The IT systems of companies will continue to develop in 2022. Johannes Kreiner, Managing Director of Sage DPW, knows how and which trends play a role in this. […]
Covid–19 has noticeably slowed down some dynamics in the past year – especially in economic contexts. In one area, however, Corona has provided unprecedented dynamization. We are talking about digitalization. The momentum of this development will also be shown in the coming by the example of several trends. Sage has identified five technology drivers that will have a noticeable impact on operational IT applications in 2022:
- Distributed Cloud and Edge Computing
- Process Mining and Data Mining
- HR 2.0
- Ethically responsible AI
- Data hygiene
Distributed Cloud and Edge Computing
The demand for software that can be flexibly adapted and is available everywhere via the cloud will also increase in 2022 – also in the human resources sector. After the development from large monolithic systems to small-sized HR microservices is already clearly recognizable, the distributed cloud is now also following the underlying infrastructure. With this architectural approach, there is no longer a central data center, but the computer load is divided into small regional clouds. This infrastructure of networked and distributed servers also provides the ideal basis for a concept that is derived directly from it: edge computing. The aim is to bring servers and applications closer to the place where the data is generated, and thus noticeably shorten their processing time.
“The decisive advantage of the distributed cloud and edge computing, in addition to the lower latency and better performance, is a higher reliability, since the individual regional clouds can work independently of each other. This means that if a cloud server should fail, this does not result in the failure of the entire HR system. The demand for distributed cloud and edge computing will also be driven by data-intensive applications in 2022, for example in the field of HR and people analytics.” explains Johannes Kreiner, Managing Director of Sage DPW.
Process Mining and Data Mining
In 2022, too, many companies will have to adapt to irregularities in the course of their HR processes: home office phases will once again alternate with periods in which people will increasingly work locally in the office again. Familiarization and onboarding processes for new employees will take place either remotely or personally in the company – depending on how the pandemic situation allows. The same goes for recruiting. Against this background, process mining will gain in importance – this means: the systematic analysis and evaluation of business processes and thus also the HR processes. Process mining has its origins in data mining, i.e. the analysis of large data sets with the aim of identifying new cross-links, patterns and trends.
For example, companies can use data mining in the human resources area to increase the personalization of their training offers for employees or to conduct employee potential analyses. In process mining, this procedure is transferred to a complete process – for example, recruiting. The events occurring in it, so-called events, are logically linked with each other in terms of their chronological order. Johannes Kreiner explains: “On this basis, a process can be visualized and analyzed in real time. However, this requires fully digitized processes. Only in this way is it possible to create the necessary database for process mining. The integration of AI also makes it possible to obtain even more well-founded and, in particular, more intelligent, because prescriptive analyses. Keyword Predictive Analytics. For example, it can be used to show when the demand for a certain employee or competence profile will increase in the future and how much.“
HR and people analytics have enabled companies to have an unprecedented overview and level of knowledge about their employees. The IT systems used for this purpose produce a huge amount of data every day. This creates an important basis for improving personnel processes and making them more efficient if companies use and evaluate this information in a targeted manner. On their own, however, the recorded data do not yet offer any great added value. It is only in a larger context that they unfold their benefits. A decisive role is played by correlating HR information with other operational information – for example, by comparing availability data and competence profiles with capacity requirements and shift schedules from production. On this basis, personnel deployment planning processes can be controlled much more precisely if the personnel department can directly access information from other areas of operation. “Due to this advanced integration of HR and operational data, there will be a new generation of HR systems in companies,” comments Johannes Kreiner and at the same time emphasizes the requirements: “The decisive prerequisite for HR 2.0, however, is that all components of an HR software can be connected to all relevant operational control systems via standardized interfaces – starting from production control to the CRM system.“
Ethically responsible AI
The potential of AI is not only now known, but meanwhile there are already very mature systems in which the technology proves to be practical every day. Here, AI helps to make strategic personnel decisions in the company based on data and thus becomes a powerful tool for companies to position themselves in the best possible way in the “war for Talents” against the market competitors. However, the findings derived from AI systems also repeatedly cause critical questions. They revolve around the topics of data protection and compliance, for example, and come from the ranks of the stakeholders of those who use this technology. “Against this background, it will no longer be sufficient in the future to blindly use AI in the sense of one’s own entrepreneurial goals. In the future, AI will no longer be seen only from a purely functional point of view, for example in terms of process excellence or automation of HR processes. Rather, this technology is increasingly being placed in a direct relationship with the stakeholders it is supposed to serve. In this context, it is also about questions of fairness, fairness in competition and transparency towards supervisory authorities,“ comments Johannes Kreiner.
The value of data as a basis for reliable business decisions is increasingly recognized. However, with the exponentially growing amounts of data available to companies, the question of data quality will also become louder. At its core, it is about avoiding dirty data. Against this background, a challenge for many companies is the sheer number of operational data sources and thus the fragmentation of data, which is often available from outdated systems, in different formats, metadata, forms and outdated database formats. This also applies to HR and personnel data. As a result, this leads to low data quality. “Data quality management will therefore increasingly become the focus of entrepreneurial activity. This is about ensuring data quality from the outset and preventing dirty data from being created in the first place,“ says Johannes Kreiner. A prerequisite for this forward-looking form of data hygiene is data governance. More and more companies are therefore likely to adopt a set of rules for the handling of data in the company.
Conclusion: 2022 will be the year of digital evolution
“Starting next year, companies will be particularly interested in pursuing the logical and often necessary next steps in digitization in order to position themselves optimally for 2022 and beyond. After cloud comes the distributed cloud, after big data comes targeted data and process mining, as well as a stronger focus on data hygiene. HR needs an update to HR 2.0 and instead of simply using AI potential, the focus is on ethical responsibility in artificial intelligence. So we will be dealing with a year of digital evolution in the coming year,“ says Johannes Kreiner.