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7 min read
What can a responsible company manager do when costs get out of control? - Rational responses to economic difficulties
Skyrocketing energy costs, soaring - and gallooping - inflation and out-of-control procurement prices are causing headaches for even the most accomplished business leaders. Everyone is looking for means and places to save money, to find ways to keep things running. In more and more sectors, the survival of companies is at stake. But the solution may be closer than you think. There is a huge potential for savings in corporate data assets and their proper interpretation. Did you know that data-based efficiency gains alone can be enough not only to survive, but even to grow in times of crisis?
The year 2022 will certainly be an important entry in history books: The global world bursting at the seams. Russian-Ukrainian war, sanctions, unharnessed, spiralling energy and commodity prices. Parts out of stock, inflation, skills shortage, COVID, and fears of market collapse. There is a lot of information overwhelming you; you must indeed be a manager with guts to see through the plight and steer your company in the right direction with your team.
Anyone who produces, provides services, and creates value knows that, in the current situation, efficiency, the unit cost of one Hungarian forint of price revenue, is the indicator that is the key to survival in the short term and development in the long term
But what do you do when the equation with many variables is ambiguous?
If the payback formula has many more unknown input variables moving much faster than we have been used to in recent years? If you feel unable to track this with tried and tested methods?
The good news: there is a solution!
Recently, the digitisation of businesses has accelerated. The proliferation of ERP schemes and various systems that monitor production, logistics and other processes is giving decision-makers opportunities they had never dreamed of before.
A simple example: Monitoring the data of large electricity consumers is now not only an option but also a legal obligation. In the field of energy consumption, the conditions are thus in place to monitor and analyse a company's electricity consumption and make decisions that will improve its energy efficiency. Considering the current energy prices, this is an opportunity not to be missed. A US study showed that the energy efficiency of the manufacturing sector is around 50%. Half the energy used in production is squandered!
There are several reasons for this: idle machines, breakdowns, scrap production, cutover losses, etc. As long as the energy content is 5-10% of the production cost, it is still a significant factor, but with energy prices pumped up tenfold, it is vital that companies improve their energy efficiency. There is huge potential for this at 50% efficiency!
Where can a company save energy? How can it improve efficiency and quality?
After all, scrap waste also leads to losses in terms of raw materials, energy, lost production capacity, labour costs, etc. Every manager knows that s/he can make a good decision if and only if the information at his/her disposal is reliable. However, this requires well-structured data collection and presentation. The basic idea of a data-driven company is that in possession of data, managers make decisions faster and based on real facts than without them.
The basic axiom of a data-driven company is: Measure what you can and base your decisions on that!
Where are we in this process?
Are we taking advantage of the opportunities available to us? Where does the integration of the company's information systems stand? Many other questions arise in connection with the above:
1. What data does the company have?
2. What role does the available data play in decision-making?
3. Do I see an opportunity for improvement here?
4. How can I get more accurate, fresher, and more detailed data?
5. Can I/will I develop this area?
In our experience, the majority of manufacturing companies have the right amount and quality of data to pick the "low-hanging fruit": They can quickly and efficiently see through correlations and make decisions where data are easily and quickly accessible. However, the majority of companies use a multitude of sub-systems, not necessarily communicating with each other, covering specific areas: ERP systems, logistics systems, production management systems, document management systems, in many cases Excel spreadsheets, and a variety of other systems developed for specific purposes. These are typically isolated and the flow of information between them is sluggish or unsolved. The data on which decisions are based are therefore often incomplete and unreliable.
Digital transformation is the process whereby a company's operations and processes are also tracked by IT systems. By integrating the different systems, the relationship between people and data changes, as large amounts of data become easily and quickly accessible, displayed, visualised, and analysed thanks to digital technology. Digital transformation makes the company's operations transparent, data-based and efficient.
External, expert support can help to identify opportunities within the frame of a workshop or audit and, after assigning priorities, develop solutions to improve efficiency and reduce costs.
At Stratis, we have created and delivered solutions for the development and exploitation of corporate data assets for more than 20 years. We develop data warehouses, integrate IT systems, and use our data analytics solutions to improve the operational and decision-making efficiency of our partners. Recently, we have been working hard to explore, showcase, and exploit the potential of manufacturing companies.
We develop solutions that enable our partners to:
improve their production efficiency (OEE measurement, quality management, etc.),
optimise their energy use,
make their maintenance tasks more efficient (abnormal operation prediction, data-driven predictive maintenance),
improve their supply chain metrics (demand forecasting, logistics task optimisation, inventory optimisation, risk analysis),
make their quality assurance processes more efficient and flexible (AI-based quality control, root-cause analysis),
Improve the flow of information in the company (KPI visualisation, dashboard development, balanced scorecard development, daily/weekly report development).
We are convinced that the challenges of today can only be overcome efficiently with today's technology. Digitisation is the toolkit that offers an efficient solution here and now.
The digital processing and accurate interpretation of available information and data can save you a lot of time and money. If you too are also concerned by rising costs, increasing supply uncertainty, and deteriorating efficiency, it's worth involving experts to investigate the hidden potential in your company.
About authors
Andor Havasi has been involved in several IT system implementation projects as a senior consultant at Stratis since 2007, as well as in IT organization and process design. Afterwards, his activities focused on the management of Stratis' solution delivery projects such as the implementation of the HungaroControl financial, controlling, HR and technical data warehouse and the creation of the MOL retail data warehouse. From 2020, he supported Stratis's work for several years with the professional planning, supervision and project management of BI projects, until he became the Director of the Analytics business unit, responsible for the management and further development of the data management area.
Gáspár Sándor has been leading Stratis' artificial intelligence division since 2020, bringing over 20 years of experience in data science. Together with his team, he develops machine learning-powered decision support solutions for large enterprises, leveraging our clients' existing data assets. Additionally, he assists in automating our clients' existing processes using deep neural networks-based NLP and machine vision solutions.
