Part II: Customer story
This blog post is part of the blog series “Unleash your procurement transformation potential with SAP Signavio for SAP Ariba”. To get an overview of the SAP Signavio capabilities for analyzing processes across SAP ERP and SAP Ariba, check out the first blog post by @dianakveit. To make these capabilities more tangible for you, we'll now look at a concrete customer example.
Business processes have become increasingly complex and frequently lack transparency within an intricate IT landscape. They're often fragmented and full of hidden inefficiencies. This results in uncertainty about the relevance of process transformation efforts, which is compounded by the high costs associated with these projects.
Imagine this:
This is exactly what the new value accelerator for analysis of source-to-pay (plug and gain approach) offers. It provides an out-of-the-box analysis across SAP ERP and SAP Ariba, enabling you to gain transparency and realize untapped value within a few short hours.
We've created several deep dive analyses that are easily available for customers to use in their ongoing enhancement efforts and transformation projects. Each deep dive aims to give you insights into a specific business scenario and includes value identification and SAP recommendations as basic characteristics.
The data used originates from SAP Signavio Process Insights, which is standard in the plug and gain approach. This means that the dashboards provide data quickly without a need to create or use special extractors in SAP Signavio Process Intelligence. You get insights out-of-the-box. The data spans multiple process flows, standard performance indicators, and master data from both SAP Ariba and SAP ERP systems. This means that you can see your whole source-to-pay process. You can also view the data over long time periods, which helps you to identify patterns and trends.
The dashboards are designed to conveniently guide users through the analysis. You'll get explanations about the context and underlying motivation, as well as possible conclusions and recommendations for each analysis. You also get information about what to do next and how to resolve root causes. This makes it easy for all business users to use the analysis without extensive technical knowledge of SAP ERP or process mining.
Start with the full picture
An overview of the end-to-end processes used in your organization provides the ideal starting point for analysis. As part of the plug and gain approach, you get access to your organization's own process house, packed with best-run scores for each of your end-to-end processes. The process house is a central point for you and allows you to understand performance in terms of efficiency and end-to-end process usage throughout the organization. The best-run score is an aggregated score over all sub-processes currently available for your organization. To learn more about the best-run score and process house, check out the following blog posts: Best-Run scores, process house.
Thanks to the traffic lights, it's easy to identify if there's improvement potential in the source-to-pay and financial area. We can even already estimate the potential impact, because these processes are used frequently according to the case count provided. Let’s take a closer look and deep dive into the source-to-pay modular processes.
Identify focus areas
Based on the best-run score for the specific process variants, you can see which variants need our attention most:
We can also see that these processes have a significant number of completed cases. Let’s jump into SAP Signavio Process Intelligence to analyze the processes in detail. We'll start with the process from purchase requisition item to invoice receipt...
Dive deep into the process
In the process execution widget, you get full transparency into your source-to-pay process across SAP ERP and SAP Ariba. In the upper lane, you see all the events that took place in your SAP ERP system. In the lower lane, you see all the events in your SAP Ariba system – and that’s transparency at its best! You don't need to make any assumptions – you really see the process from a fact-based perspective.
The funnel diagram tells us many things about the current situation and integration scenarios of SAP Ariba:
The metrics below indicate significant improvement potential for several steps of the process. For instance, we can see that a purchase order is manually created in more than 60% of cases. Also, the best-run score is quite low, indicating that purchase orders aren't being created in line with leading practices.
Analyze manual processing
To dive deeper into the topic of manual processing, let's take a closer look at the corresponding operational efficiency dashboard:
Looking at the main metrics, we see that there's a significant number of purchase requisitions and purchase orders that are being processed manually. These documents are created manually and later changed.
The high number of manual changes to business objects for both purchase requisitions and purchase orders means that the purchaser must adjust the documents several times before ordering, which increases manual effort. And this is worse again if the changes are made after the invoice for the order has already been posted.
The value of actively improving the automation rate is now clear. More than 10M USD of costs are associated with manual processing alone in the analyzed period of one year. The next question is, what we can do to improve this situation?
Start improving right away
To enable you to start improving right away, SAP Signavio Process Insights offers correction recommendations, which provide specific quick fixes with a relevant impact.
In our example, we want to start by improving purchase order creation to avoid manual changes. To enhance the process to create purchase orders, SAP recommends training users to use the catalog instead of free text. The following action items are recommended:
This is how you can start improving straight away. The first action item has already been identified!
Let's now take a closer look at our invoicing process, because this was the second focus area identified earlier. We'll continue our analysis in Part III of our blog series, shared by my colleague @nklimenko…
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