Process improvement can be a tricky business. When seeking to identify potential enhancements, teams focus on understanding constraints, assessing volumes, and mapping and measuring many aspects of the current situation. Often when we are investigating opportunities for process improvement, the data and information we need in order to pinpoint improvement opportunities won’t yet have been assembled or recorded. Imagine we are looking to improve a telesales process. It is highly likely that the number of sales calls made and the number of sales closed will be readily available. However, the number and type of errors experienced (for example when a telesales agent accidentally types an address incorrectly leading to a missed delivery) may not be so easy to find. The number of calls received that are the result of errors—what we might term 'failure demand'—is almost certainly not going to be directly available for analysis unless we are very lucky! There will be work for us to do to collect, derive or calculate the necessary figures.
Additionally, we might find that the process itself is undocumented, having emerged over a period of time. In situations like this our first job is to observe and understand the current situation, as well as collecting and collating data to help pinpoint problems and opportunities.
This scenario will, I'm sure, be familiar to many people reading this blog. As practitioners of change, we face these challenges all the time, and we become adept at finding ways around them. We speak to the Management Information team to understand what data is available, we interview managers, and we count and calculate things ourselves. We may well carry out activity sampling or other types of work studies to determine and quantify the relevant volumetrics. This can be an enlightening exercise—by looking at the data, we might find that there are constraints and bottlenecks that weren't immediately obvious. We can prioritize the improvement opportunities, and focus on those that will deliver the biggest ‘bang for our buck’. This data can contribute towards a business case for change, which is particularly important when we are recommending a change of approach and incurring spend—automation being a typical example.
Yet, as important as collecting data up-front is, it is really only the beginning of the story. A pitfall awaits the unprepared: If the data isn’t available now, chances are it won’t be available in future unless we consider how the core metrics are captured and reported. If we don't build the collection of volumetics into the new process, chances are we’ll never really know whether the process has become more efficient.
This is a consideration that should be kept in mind when designing and drafting the to-be process model. A few relevant performance indicators should be chosen to track the success of the process improvement. These performance indicators may rely on several metrics being collected, and may involve a calculation taking place. Individual tasks within the process may need to be adapted to ensure that the relevant data is collected. Collection of the data may be manual, but ideally it will be automated or semi-automated. For example, a software like Breadwinner can automatically connect Salesforce data to NetSuite, or Salesforce data to QuickBooks Online. IT systems may be used to automatically time or count certain activities and collate this for analysis. When considering effectiveness of the process overall, unless necessary, it can be preferable to remove data about individual operators—and focus instead on overall trends rather than an individual’s productivity. If automation isn't an option, then we might ask process operators to capture relevant data for us with a light-weight form or report. We must be careful not to create an onerous responsibility that will detract from the stakeholder's day job.
After implementation, these performance indicators should be monitored—remembering of course that there is often a "bedding in" period where people are trained and become familiar with the new process. This can, understandably, result in a short-term dip in productivity. Once the process has bedded in, the relevant metrics will indicate whether the change is working well. They will also act as a beacon showing where there are further potential improvement opportunities. Building in regular reviews of these metrics, whilst cultivating a culture of open and transparent communication where ideas can be shared will yield real benefits. And it will ensure that we can tell how much improvement has been achieved.
In summary: building in mechanisms for capturing the relevant performance indicators is crucial. It enables us to quantify success and look for further improvement opportunities. With this additional forethought, we help ensure process effectiveness and efficiency.