regarded as a way to manage workflow and "glue together" the various siloed functions across an organization that together constituted an end-to-end customer interaction.
However, today BPM software is expected to provide much more than a simple cost reduction or management of employee productivity. More and more companies are planning their process improvement and automation initiatives to deliver end-to-end digital transformation and improved customer experience.
The reason why so many BPM initiatives implemented just a few years ago failed to deliver, could be attributed to the immaturity of the underlying analytical process. Most of the time the information gathering was manual - a team of consultants would spend weeks interviewing process participants to gather information about a process. The results of such an approach are naturally flawed: human perspective is subjective, each person has a limited view of the picture, exceptions can be amplified or excluded, and some parts of processes are invisible.
A related reason for the growing dissatisfaction with BPM can stem from the lack of change management within most of the process transformation projects. Change management always plays a vital role in the success or failure of every business process initiative and accurately measuring the impact of changes on the process and its participants has been notoriously difficult to achieve. Failing to address the real concerns of those affected by process changes may cause anticipated results to stop in their tracks. The process of change management needs to be monitored, evaluated and frequently revisited. Read more about the top reasons BPM initiatives fail here.
When organizations have to rely on manual process analytics approach and dig through participants’ subjective views, accurately qualifying the impact of changes it is challenging.
As one of the fastest growing Process Analytics technologies Process Mining provides the answer to issues mentioned above, by analyzing real data from systems involved in the daily running of your business to paint an accurate picture of the process. Software such as Minit, can take process logs created within various IT systems and automatically generate a process model to enable in-depth analysis. Process Mining provides actionable insights by highlighting problems that need to be addressed by BPM and represents an accurate and cost-efficient way to repeat the process analysis to sustain and monitor process change.
According to the Forrester Report, for most organisations, the primary driver of process improvement efforts by 2020 will be to accelerate digital business transformation. Digitized processes are becoming the new competitive differentiator and a way to attract customers who require the same excellent customer experience regardless of the channel. In addition, 49% of the respondents expect digital transformation to become the key driver of their process efforts within the next two years.
The Process Analytics Market will continue to grow as the acceptance of innovations becomes more and widespread. Companies will need to increasingly adopt process analytics solutions to identify undiscovered risks and improvement opportunities in their enterprise processes and become more technologically advanced and efficient at driving effective operational processes.