Is digitalization suitable for SMEs? Any company of any size can define a deep industry 4.0 transformation roadmap, or this is just a big players game? How to find what it takes to start a rollout?
Small and medium-sized enterprises (SME) are at the core of business development in Europe. 25 million companies, producing 50% of European GDP and 2 out of 3 jobs are coming from SMEs. Digitalization should be the cornerstone for business success but somehow we need a final push to jump from the springboard, when it comes to implementation.
What it brings. Clarifying goals to be achieved.
Opportunities coming from an Industry 4.0 roadmap are on everyone’s lips, but sometimes it’s not so easy to find arguments to justify our own case and move ahead. Here are some clues that can be helpful in order to understand what digitalization brings to a SME.
| Cost reduction | It’s easy to think that one of the first source of benefit that can be identified is close to direct labor cost reduction. Automatization of manufacturing operations and tasks performed by workers comes to direct headcount savings.
Nevertheless, the impact in indirect labor is also relevant. Information gathered from the shop floor is downloaded into a data lake creating a structured plant information map. Dashboards and both real time and historian analysis tools are deployed to help decision taking. This deployment comes with the reduction of non value tasks and the optimization of indirect labor. |
| Increase of plant capacity | OEE and LTA (lost time analysis) metrics allow to identify hidden sources of waste.
Plant teams are trained in lean manufacturing techniques and waste reduction initiatives become part of day to day factory culture. New machine capacity arises as waste is been reduced. |
| Eco compliant
factory |
Resources usage (water, coolants, energy ….) can be easily gathered from IoT devices. When included in the equation, sustainability metrics are calculated and so the impact on the environment can be tracked.
Very often environmental care can easily be translated to cost saving figures. |
| Customer loyalty | Production follow up, idle times identification and wip optimization come to lead time reduction. Depending on the manufacturing strategy (product structure and process flow) savings can be huge.
Variance reduction (with 6sgima, SPC or deep knowledge models) increase process robustness and therefore lead to higher quality standards. Both lead time and non-quality reduction are key factors to increase customer satisfaction. |
| People development and organization growth | Data becomes a new raw material. The smart use of factory data leads to new disruptive opportunities.
o Machine learning models based on real data allow to create explicit knowledge on how processes work, and to deploy this knowledge organization wide. o New capabilities are developed in existing workers mixing up both manufacturing and IT skills. o Business as usual is continuously questioned and innovation processes are part of day to day job. o Plant is a technological entity plenty of attractive for new talent recruiting. |
Adding the specifics of each industrial sector and the maturity level of each company, the above arguments, and for sure many others, can be the basis for setting up a reliable transformation project.
What it takes. Best practices tips
Transformation roadmap is not an easy process and there are many decisions to be taken that can make the project fail. There are some tips that can help in the early stages
Make your customer the hearth of the process. Market trends and customer needs are changing. Define your goal starting from your market/customer requirements and then design the transformation roadmapOnce our goal with digitalization is fully understood a tangible case study can be set and will clarify the benefits of deploying a transformation roadmap. Financial figures based on short term benefits are needed, but beyond this, there are insights that if properly focused to cultural change that can boost ROI. Don´t forget to add them to the magic formula
