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Which processes should one optimize first?

“The noblest pleasure is the joy of understanding.”

-Leonardo da Vinci

Process optimization is one of the most important activities businesses can currently be engaged in. In their report “Perspectives on global organizations” strategy consultancy company McKinsey stated that “strengthening processes is crucial” and that “companies can miss up to hundreds of millions by not standardizing processes” [1].

This is especially true in the insurance industry. This industry has been ‘plagued’ by negative press, increased supervision, increased life expectancy and a reasonable to bad performing economy. This has resulted in a decrease in premium income and also a stop in accepting new customers in existing product lines (the closed-book products). The only way to increase market shares and to satisfy shareholders while also making sure that policyholders rights are protected, is by cutting costs in the form of optimizing processes.

Doing this is easier said than done and many theories exist on how to optimize processes, but which should one do first? The answer which is normally stated is: the one with the biggest ROI, but in this document a different approach will be suggested. The approach that I suggest is: take care of the easiest processes first, despite their respective ROI.

To understand this, let us first think of our processes in terms of their benefits and ease of implementation. If correctly done and correctly quantified, we could list all processes in a graph. In figure 1 a theoretical situation is displayed where the x-axis represents the benefits going from low to high and the y-axis represents the complexity which goes from high to low (click to enlarge).

Figure 1: Graphical representation of a process analysis where processes are plotted against their possible gained benefits and complexity of implementing the optimization.

In figure 1 the process first to be optimized is of course A. This process has the highest benefits but is also the easiest to implement. But what happens if the process is successfully optimized? This can be seen in figure 2 (click to enlarge).

Figure 2: Graphical representation of a process analysis where processes are plotted against their possible gained benefits and complexity of implementing the optimization and what happens when one process is successfully optimized.

As can be seen, the complexity decreases (please note that the y axis is inverted). The other processes become easier to optimize. This is because:Figure 2: Graphical representation of a process analysis where processes are plotted against their possible gained benefits and complexity of implementing the optimization and what happens when one process is successfully optimized.

  • There is an increase in lessons learned concerning process optimization which can be used to improve the process of optimization itself as some features can simply be copied (especially true when building software)
  • The overall motivation to optimize processes is increased by the gained success (with a fail the processes also decrease)

 

The copying or lessons learned value is widely recognized and is easy to understand. If I have to make product 1 for project A and product 1 and 2 for project B it is better to do project A first because then most of the work of project B is already done. It is doing things in such an order that during the longest path small projects can be easily done.

However, more important is point 2, which is creating success after success. This makes organizations more likely to accept change. That is because people are more willing to take risks if this previously resulted in success. For one thing the motivation “but this is how we have always done this” no longer applies when small changes have been implemented. With success the sceptics are silenced and the innovators are more seen.

This is especially important in our current era of massive disruption. Organizations need to be flexible in order to meet market demand and competition. This means having willing and capable employees who are not resistant to change. These people cannot be recruited, but they have to be trained and therefore doing small things first is the way to go.

[1] http://www.vcloudnews.com/every-day-big-data-statistics-2-5-quintillion-bytes-of-data-created-daily/

[2] https://www.youtube.com/watch?v=mCDkxUbalCw

 

Wouter Mertens

Business Manager IT

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