Pattern View: First Line Issue Recognition for Your Processes

Hi there! It’s been a while since we’ve done one of these – the last couple times we covered more high-level, philosophical topics in this slot – but we’re back with another Feature Highlights! This time, we’re looking at our Pattern View, which give you another way of looking at the process distribution in your organization. Known formally in the scientific field as Dotted Charts, these evaluations help you find process distributions along a variety of factors. Today, we’ll be focusing on looking at the distribution of our processes on the basis of time, since that tends to be the most common use case. Strap in – we’re about to get colourful.

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Using the Feature

We start off with an unfiltered view of all the cases in the organization, organized by duration. Right off the bat, you can see that there’s a large variance in the total run time of the different process instances in this organization. At the top, we see the shortest processes, which start and end in around a day – in our test set, likely rejected offers. In the middle, we see processes that run for a few weeks to a month. At the bottom we see outliers and special cases, which sometimes run for up to a year. Mousing over any individual data point, you can see its ID and its time.

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Here we’ve changed the display options to show the chart organized by real-world start time, which helps you see how many individual activities happened during which real-world time window. It’s easiest to read this version by looking at, on the one hand, density of activities at any given moment in time, and on the other hand how high up activities at any point in time extend. The former tendentially indicates times when your organization was under heavy load, and the latter indicates processes that went on for an exceptionally long time.

Here, for example, we can see that the density seems lower towards the tail end of the chart, but the vertical spread becomes higher – this would seem to indicate that our organization’s processes became longer as time went on, which would then correlate with a lower number of new cases – in this case orders – as the organization was busy cleaning up older work.

Another interesting thing we can clearly see is periods of time in the organization’s processes where nothing happened. In the image above, for example, we’ve purposefully selected the Christmas period, where we can clearly see that the public holidays were observed, and no work took place. In a real-world situation, you can use evaluations like this to identify the impact of organization-wide issues like system outages or strikes.

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By now you’re probably thinking – alright, I’ve got all this high-level information, now what? As with all our tools, our goal here is to get you from high level indication to root-cause, so that you can then find and address the issues in your real-world organizational context. To that end, next to our usual ability to filter the view, as we’ve done here for only cases with violations, we also offer a process preview mode that lets you see the individual process case trace for any data point you find on the chart. From there, you can look at the process in Case View and continue your analysis and triage.

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Real-World Use Cases

Now that we’ve delved into the Dotted Chart feature, let’s explore some practical, real-world use cases. These scenarios illustrate how this powerful tool can benefit your organization, enhancing both transparency and operational efficiency.

Enhancing Team Performance

• Problem: There is a noticeable variance in the performance of different teams handling similar processes.
• Solution: Visualize the performance of each team using the Dotted Chart. By comparing the duration and frequency of activities across teams, you can identify best practices and areas for improvement. Sharing these insights fosters a culture of continuous improvement and collaboration within your organization.

Improving Customer Experience

• Problem: Customers are experiencing delays and inconsistencies in service delivery.
• Solution: Use the Dotted Chart to analyze customer-facing processes. Identify stages with frequent delays and investigate the root causes. Implementing targeted improvements in these areas ensures a smoother and more consistent customer experience, leading to higher satisfaction and loyalty.

Planning for Future Growth

• Problem: Anticipating the impact of organizational growth on existing processes can be complex.
• Solution: Leverage historical data in the Dotted Chart to project future process performance under increased workloads. Understanding how your processes have performed in the past helps you plan effectively for growth, ensuring that your organization scales efficiently without compromising on service quality.

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The Pattern View is a powerful tool for process optimization. While there might be a bit of a learning curve to really get a solid feel for how to spot the visual patterns we’ve mentioned in this article quickly and reliably, once you get the hang of it, there’s no better tool for taking a first look at work distribution and high level trends in the organization over time, and via this getting into the root-cause drill down flow needed to act on these problems.

Stay tuned for more Feature Highlights, and feel free to reach out with any questions or feedback –as always, we love hearing from our readers about their experiences so we can help them succeed in their optimization journey. Until then, keep innovating!

Best,

Evgeny,

Head of Product @ noreja

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