Recently, Elon Musk was interviewed by about SpaceX’s five-step design process and manufacturing process. He echoed the thoughts of every process excellence analyst: “The greatest error is to optimize something that shouldn’t exist.”
These words are very relevant to digital conversion. Many innovation centers and excellence are trying to optimize business processes when they should be looking at what processes shouldn’t exist or how to eliminate them. They make the same mistake Musk admits to having made – they automate first.
Automation without understanding the process can have costly consequences. New research shows that 1-in-5 decision-makers abandoned their automation project, while 1-in-3 didn’t use it as planned or found it not to work as they had hoped.
There are many vendors that insist on optimizing first and automating second. Musk’s perspective begs the question: “Can process mining add to my automation projects?” Many organizations believe so, given the rapid growth of this advanced technology in recent years.
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Recent statistics show that the market for process mining software will increase by 42% to nearly $7 billion by 2028. Technology is not without its challenges. Organizations must recognize the potential benefits of the software in order to reap the full benefit.
We offer strategies to help you succeed with process mining and the next-generation approach: Process Intelligence.
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Process intelligence is a valuable tool for improving process behavior. A process behavior is a set of steps that occur or do not occur during a procedure, or where steps are repeated. It is important to consider the sequence of steps.
Is one step more important than another? Are steps that happen before or after another step possible? It is common to use different fields, such as customer or department when filtering data.
These are important, but there are many more things you can know when you have a digital duplicate of your processes. This is where the events that create them are created.
You can use the process steps’ raw data to create a model. This allows you to define process behavior. Then, you can query against the behaviors to distinguish process instances that exhibit certain behaviors from those that don’t.
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Is a step time-consuming or takes longer than a threshold? You could, for example, set a threshold that a step should not take more than an hour from the time it starts to be completed. Then, investigate inefficient steps that caused it to take longer.
Although this may seem simple, it is impossible to find all the information needed to evaluate behavior.
We wouldn’t still be able to answer time-related and behavior-related questions if the data wasn’t organized and understood in a series of steps.
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Advanced process intelligence, however, generates the process model out of the data and provides the tools to specify these behaviors. Then, it evaluates all instances of the process against these behaviors.
Analysts of process excellence wish that a control plane could automatically monitor distributed operations and take appropriate action when necessary. Process intelligence, which is a data-driven, bird’s-eye view of all your operations, can help you gain a complete understanding of the processes.
Industry leaders can make better decisions at the moment by using a non-bias approach that is based on facts.
This visibility will allow you to see exactly what your processes do and answer questions such as: How automation can improve customer experience? What employees are most consistent and efficient?
What are your bottlenecks and how can they impact compliance and delivery of services? You can improve your supply chain efficiency, as well as the purchasing and sourcing processes. You can also discover, analyze, and monitor the real workings of your procurement process.
“You are able to uncover delays that cost money and time, and find the most efficient process paths for positive business outcomes.”
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An alternative way to guarantee process execution success is to use Process Behavior as an analytical dimension. As an analytical dimension, it is common to use different data fields such as customer and state.
This allows us to analyze process metrics by one or more dimensions such as customer or set customers. Or, we can look at bottlenecks by product type to determine which product is responsible for the longest delay.
This type of analysis can be used to help with root cause analysis and reporting. However, this type of dimensional analysis is not able to provide actionable insights. It is useful to know how processes perform across customers, but it is not enough to make improvements to a process.
Business analysts and process excellence specialists can identify any process behavior they are interested in and then see how the metric results change with this behavior. This information can be used to make optimizations decisions.
They are able to answer common questions like “How does customer Satisfaction vary when we follow the older protocols or timing guidelines vs instances when we followed newer recommended policies?”
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The information systems of today generate an incredible amount of data from both physical and digital sources. This wealth of data can be used to uncover patterns and insights to help you create better customer experiences as well as new operational efficiencies.
Process intelligence can help you better understand, manage, and plan your business processes.
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