Benchmarks & Case Studies

Diagnosis and Digital Transformation Plan

This project arose from the need to establish a short, medium and long-term digital transformation plan that is aligned with the company's strategic goals, focused on having a real impact on processes, improving people's work in a disruptive way.

The company

This company belongs to a Spanish multinational dedicated to the production of solutions for electrical substations in primary and secondary distribution. The case study factory produces protections and automations, which are integrated with the rest of the solutions produced by other companies in the group to deliver a complete solution to its end customers.

The case study factory has 90 workers and an annual turnover of €30 million.

Within the group, this plant is a production unit, so the analysis mainly covers operational areas directly linked to production, including product and process engineering, procurement, planning, internal logistics and production.

The company specialises in the design and production of customised solutions, which generates a high level of variability in the production process. The products can be grouped into 3 large families: standard products (catalogue products with high demand), standardised products (catalogue products with low demand) and special products (non-catalogue products).

The production process is mainly manual assembly and final testing. Due to the high variability of the product, the supply of materials to the lines is mainly done in specific kits. Similarly, the documentation required for production (wiring diagrams, assembly instructions etc.) is generated specifically for each unit.

Production is made to order in 100% of the cases and most of the components are purchased and supplied against a specific order.

The challenge

The company has been working for years on the implementation and evolution of its continuous improvement system (Kaizen) as well as the improvement of production and logistics processes within the group's global strategy.

In recent years, some initiatives have been launched in the field of digital transformation, but the need was detected to create a structural plan for digital transformation that covers all areas of the company and its processes with the aim of creating a global plan that prioritises the initiatives, sequencing them in an optimal way, and helping to define the necessary investments and the potential benefits year after year.

The main opportunities for improvement are in the area of digitisation and automation of information flows that drastically reduce the need for manual handling of information, as well as improving the visibility of the status of processes, the reliability of data and the information available, thus reducing errors.

The information flows analysed are transversal to the different departments, including interaction with customers and suppliers.

The approach

The methodology used for the analysis and design of the digital transformation plan is the Digital Transformation Value Stream Analysis developed by the Kaizen Institute.

Most of the methodologies developed by consultancy firms, universities and research centres to carry out a digital transformation diagnosis focus on auditing and comparison with sector benchmarks. The Digital Transformation Value Stream Analysis methodology has its focus on a detailed analysis of processes and value chains, which allows identifying opportunities for improvement and designing solutions that go directly to the point of impact on the generation of results. In turn, this approach makes it possible to understand the transformation needs adjacent to the implementation of technology (processes transformation, people, business model etc.) and how these implementations must be synchronised.

The methodology starts with an end-to-end mapping of the material flow and the main information and data flows. In this stage, main opportunities for improvement, waste and process variability are identified.

The detected opportunities have to be grouped in different lines of solution analysis, as it is most common that many of the detected opportunities will be treated under the umbrella of the same solution.

In this initial analysis, opportunities for improvement were detected, mainly focused on:

  • Lack of visibility of process status (from order acceptance, solution design, procurement and production).
  • Information flows and databases that are not robust, are manual, and have little traceability of information.
  • Lack of data for decision making
  • Inaccurate and unreliable data
  • Duplicated information in several locations and not updated
  • Difficulty in finding the necessary information, rework and associated efficiency losses.

The next step focused on the analysis and macro design of solutions on the different improvement opportunities detected. During this step, it is essential to establish a list of requirements and necessary functionalities of the solution to be implemented, as well as a macro design of the architecture of the solutions that allows us to understand what we are looking for. This makes it much easier to find solutions on the market that really cover the needs detected.

In this case, the main solutions proposed were:

  • Creation of a database of process times, associated with a product configurator, to automate the calculation of personnel requirements based on demand, as well as product labour costs.
  • Digitalisation and automation of the planning flow by updating the ERP system, as well as the implementation of cloud platforms for data and information management with suppliers and customers. In turn, the development of an Advanced Planning & Scheduling (APS) module that allows them to automate capacity and sequencing planning in an optimal way, being able to carry out simulations and scenario analysis based on confirmed and unconfirmed orders.
  • Development of interactive work instructions, automatically configurable based on the configuration of each specific product. These instructions will evolve towards more dynamic supports such as video, interactive 3D plans and augmented reality.
  • Lack of data for decision making
  • Implementation of a document management system to ensure the reliability of information, as well as to reduce search times, eliminate errors due to incorrect or outdated documentation and eliminate rework.
  • Implementation of a warehouse management system to optimise picking processes with information on mobile devices, optimised picking routes, poka-yoke systems to avoid picking errors etc.
  • Update of the product design systems to allow the integration of electrical and mechanical designs to be tested in a virtual environment.
  • Development of a digital twin of the product to automate the integration test of the product control software, reducing the time required and eliminating the possibility of sending products with defective software to the customer.
  • Adaptation of the company's daily management dynamics to adapt to the availability of real-time information, enabling the reduction of response times and effective use of data to analyse and resolve incidents in a structured way.
  • Design of a governance model for digital transformation, ensuring the coordination of the transformation plan, including the evolution of people and their skills, processes and technology.

The last stage of the analysis consists of calculating the impact of the different work lines based on the data collected from the process, as well as an analysis of the necessary investment and the expected return.

This last stage also includes the creation of the transformation roadmap where it is essential to consider the priorities of the company, the impact of each solution, the logical sequence of implementation, as well as the availability of human and economic resources, which allow us to define the speed and sequence of implementation.


In this case, a 4-year implementation plan has been established, which can be reviewed every year following the Digital Transformation Value Stream Analysis methodology.

The calculated potential of the transformation plan has an impact of 17% on the company's EBITDA.

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