Customer service. Lead times. Process costs. – More Process Efficiency through data-driven decisions.

In many companies, decisions are still essentially made on the basis of financial key figures. However, relying only on these past-related key figures is no longer sufficient to manage a company successfully in the long term. The measurement and analysis of performance must increasingly take place where the actual (direct and indirect) value creation takes place: in your business operations – hereafter referred to as processes. Therefore, a key performance indicator and analysis system is required that provides information in real time in order to be able to take corrective and improvement measures in the operational processes and thus increase process efficiency.

A corresponding process monitoring system therefore has the task of providing faster insights into complex interrelationships and making them available to the corresponding decision-making teams in different departments so that the right prioritized decisions can be made in a targeted manner. In contrast to classic KPIs (Key Performance Indicators), so-called PPIs (Process Performance Indicators) are used.

PROCESS EFFICIENCY | Efficiency-related indicators show the effort required to produce the service – i.e. the resource consumption resulting from the activities of the process in relation to the process performance. The most important parameters of process efficiency are process or lead time, on-time delivery, process quality and process costs. These performance parameters should be used as the basis for measuring process performance in all business processes and should be regarded as standard performance parameters.

Process Controlling – Costs, quality & time in view

To increase process efficiency, it is necessary to make decisions and implement measures that have a direct impact on costs, quality and lead times. Particularly in medium-sized companies, the potential for optimization in this area is very high. One reason for the lack of lived process monitoring may be that the appropriate analysis option of relevant key figures is missing and thus also a correspondingly reliable basis for decision-making. Modeling processes and manually recording the as-is state is not sufficient for this, and is also far too time-consuming and outdated. Fortunately, a technology that was developed specifically to visually represent process flows on the basis of the data in your systems and to enrich them with key figures can help here: Process Mining. This provides companies with a digital diagnosis expert, so to speak.

Over the last few years, Process Mining has become more and more popular, but has not yet found its place in every company. The use of Process Mining and the thus created possibility to observe process key figures and to initiate corrective measures at an early stage is recommended for every company – from medium-sized enterprises to large corporations – in order to increase the process efficiency of important core processes. Target values can be defined for the key process indicators, actual values can be measured automatically and deviations can be detected. The optimization potential that lies hidden here should not be underestimated.

Data literacy – the key to success

The way in which process metrics are presented is of great importance, so that raw data can be turned into information, insight can finally be gained from information, and a data-driven culture can be established. This is only possible if the data can be presented and analyzed in analysis interfaces that are easy to interpret and use – in line with the data skills of individual employees. To drive and support this development, there are approaches to support users in the interpretation of key figures by means of augmented intelligence-based analysis helpers.

EXAMPLES FOR EFFICIENCY KEY FIGURES - DEPENDING ON THE PERFORMANCE GOAL

TIME | response time, processing time, cycle time, control time, idle time, setup time, transfer time, value added time

COST | error costs, total costs, resource consumption, value added costs

QUALITY | output quality, process variants

CAPACITY | bottlenecks, resource capacity, employee capacity, output, resource capacity

INTEGRATION & COMPLEXITY | Automatization, information flow, timeliness (of information), degree of standardization

The combination of efficiency-related AND effectiveness-related key performance indicators enables a holistic view and economic management of business processes. The relevance of establishing relationships between different KPI systems and across different data sources has also been recognized by solution providers: there are Process Mining technologies that build on business intelligence platforms to deliver complete transparency.

Conclusion

Only by involving the specialist areas in process performance management and ensuring a consistent focus on success across all management levels it is possible to harmonize the individual goals to achieve an overall success. Process Mining provides the technical basis for automated analysis of process performance and operational performance indicators. In combination with associative business intelligence, correlations can also be analyzed and KPIs derived. This provides the company with a digital diagnostic professional that can be consulted in all relevant areas of the company.

Webinar on Demand | Live e-seminar with customer cases | [Language: EN]
Making data-driven decisions. Increasing process efficiency. Whether it's a strategic decision with far-reaching impact or a detail in day-to-day business, your process analytics solution should provide the right impetus for each of your data-driven decisions. Invest 60 minutes of your valuable time to learn how Deutsche Bahn, Siemens Healthineers, STRÖER and other innovative companies use Process Mining to make their business processes more efficient and continuously optimize digitized products.