How efficient is an organization at executing? Efficiency is defined by a number of parameters: quality, cost, and duration. In this article, we will be looking at duration. When thinking about your own organization, you can probably find many examples where duration is a yardstick for efficiency. Customer service, order delivery, and production flow could be such examples. All three examples are processes.You may have actual numbers or just indications of the duration of these processes, but can you break down the duration of each step in the process? We often find that the data and information we have on hand does not provide enough granularity to focus our improvement efforts. The deeper you can track your engine room, the better you will be at improving efficiency.
Log data (in its simplest definition) is nothing more than a continuous list of activities with a time stamp of occurrence. As a result, log data can help you calculate duration between many different activities. You most likely have an ERP system supporting the execution of different processes inside your organization. Most ERP systems can log system activity giving you the possibility to calculate duration between system activities. The beauty is that many system activities actually resemble activities being executed in the aforementioned processes. But how do you know which system activities are connected to each other inside the same process? The order number, service ticket, and production batch number are needed to link the activities together. As the log data aggregates over time, a very detailed picture of your process performance will unfold. Not only will you see detailed duration measures but also that activities inside your processes follow many different paths. Activities can repeat themselves, go backwards in the process, and/or split in different directions. You will see that your processes are not following the optimal linear path you intended when designing the process but seeing a view of reality puts you in a position to improve where it matters the most.
Let’s take a look at some examples. A purchase order process is ideally a linear flow of activities:
- Send purchase request
- Receive order confirmation
- Record goods received
- Clear invoice
The example above is quite simplified. In practice, the process could entail activities such as price changes, approval escalation, partly delivered, and pending with other orders. If your log data can capture such activities, over time you will see an aggregated picture of how these activities connect to each other in the process and the duration between them. For example, how many purchase orders require approval escalation and what is the duration of this bottleneck?
A customer service process could be regarding technical support, field service, or a warranty claim. As the customer request is received, it is ideally solved immediately. However, the service ticket could be moved around different departments and may even involve sub-suppliers. Hence, tracking both the path and the duration of this journey will unveil opportunities to shorten the resolution time.
You may have a digital footprint of your production setup. Whether we are talking mass, batch or assembly manufacturing, you will have a line up of your production facilities showing location of machinery, work stations, and work-in-progress inventory. Again, we are looking at a process where, with the support of log data, you could capture deviations, reworks and durations of each step in your production process. Furthermore, a production setup requires a variety of supporting processes such as maintenance, transportation, repair and quality control. All these different processes need to interact in order to maintain an optimal flow so why not investigate what log data, your current ERP, MES or SCADA systems can generate. It may be a step-by-step evolution of linking it all together but the outcome would be a dynamic digital twin of your entire operation.
Let’s recap. Processes are nothing more than a sequence of activities that repeat themselves. Log data contains time stamps of registered system activities. If you can identify these building blocks within your organization and IT landscape, you will have endless possibilities to extract very detailed insights on your existing performance. The devil is in the details, but the details make your improvement actions concrete and with continuous monitoring, you will quickly be able to measure the effects of your actions.
This article is written by Carsten Engelsfelt, CEO of Cenarity. We are a European based software and data processing company specialized in turning log data into valuable process insights. Just reach out on LinkedIn https://www.linkedin.com/in/carstenengelsfelt/ and I’ll be happy to continue the dialogue.