A major part of Business Process Management (BPM) is to understand how processes were executed and to find out ways to improve current processes. In order to do this we need execution data. But how much data is needed? Answer is, the more data we can collect, the more we can discover.
How do we collect data during process executions? If there is a process step which involves an employee filling a web form, it can easily generate data about who filled the form, start and end times of filling the form, values entered, etc. But what about process steps that do not involve someone entering data into a computer.
Let’s take the below shipment process. When a package has to be shipped, an employee fills shipment details in a system. Then the package is transported to a port and shipped. Once the package is received, a user sends an acknowledgment message through the shipment system.
We can easily collect data on first and last steps as those are done through the shipment system. We can perform some process analysis from that data as well. For example, by considering start time of the first task and end time of the last task along with shipping destination for each shipment, we can derive average time for shipping a package to a given destination. However, we can’t say much on what happens during the shipment process as we don’t have data on loading the package, transporting the package using a truck and shipping the package. This is where IoT helps in business processes…
Let’s assume that each package is tagged with a RFID. Further, each forklift, truck and ship has RFID readers, which can track all packages it currently holds. In addition, operators of forklifts and trucks wear RFID tags so that corresponding forklift/truck can track its operator. Then each vehicle sends events about its actions. For example, forklift sends the below event when it picks up a package:
<forklift id, package id, pick up time, operator id, location>
Furthermore, an example event sent by a truck when a package is loaded can be:
<truck id, package id, loaded time, driver id, location>
These events can be captured by the shipment system, so that it has data on each intermediate process step in addition to the two steps with direct user involvement. With this addition data, we can do more detailed process analysis such as which steps have most waiting time (i.e. in which places a package sits idle without being transported), how many packages got delayed due to traffic congestion, who are the most efficient forklift operators, etc. Thus, if a process step is performed using a IoT enabled device, execution data on that step can be captured and used in process analysis.
Process execution analysis is not the only area where IoT can help. Events sent by IoT enabled devices can be used for other important functions such as enhancing process models (e.g. by identifying missing steps), discovering new process models from event streams, automatic task completion by integrating events directly into process runtimes, etc.