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Case Studies, Business Case

How to Optimize Order to Cash with Process Mining

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Order to Cash (OTC, O2C) is a fundamental business process which oversees the transition of customer orders into payments. 

It’s the holy grail of success — the effectiveness by which a company is able to convert a product or service into money. 

A sluggish or complicated OTC process can result in lost revenue, lost customers, reputation damage, and even compliance issues.

Improve the end-to-end OTC cycle with process mining and download the Minit OTC Mini Success Story here.

This article breaks down common Process Mining use cases and applies them directly to the order to cash cycle. The outcome is a comprehensive hot-spot map which reveals bottlenecks,  compliance red flags, duplications, time-draining rework, outliers, and opportunities for improvement

Armed with such data, as a decision-maker you can select the best path forward for OTC optimization. 

 

Why Process Mining for OTC Optimization?

You can take several approaches to improving your organization's OTC process, including automation, better data collection, and standardization. However, these approaches may not be effective if you don't properly identify the root cause(s) of a poor OTC.

Process Mining is the first line of defense in discovering what’s going wrong, and more importantly, what’s going right. 

OTC kicks off the moment a customer confirms an order. Whether that initial step stems from an e-commerce platform, telesales or face to face confirmation, some sort of order management system is in place. The process continues on to credit management, order fulfillment, shipping, invoicing, accounting, collections, reporting, and potentially much, much more. 

That’s a lot of systems, a lot of people and a lot of ways to screw things up! 

Because the OTC cycle is stretched across multiple departments and systems, a solution like Process Mining — built to bridge interdepartmental white space — is the best means to OTC improvement.

 

Which Use-case to Apply to OTC Process? 

Process Mining software is often applied in one of four ways

  1.  process discovery, 
  2.  conformance checking, 
  3.  resource optimization, and 
  4.  cycle-time optimization. 

Let’s take a look at each of the use cases and how they can be specifically applied to OTC

1.  Process Discovery

This use case is most applicable when the OTC process is not known or has deviated from process architecture. 

Even in circumstances when OTC is thought to be known, process discovery reveals a detailed as-is representation of the process

Process discovery can identify the root cause of these common OTC problems: 

  • Poor on-time delivery metrics
  • Delays in order confirmation to customers
  • Delays in order fulfillment
  • Late payments, resulting in cash flow problems
  • High number of order changes

2. Conformance checking 

Service level agreements, industry regulation, and agreed internal policies necessitate conformance checking. 

This use case is applied to OTC when specific steps in the process are mandatory and inflexible.

An example specific to OTC applies to enterprises which partake in subsidiary sales. When goods or services are sold among subsidiaries, payments must be properly recorded and realized against the appropriate business unit. Conformance checking with Process Mining helps enterprises self-regulate.  

3. Resource optimization

Once the as-is OTC process is established, Process Mining reveals ways to better use resources. Focus on two ends of the process spectrum:

What’s going wrong — weed out process redundancies, identify underperforming employees, find bottlenecks and outliers, reshuffle headcount to understaffed teams.

What’s going right — which parts of the process face the least friction? Why? Identify these areas and seek to replicate effective structures in other parts of the process.   

Resource optimization can lead to huge cost savings in the OTC cycle. 

For example, a high volume of sales order changes – which increase transactional costs – can be a result of poorly designed processes. Process Mining will highlight the reasons behind sales order changes, and in turn, empower managers to take action. 

4. Cycle time optimization

Some stages of the OTC process simply take time. 

A business which operates in an intense demand, limited supply sector (natural resources, highly technical services) may face a long order confirmation process. Not all businesses are able to automate order approval: selling a smart phone online is a lot different than selling a raw chemical material.

Some stages, however, become unnecessarily sluggish, which can cause frustrating delays and unsatisfied customers. 

The cycle time use case highlights both employees who may need additional training and stages which are ripe for RPA. Cycle time optimization in OTC isn’t always about taking disciplinary action. Training stages may have fallen to the wayside for a period of time, making that particular batch of new hires less effective at processing orders. 

Additionally, the OTC processes tend to accumulate extra offline steps which remain outside the prescribed cycle workflow. 

In relation to process discovery, as a decision-maker, you may want to remove some of these obstacles or simply bring the process back on track to reduce cycle time. 

 

OTC Process Mining Success Story

We put Minit Process Mining technology to the test to help a client minimize OTC costs and streamline payment collections. 

The results were astounding. 

This case study focuses specifically on a global chemical company with 50+ manufacturing sites, 35K+ employees and over $18 billion in revenue. Download the OTC Process Mining Success Story to learn more. 

Download the Mini Success Story

Does your organization need help optimizing this critical process? Minit can help bring a sluggish OTC process up to speed and set your business on a path towards operational excellence.

Reach out to our team of Process Mining experts today to see what our technology can reveal about your data.  

 

Jana Gregusova

16. 07. 2019