Compliance Efficiency Simplification Trufa Use Case


Compliance, Efficiency & Simplification of Enterprise Processes

A Trufa Use Case

Business processes are a key element in organizing enterprises. Accordingly, they are crucial when it comes to improving the economic outcome of the enterprise. This is why implementing processes in an ERP system requires plenty of effort and consideration. However, measuring the quality of enterprise processes and learning how to improve based on such measurements presents a challenge as well. The Trufa application measures and monitors process efficiency and effectiveness. This includes checking the compliance of processes used with the prior intentions at the time of process design. In addition, it helps users overcome the permanent struggle of keeping things simple and manageable.

The Trufa application offers functionality beyond a mere analysis: It autonomously gives advice on improving processes and the economic outcome: Artificial intelligence for enterprise performance.

Discovering, modeling, analyzing, measuring, improving, and optimizing enterprise processes – which basically sums up business process management – is anything but easy.

Process mining tools have seen wide acceptance over last years to offer support in such activities. They visualize process step sequences and show the duration of each step as well as the number of times such steps were executed. The tools enable the user to inspect the visuals, learn about how processes are used in the enterprise, and draw conclusions after slicing and dicing the data. However, users often struggle when it comes to identifying the real impact of process variations, especially the impact on the financial results.

Moving away from the “manual” approach of inspecting graphs and checking them against personal experience or intuition, Trufa is an AI-enabled application which supports users by automatically analyzing processes. Its results are based on mathematical algorithms and other data-driven techniques. The Trufa application provides direct, deep insights and, supported by the enterprise’s own data, establishes a basis for well-founded decisions and a fast track to action. The main areas of use include:

  • Measuring process quality 
    Quality targets include key financial results such as contributions to profitability or impact on working capital and related subcomponents.
  • Identifying opportunities to improve processes 
    for profitability or working capital consumption, identified by well-specified change actions
  • Identifying potential for simplifying processes
    Mostly used for process redesign in the context of S/4HANA transformation programs.
  • Monitoring process compliance
    of to-be processes


I. Measuring Process Quality

First, let’s have a look at the motivation that lies behind process management.

The primary goal of enterprise processes is to organize work in such a way that it can be performed in a repeatable way, which itself forms the prerequisite for managing a company’s operational and financial output.

This is why Trufa uses measures that extend beyond the mere process duration or other figures that simply count and visualize facts.

Financial key factors decision makers must take into account when judging process quality are “contribution to profitability” and “consumption of working capital”.

Pic. 1: Process steps along with their working capital need
Pic. 1: Process steps along with their working capital need

Of course, process duration has an impact on working capital, but so does the volume of goods and the individual value of goods, orders, and batches. If we precisely know how much working capital is needed, e.g. due to the time gap between “delivery initiated” and “sending invoice” and the goods involved, this gives us an immediate measurement of the economic value of the process.

Moreover, having a business case at hand, it becomes a lot easier to discuss changing or influencing such a process with the appropriate stakeholders.

In real-world numbers, measurements like these are the difference between knowing that the average process takes 1.6 days and knowing that we need working capital of $7.2m for this process step. The mere fact that we know the amount of money involved establishes a foundation for a meaningful evaluation and lays the groundwork for a productive management discussion on whether it would be at all beneficial to pursue this process for achieving improvements.

Additionally, the Trufa application identifies the potential actions for the process improvement, which is essential for moving forward.


II. Identifying Opportunities for Process Optimization

Trufa’s capability of autonomously identifying improvement opportunities and potential actions represents a major improvement compared to the traditional manual investigation of process model visualizations.

After loading the data – which is cyclically updated with new data retrieved from the source ERP systems – the Trufa system generates a vault of opportunities. A Google-style full-text search option helps navigate these.

Pic. 2: Search for improvement opportunities
Pic. 2: Search for improvement opportunities

Image 2 shows the example of a search for “Brandenburg” and “DSO”, which delivers the opportunities identified for the cash collection process for operations in Brandenburg.

There is more money involved than in the previous example: the Trufa application has identified potential of roughly $36m through shorter DSO, the time between sending out invoices and collecting the payments.

And since the Trufa application also offers simulation functions, it allows the user to work on the identified potential process improvement and add strategic directions. A separate white paper details the options for tracing the improvement potential step by step, down to specific actions.


