Digitalization: At risk of being blind-sided by confusing data
August 12, 2024
|
Digitalization
Why Companies Make Wrong Decisions Despite a Flood of Data
Many organizations fall into the trap of hallucination even without ChatGPT and the like. That is because even though they have no clear understanding of much of the collected data, they use it as the basis for their strategic decisions.
Pilots conduct preflight checks before each flight to verify the technical condition of the aircraft. Information on weather and cargo is also fed into the aircraft systems. Careful flight planning that includes all weather, cargo and traffic information is crucial for a safe flight. There’s nothing worse than starting off in Germany in the best weather only to be surprised by thunderstorms or slippery cargo halfway through the flight to South America.
A company should be organized in the same manner, because, after all, throughout the value chain there are a multitude of extremely small variables, which due to their interdependencies have a strong impact on the end result. In many organizations, though, the integrated view and coordination of all data is often lacking, and what you find is a true hotchpotch with no consistent approach. This makes it extremely hard to derive relevant insights from the data. The variety of formats and applications are obstacles in a heterogeneous IT system landscape preventing cross-departmental planning and collaboration.
Michael Feldmeth has implemented various Lean projects in the automotive industry as well as in mechanical and plant engineering. His projects included the restructuring of the entire order processing. The focus of the projects was the optimization of the production processes as well as the associated administrative processes. Due to the production of cooling systems and special machines, he was able to achieve a significant increase in efficiency and flexibility of production by reorganizing the manufacturing according to Lean principles and by training the employees. Most recently, he worked at Robert Bosch GmbH in the Central Department for the Development and Coordination of the Bosch Productions System. He was responsible for the further development of the production system according to the future requirements of the manufacturing industry. Michael Feldmeth has been working for Staufen AG since 2014. Since 2019 he is employed as a Project Manager.
Companies cannot see the KPI forest for all of the many numbers
Just how large these challenges are for the industry can be seen in our “Digitalization 2024” Study. In a survey of 417 organizations from the German-speaking region, six of ten of the respondents admitted that although they do view the individual figures from the various areas, they know very little about the interdependencies. Insufficient IT compatibility and a lack of analysis expertise prevent the interrelationships between the data from being recognized. The accumulated information is more likely to confuse rather than provide added value or form the basis for precise recommendations for action. In short: companies cannot see the KPI forest for all of the many numbers.
And how do companies deal with data archiving?
So, how do organizations deal with data archiving? For 77 percent of the respondents, an ERP system is the most frequently chosen solution, followed by databases such as Microsoft SQL Server or PostgreSQL (69 percent) and Excel lists (54 percent). Yet, programs such as Excel function as spreadsheets and are tailored to a very specific application area and – just like an ERP system – are not ideally suited for data archiving. As a consequence, data silos and limited functions of the individual systems slow down the efficiency and productivity of organizations.
Especially now, in economically challenging times, an efficiently organized company focused on operational excellence is extremely important. Using sophisticated analysis tools from the digitalization toolbox, organizations can perform a virtual pre-flight check of the entire value chain and identify any potential sources of risk or optimization potential. This is followed by practical implementation.
Faster, better, cheaper
Often, however, the opposite is still the case: while existing data is collected, most companies neither fully understand nor properly analyze it. Nonetheless, a good three-quarters of companies state that they will use this data for future strategy development. A risky endeavor.
At the same time, the potential hidden in our own world of data is well known: for example, 72 percent of the respondents concede that a data analysis would increase the efficiency within their organizations. 57 percent expect their lead times to be optimized, 52 percent expect an increase in quality, while 48 percent hope to see a rise in customer satisfaction.
Organizations need to understand what makes them tick
Professional data analysis combined with an operational excellence strategy is essential if organizations are to avoid flying blind in the maze of increasingly complex products and production processes and choose the shortest and most efficient path: organizations need to understand what makes them tick, which changes lead to which results and how the value creation process can be optimized. Because regardless of whether the issue is supply chains, production processes or HR challenges, often even small modifications and fine adjustments can have a major leverage effect.
Michael Feldmeth has implemented various Lean projects in the automotive industry as well as in mechanical and plant engineering. His projects included the restructuring of the entire order processing. The focus of the projects was the optimization of the production processes as well as the associated administrative processes. Due to the production of cooling systems and special machines, he was able to achieve a significant increase in efficiency and flexibility of production by reorganizing the manufacturing according to Lean principles and by training the employees. Most recently, he worked at Robert Bosch GmbH in the Central Department for the Development and Coordination of the Bosch Productions System. He was responsible for the further development of the production system according to the future requirements of the manufacturing industry. Michael Feldmeth has been working for Staufen AG since 2014. Since 2019 he is employed as a Project Manager.
Intelligent Industry 4.0 production processes can be applied to accomplish a variety of objectives. These include achieving greater productivity and efficiency, fulfilling consumer specifications faster and more expediently, and developing brand-new industrial products and business models. Small and mid-sized companies often have a particular need for this kind of consulting and guidance.
The digital transformation should by no means be considered a sure-fire success. Even German flagship industries and technology integrators such as the automotive industry, the electrical industry, the aviation and aerospace industry, but also
the mechanical engineering industry have not yet been able to show any substantial benefits from the new opportunities. Although the tremendous need for action has been recognized, and here and there and we can in fact celebrate the initial successes. By and large, however, measurable productivity gains and really successful digital business models are the exception. As the study “Aerospace 2019 – Leadership in Times of Change” has confirmed, management teams and top management oftentimes find it difficult to develop their own company in a targeted manner with view
Ostrich tactics have outlived their usefulness. The wheel of change is turning much too quickly in the age of digitalization for the new challenges to be sat out or put on the back burner.
