Have you ever heard of “the lean and mean trap”? Last month I visited a company that manufactures specialty chemicals. We initially discussed the market conditions and the current economic situation of the company. I was not surprised to hear that they are doing well because, over the years, they have changed their strategy from general to a specialist supplier. As a result of this strategy, they have also been able to reduce their costs. Most of the savings were achieved by introducing a lean and mean organization, leading to a relatively small team that is responsible for production. They created an integrated production system without wasting resources.
Who is the Winner of the Lean and Mean challenge?
The challenge when it comes to the lean and mean strategy is “where does it stop?” Market conditions will force manufacturers to work even smarter at even lower costs. In principle, I believe smarter working and focusing on lower costs – a synonym for digital transformation – are prerequisites for survival for a manufacturer based in Europe. In my opinion, there is no market for companies that are unwilling to change and still supply generic products or services and simply try to reduce their costs. A holistic view is necessary, keep the big picture in mind.
To get back to my meeting with the management of the above company, we discussed the options for saving energy. Many manufacturers are faced with significant energy bills. In this particular case, the energy bill for fuel (mainly natural gas) is more than 20 million euros per year. Most of this energy is used by the utility to produce steam. Saving energy is already a challenge, and it is now an even bigger one in light of the new regulations regarding emissions and carbon dioxide. Luckily, there are numerous options available for saving energy such as monitoring by means of rigorous modeling.
With rigorous modeling, the actual utility plant is completely simulated in a model running on a server. Once this complete utility has been modeled and is fed with real-time data from the field, users can see energy consumption, efficiency, imbalances and emissions at a glance. With the help of this model, also called digital twin, they can monitor the plant’s energy efficiency and run various scenarios, for instance, to determine the impact of changing the boiler, the fuel or the drive (e.g. from steam to electrical). Energy monitoring allows the management to keep a close watch on how much energy is saved over a period of time.
Trapped
Energy saving is low-hanging fruit for many companies, so I would think this is a no-brainer and totally in line with the company’s strategy. On top of this, society expects manufacturers to fulfill their claim that they will contribute to solving environmental challenges. However, the reality is more brutal because of the “lean and mean trap”. The company management liked our value proposition enormously and they were also convinced that it could save them a lot of money. Yet in spite of this, the investment in model-based energy monitoring was rejected for the time being because they didn’t have the resources to execute the project. In other words, the company is so lean and mean that they lack the resources to change their business process for energy, even though it would help them to save money and solve environmental challenges.
Outlook
This is a constraint that is also affecting other companies. There are so many new opportunities for them to improve and save money against the background of IIoT, Industry 4.0 and IT / OT convergence, yet constraints on resources mean most of these projects can’t actually be launched. Maybe it’s time to invest more in resources and knowledge in order to get out of the “lean and mean trap” so that companies can make the transition with the support of technology and be prepared for tomorrow’s market conditions.
