Digitalised production - a holistic perspective and supportive working methods

Digitalisation in production - a tool for creating value

Digitalisation is often seen as a kind of multi-tool that can solve all kinds of problems. Digitalisation can be about very different things - from transferring previous analog information to digital form (sometimes called digitisation), and measuring and collecting more data, from more data sources, to being able to store and disseminate the information more easily, make more comprehensive analyzes , visualize, mm. Everything to improve working methods and results from work. Digitalisation creates opportunities to improve the way of working and offering you have today, to carry out your work in a better way (more sustainable, more efficient, more flexible, faster, cheaper, quality, etc.) or that the end result will be better (higher quality, flexible, better decisions , and more). The opportunities are great, but work with digitalisation does not always give good results.

In production, digitalisation is about the design and operation of the production system with, among other things, equipment that is increasingly digitized, automated and interconnected, increased data collection, for monitoring, control and analysis. But it is also about the fact that digitalisation can offer better information base and more advanced tools that facilitate and improve work with building, configuring, simulating, and installing systems.

It has been said and written many times - and is really a matter of course: digitalisation is not an end in itself but a tool to support work, tasks, decisions, collaboration, and learning. So it is important not to see it as a technical installation, but to be clear about why you are carrying out a digitalisation. That it creates added value for work, decision-making - internally in the organization or for relationships and deliveries externally, for example to customers. Even if this insight exists and if the intention is good, many unfortunately still easily fall into the trap of starting from software, technology solutions and have a superstition that it should solve problems they have, streamline work, etc. A new software can streamline the work for someone, but can also mean changed and expanded tasks for others in the organization.

Therefore, it is advisable to start from the value you want to achieve, and only then choose tools to achieve this - equipment, software, sensors, etc. digitalisation techniques.

Changed working methods, organization and competence needs

New equipment or software has a price tag that is clear. However, the cost of implementing this in an organization properly has no price tag, and can be difficult to assess and easy to underestimate.

Digitaliszation is a potent "tool" that can streamline organization, working methods in general. This is the strength but also a challenge - many people's tasks can be affected, both improved and worsened. It is then important to think beforehand so that the result for most people is a positive change in the organization, not just provides benefits in some individual respect, tasks, or certain group of people. To increase the chance that there will be a positive experience of a change, it is important to carefully reflect which different functions are affected, what impact the change has on established working methods, ergonomics, organization, meeting structures and competence needs.

Production and consumption of information

Digitalisation can be seen as an engine for achieving a data-driven approach where decisions are based to a greater extent on facts and less on gut feeling. The facts that are offered should provide increased knowledge, better ideas, faster work, better analyzes, better decisions, etc. This is one side - that information is demanded and creates value - is consumed. Consumers of information can be found in, for example, preventive maintenance, disturbance management, improvement work, quality management, or environmental management. The other side is where all data is collected and created - produced by machines, sensors, computer systems, etc. These two sides need to meet in a balance: on the one hand the production of data and on the other hand the consumption of information. Many industrial companies have the situation that they lack the information they need. The reason for this can be found on both the producer and consumption side, eg:

• The information produced is "put on the shelf", and made available to those who need it.
• Consumers do not know that the information exists, or how to access it.
• Consumers do not know what information they would benefit from, and do not even look for it.
• The information available is not sufficiently processed, analyzed or combined (cf. consumers want composite products in components).
• The information that is produced and available is not the one that is requested.
• Data that is the "raw material" for producing the desired information is missing.
• Data exists but is analog, has the wrong modality, low quality, not complete, not sufficient quantity to allow analysis.

Information needs

What information is needed? This may seem easy to answer, but it is more difficult than you think to describe the information you need to make your work more efficient, or with better results. It is simply difficult to understand what is missing, to see what does not yet exist.

To define the need for information, you can conduct a workshop. One method is to start from defining the goals (and any sub-goals) and what criteria there are for these. Then you list which parameters are the ones that make you know that the goal criteria have been achieved, or what the status is? Then you can list parameters that you know affect the process in a positive and in a negative direction. Information about these can be valuable to have information about, to be able to steer the process in the right direction. For the target and impact parameters, you can then describe which data you see would be needed and which processing/analysis of the information is necessary.

Describing information needs may need to take time - instead of directly defining all needs, you gradually learn what information is needed. The starting point is then an identified limited need. This is realized and tested and evaluated and new needs are defined that reinforce those already introduced. The idea is when you have offered users certain information, it is easier for them to see additional opportunities, more needs, more possible users and more sources of information that should be linked together. Step by step, you can then move towards an increasingly data-driven approach.

Think big, but start small

In the initial phase of digitalisation projects, technology challenges have proven to be less decisive than challenges in shaping the strategy. The main obstacles in the initial phase were considered to be a lack of strategy, lack of focus and low insight from the management. Technical problems become important obstacles later in the process.