III. Identifying Potential for Simplifying Processes

While process simplification is not technically bound to setting up new systems, motivation to engage in this discipline originates mostly in current R/3 to S/4HANA transformation efforts.

Due to conflicting targets, process simplification is anything but easy. Having just a small amount of simple processes in place is desirable because it reduces the need for end user training, minimizes the risk of errors occurring during the process, makes it easier to assure process execution quality, and so on.

On the other hand, the desire to create elaborate processes results from a company’s goal to serve customers better and e.g. offer faster, higher-quality delivery to gain an advantage in the market.

The trend towards increasingly complex processes is also fueled by progress in digitalization, specifically is towards custom services and even products, faster reaction times, etc.

As a result of digitalization, we can expect that new process variants will be produced at even higher speeds. This means that automated ways of checking for simplification options will grow even more crucial in the future.

While processes are mostly identified by a sequence of actions (such as taking an order, sending out goods, collecting payment) in process mining tools, Trufa takes this to the next level and, in addition to events, also takes the configurations of such processes into consideration, the so-called “variants”.

These include order types, delivery types, different kinds of invoices and payments, etc. Trufa’s above-mentioned identification of the financial or operational impact works on this level; so does the simplification process.

In this contex, simplification can be translated as “giving up variants”. The first question to ask is: which variants are candidates for extortion? It is extremely important to provide measured facts on process variants to avoid a battlefield with individual stakeholders fighting for “their variant”, based only on individual preferences or ostensible significance for “their market” or “their customer”.

Trufa provides two evaluation methods for simplifications:

  • The first is to review usage profiles along with profitability and working capital impact. For every combination of process variants, the individual usage pattern and contribution is calculated as shown in Image 3, where we see the greatly varying margins delivered for different process variants. The total number of variants in this company’s order-to-cash process is 611.

Pic. 3: Process variants and related gross margin
Pic. 3: Process variants and related gross margin

  • The second aspect to evaluate is whether retiring a specific process variant will actually impact the business negatively. For example, if we consider ruling out payments via bill of exchange in the future, this might create a disadvantage for the business. On the one hand, it is therefore important to know how much of the business relies on this variant, which we looked at in the previous paragraph. On the other hand, we want to avoid manually scanning all process variants to determine their elimination and impact potential.

That is why Trufa features a simulation function which provides an ideal way to identify variants that, were the company to stop offering them, would only impact business in a minor way. The function can filter out all variants which would only affect 1% of the business, for example.

Pic. 4: Simplification impact transparency
Pic. 4: Simplification impact transparency

A typical ratio from past simplification projects showed that that less than 50% of all variants were good for 99.5% of the business. Nevertheless, the power of the Trufa simulation is not based on common knowledge or the latest research studies, but instead the very data from a company’s ERP system.


IV. Monitoring Process Compliance

The term compliance does not focus on legal issues here. We will cover the legal impacts of screening process execution legal impacts in another paper.

The focus here lies on the match of “planned” vs. “all available” variants of execution. In other words, we are looking at to-be processes and as-is processes.

There are quite some reasons to examine as-is vs. to-be:

  • To check whether processes are adopted as planned.
  • To check whether processes are executed in a straightforward manner or whether loops can be identified, slowing down the flow.
  • To check for not allowed shortcuts such as maverick buying.
  • To check whether users make use of intended business variants. (This could often be enforced through appropriate configurations but isn’t in order to leave options open for “emergency needs”.)

Trufa helps carry out these examinations with the same functions mentioned in sections I and II of this paper. All processes are evaluated by their financial outcome. Faster execution, leading to higher profitability, are evaluated positively, a downward trend calls for improvement.

Pic. 5: Monitoring business alerts
Pic. 5: Monitoring business alerts

To complement this investigative approach, Trufa also offers automatic checks. These are conducted with “Business Alerts” which are defined by Trufa users, either individually or shared between users or groups. The user defines the conditions under which they are alerted.

In the context of process compliance, alerts could be for example:

  • Order types which are depreciated for everyone or only used for defined situations.
  • Missing steps such as purchase orders without a purchase requisition.
  • Process steps exceeding the expected amount of time.

The separation of the investigative approach, which works with a large number of process steps to identify potential for financial optimization on the one hand, and alerts that point out individual actions to be checked on the other, have proven to be very effective for process flow controlling.