Skip to content
BPM Process Intelligence Feature Highlight

Batching: Is Bundling Work Always Good?

Lukas Pfahlsberger |

Welcome to this month’s edition of Feature Highlights, our monthly segment giving you a view into what we’re building and how you can leverage it to make your business leaner and meaner. Today, we delve into a hallmark feature of Noreja Process Intelligence’s Causal Process Mining approach – Batching. Its unique benefit lies in helping you discover hidden inefficiencies within your processes and identifying bottlenecks and waiting times that are silently draining your resources and delaying your Order-to-Cash turnaround.

 

Using the Feature

A process model showing bundled activities in the middle.

Working in our trusty test dataset, we can see that the picking step is a high-volume bundling node – we talked about node types in a previous article on Cardinalities, but left this one to this article. This is a quick identifier of batching – a scenario where multiple orders or items are processed in one step. While batching might seem efficient at first glance, it’s essential to look closely at what effects it might have on the overall process.

 

A process model showing large amounts of converging steps.

Here we’ve saved some discovery work and zoomed in on a case where batching is happening by leveraging the built-in Batching filter, which is available across every dimension of Noreja Process Intelligence. As we can see here, Batching means that multiple individual cases run together into one joint processing step before then splitting up. A closer examination reveals a stark disparity in the duration of items entering the Plan-for-Picking step – something that warrants a closer look.

 

A process model showing discrepancy in waiting times leading into a batched node.

Zooming in on the transitions, we find items within the batched process whose processing time exceeds others by four days. This discrepancy isn’t merely an operational hiccup; it’s a bottleneck that halts the progress of an entire order. Where we could potentially begin picking for the order and perhaps even have it in the customer’s hands nearly one week earlier with partial shipping, instead we need to wait for every position to be planned concurrently. For a customer whose business is time-sensitive or runs on Lean approaches, such delays could lead to an erosion of trust and satisfaction.

 

A process model highlighting additional waiting times down the line, where technical steps wait for manual steps.

Further exploration into the process reveals a subsequent split for individual item picking. Here we find some steps being completed nearly-instantaneously, despite requiring physical interaction. This anomaly suggests that the pickers are already aware of the problems with this kind of batching and are working in advance to mitigate prior delays. Even though this is likely positive, this means that the process is, in practice, not being adhered to, and this preemptive action, by virtue of not being tracked, might escape certain quality steps, lead to improper documentation, and cause a loss of data granularity. As such, there’s a strong indicator here that the batching around this activity needs to be addressed and managed.

 

Optimizing Batched Work in Order Management

The insights gleaned from the Batching feature are not just diagnostic; they’re prescriptive. They guide us towards optimizing batched work in order management, ensuring that each step in the process is as efficient as possible. By identifying and addressing these bottlenecks, your organization can streamline operations, reduce waiting times, and enhance overall productivity.

Remember that batching, like any process, requires careful consideration and constant evaluation. In the quest for efficiency, transparency, and reliability, it’s crucial to remain passionate about uncovering and addressing the nuances of your operations. Trust in the power of data, the insights it provides, and the transformative impact it can have on your business. However, as always, any interventions need to be viewed not only from the lens of data but also the people involved.

 

Real-World Use Cases for Batching Optimization

There are some tangible use cases where optimizing batched work can make a significant difference in the efficiency and success, especially in the SME Industrial space:

  • Manufacturing Line Efficiency: In a manufacturing setting, optimizing batched work can lead to a more streamlined production line. For instance, identifying bottlenecks in the assembly process can help in rearranging tasks or adjusting workloads to ensure a smoother flow of materials, reducing downtime, and increasing throughput.
  • Order Fulfillment Speed: E-commerce and retail businesses can benefit immensely from batching optimization. By pinpointing delays in the order picking and packaging process, businesses can implement strategies to expedite these steps, ensuring faster order fulfillment and enhancing customer satisfaction.
  • Supply Chain Management: In the complex web of supply chain operations, batching optimization can reveal inefficiencies in inventory management, transportation scheduling, and product distribution. Addressing these issues can lead to reduced waiting times, lower transportation costs, and more reliable delivery schedules.
  • Healthcare Process Improvement: Healthcare facilities can apply batching optimization to improve patient flow and reduce waiting times for appointments, treatments, and procedures. By analyzing patient intake and processing steps, healthcare managers can identify opportunities to batch similar tasks and allocate resources more effectively, improving patient care and satisfaction.
  • Financial Services Workflow Optimization: In financial institutions, optimizing batched work can streamline processes such as loan processing, document verification, and customer service inquiries. By reducing waiting times and bottlenecks, banks and financial services can offer quicker responses and more efficient service to their clients.

 

Bringing It All Together

We hope we’ve been able to demonstrate the versatility and impact of the Batching feature within Noreja Process Intelligence. By harnessing the power of this tool, business owners and managers can not only identify hidden inefficiencies but also implement strategic changes that lead to tangible improvements in their operations. Whether it’s enhancing productivity, reducing costs, or improving customer satisfaction, the potential benefits of optimizing batched work are vast and varied.

In embracing these insights and translating them into action, businesses can navigate the complexities of their operations with greater clarity and confidence. The journey towards operational excellence is ongoing, but with the right tools and a commitment to continuous improvement, achieving your business goals is within reach. Let Noreja Process Intelligence light the way, and feel free to get in touch with us – whether to discuss how best to integrate Process Mining into your business or to arrange a live demo.

 
 

Diesen Beitrag teilen

 

Share this post