For digitalisation, it is therefore an advantage to start from the value that you want to create, see digitalisation as a tool to achieve this. It is important to have a broad perspective on what is to change, and what will be affected. However, taking such a holistic approach can make the digitalisation project so large that one refrains. The key is to find a focused, more defined project, make sure to get started, test and evaluate, and based on that grow gradually grow in commitment, competence results towards a more long-term goal. A motto that can then be: "Think big, but start small, and learn and develop gradually". Great refers here to both a holistic perspective and long-term goals.

One way to create a structure for change work (digitalisation or other) and understand which project you want to start with, is to work to get consensus on what you want to achieve with the change, the desired situation, and to get consensus on where you stand today, the current situation . This latter is not as obvious as you might think - often you have from different functions a slightly different picture of working methods, or at least different pieces of the puzzle to a common more complete description of the working method. When you have this, you can identify possible obstacles, challenges, and risks with the change; and finally jointly describe which is an appropriate first step to take.

If, for example, in workshop form with representatives from different functions, jointly create consensus on the current situation, future goals, challenges and a first step, then you have a good basis for a smaller technology-driven change project, with good anchoring in the organization and good commitment to work. in a common direction.

Holistic understanding with the support of a canvas

Support is needed to understand, reason and plan digitalisation projects with a holistic perspective, but at the same time allow detailed planning. For this, it is recommended to use a "digitalisation canvas". Inspiration was taken from "Business Model Canvas" which is an easy way to get an overview of a large area but at the same time provides the opportunity to focus on specific challenges. Through such an approach and model, you obtain a visual tool that allows companies and groups to describe and think about all the interacting parts required to create a sustainable business model. The tool allows groups to form a common language and in a simple way discuss and create new strategic alternatives. It also provides a framework for continuous discussion and development. By having a canvas, you can see the whole more clearly, reduce the risk of losing important aspects, and jointly highlight the aspects that are most important to invest in.

The working method around the canvas can be determined according to the circumstances, but the intention is to jointly form an overall picture before the project. To fill all parts of the canvas, several workshops may be required - you can work with the canvas on paper, whiteboard or digital whiteboard. In addition, during the project it may be appropriate to update the image in the canvas together in the organization.

The proposed digitization canvas consists of eleven areas arranged in four main areas, see below. The order for working through the different parts of the canvas can be determined as needed, but the starting point should be business goals, delimitation to more focused goals, clarification of the need for information. Then it may be appropriate to describe what data is available, needed and missing, and the need for equipment and challenges regarding implementation and integration. The left side of the canvas focuses on the technology side, while the right side focuses on the softer aspects of working methods, organization, need for skills, and affected stakeholders. The bottom two fields are to highlight the negative effects and costs, and the positive effects and benefits digitalisation is expected to have.

• Business goal: What is the identified overall goal for the company and the business, which we can have as a guide in the change work? For example, that product quality is central to the business
• Focused goal: Based on business goals, you need to limit to more limited projects, among other things, you can limit to a certain subsystem in production, select a pilot plant, and decide what you want to achieve in the short term with the digitization initiative? For example, you may identify a specific machine in production that is central to ensuring product quality.
• Need for information: What information is needed to provide the support that is desired, which provides the opportunity to steer and decide against the chosen goal, what insights do you want to be able to measure? For example, to achieve higher quality in the process in the machine, certain identified measurements of the products are needed.
• Data: Data availability today, ability to collect, media, quality, quantity, modality, etc.
• Need new data to meet information needs and goals? For example, some of the desired measurements may be available, but with poor accuracy, other measurement data are missing.
• Equipment: What is available today? What is needed for data collection, data management, analysis, visualization, etc? For example, what measuring equipment is needed for the desired measurements.
• Integration: Installation and integration of a new solution with existing systems, equipment/IT infrastructure, access? For example, how should the measuring equipment be integrated with already existing computer systems?
• Work processes and organization: Impact on staff, working methods, methods, organization, meetings, decisions, ergonomics? For example, who should carry out measurements, how should it be carried out, and how does it affect ergonomics and the work environment?
• Knowledge, culture and leadership: Important skills that need education, training, culture, motivation, attitude, etc.? For example, do the new measurements of the product require that extra training efforts are needed?
• Stakeholders: Who will be affected and how do these need to be handled, etc., both internal and external stakeholders? For example, who in the company is interested in seeing the measurement results?
• Costs, negative effects: What does the project cost – in total for handling various aspects above? What negative effects are there a risk of? For example, how much do product quality deficiencies cost annually?

• Profits, positive effects: What will the profits, savings with the investment be, etc. environment, work environment, ergonomics, attractiveness, etc.? For example, what other effects do we see around increased sustainability and more stable production.

The article is written by Per Gullander from RISE (Research Institutes Of Sweden)