Elon Musk was recently interviewed about SpaceX’s five-step design and manufacturing process when he echoed what every process excellence analyst has thought: “The most common error is to optimize a thing that should not exist.”
His words are highly relevant when it comes to digital transformation. So many innovation teams and centers of excellence are trying to optimize business processes when they should be looking at which processes shouldn’t even exist or eliminate parts of them. Or they make the same mistake that Musk admits he has done – automate first.
Automating Processes When You Don’t “Get it.”
Automating processes without fully understanding them has costly consequences, with new research showing 1-in-5 decision makers abandoned their automation project completely, and 1-in-3 either didn’t use the technology as planned or found it didn’t work as intended.
Unfortunately, there are waves of vendors who push that you should automate first, then optimize. Musk’s perspectives beg the question, “Can process mining add value to my automation projects?” With the massive growth of this sophisticated technology in recent years, many organizations seem to think so.
Strategies to Achieve Process Excellence
According to recent statistics, the process mining software market will grow by an incredible 42% to almost $7 billion by 2028. But, despite its promises, the technology comes with challenges, and organizations must be aware of the opportunities presented by the software to gain maximum value from it.
Here, we provide strategies for success with process mining and its next-generation approach: process intelligence.
Success Strategy #1: Create a Digital Twin to Understand Process Behavior
An underused capability of process intelligence in process behavior. Process behaviors can be defined as steps occurring or not occurring during any procedure or where steps are repeated. The sequencing of steps is also significant.
Does one step happen before or after another? Do steps that occur before another occur at any time or directly after the other? For example, it’s common to use various fields such as a department or customer when filtering process data.
While these are critical, there’s much more that can be known when you have a duplicate of your processes in the form of a digital twin, where are created from the events that define them.
When the raw data from process steps are used to build a model of what’s been done, you can define process behavior and queries against the behaviors to separate process instances into those that do and do not exhibit specific behaviors.
Having a digital twin also allows you to also consider the timing between steps.
Does a step take a certain amount of time, or does it take longer than a set threshold? For example, for a given category of product, you could set the threshold that it should never take more than one hour from when a stock check is initiated to when it is completed, then investigate the inefficient steps that made it take longer.
While this process may sound simple, all the data needed to evaluate behaviors is not available in any one record system.
And we still wouldn’t be able to answer behavior and time-related questions without the data being organized and understood as a series of steps unless you have the right tools to query this process model as to behaviors.
Tools and Behaviors You’ll Want
However, advanced process intelligence generates the process model from the data, provides the tools to specify the behaviors, and evaluates all process instances against these behaviors.
Success Strategy #2: Use Constant Visibility to Take Control
Process excellence analysts wish a control plane could monitor distributed operations and automatically act as needed. However, until there is such an external system, process intelligence can give you a data-driven bird’s eye view of your entire operations to gain a true understanding of how processes are working.
Taking a non-bias approach based on facts helps industry leaders make better, in-the-moment decisions.
With this visibility into your processes, you can understand exactly how your processes execute and answer questions like: How can automation improve customer experience? Which employees are the most efficient and consistent?
Where are your bottlenecks, and how do they affect compliance and service delivery? For example, you can optimize supply chain efficiency and improve the purchasing and sourcing process. And by discovering, analyzing, and monitoring how your procurement process really works.
“You can uncover delays that cost time and money, and discover the most efficient processes paths for positive business outcomes.”
Success Strategy #3: Add Analytic Dimensions
Another way to ensure process execution success is to use process behavior as an analytic dimension. It’s common to use various data fields, such as customer or state, as analytical dimensions. This enables us to look at process metrics broken down by one or more dimensions, such as a customer or set of customers of interest, or look at bottlenecks broken down by product type to see what product correlates to the longest delay.
This type of dimensional analysis is great for reporting and can help with root cause analysis. But there are limits to how useful this is for providing actionable insights. For example, knowing how process performance differs from one customer to another is great for reporting, but there is the question of how much it helps make changes to optimize a process.
The Process Behavior
When business analysts or process excellence experts can define any process behavior of interest to them and see how metric results vary with the presence or absence of this behavior, they then get actionable information that can help make optimizations decisions.
They can answer common questions such as, “How does customer satisfaction differ when we follow the old protocols or timing guidelines vs. instances when we followed the newer recommended policies?”
Conclusion
Today’s information systems generate a remarkable amount of data from both digital and physical sources. When properly ingested, merged, and analyzed, this wealth of data can be used to discover patterns and insights that illuminate paths to better customer experiences and new operational efficiencies.
You can better discover, understand, and manage business process execution more effectively by seeking process intelligence.
Image Credit: thisisengineering; Unsplash Thank you!
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