Benchmarks & Case Studies

Diagnosis and Digital Transformation Planning for an Electrical Components Producer


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 that are integrated with the rest of the solutions produced by other companies in the group to deliver a complete solution to its customers. This factory has 90 workers and an annual turnover of €30 million and the production process is mainly manual assembly and final testing.

The company specializes in the design and production of customized solutions which generate a high level of variability in the production process. 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 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 prioritizes the initiatives, sequencing them in an optimal way, and helping to define the necessary investments and the potential benefits.

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

The approach

This 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 results. In turn, this approach makes it possible to understand the transformation needs adjacent to the implementation of technology (process transformation, people, business model etc.) and how these implementations must be synchronized.

Current state analysis

The first step is to conduct 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 must 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.

Future vision design

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 in the market that cover the needs detected.

In this case, the main solutions proposed were:

  • Digitalization and automation of the planning flow from orders reception to detailed lines sequencing and supplier planning and communication.
  • Implementation of a MES system to digitalize the production management from data capture and reporting to planning and resources management.
  • Development of interactive work instructions – critical in this high complexity and variable manual assembly process.
  • Implementation of a warehouse management system to optimize picking processes with information on mobile devices, optimize picking routes, and poka-yoke systems to avoid picking errors etc.
  • Update all engineering and product development tools (simulation, digital mock-up, content management, project management).
  • 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 analyze 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 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 allows us to define the speed and sequence of implementation.

In this case, a four-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. This impact comes mainly from different origins:

  • Reduction of engineering time and lead time to develop new products.
  • Increase line efficiency by reducing product design errors, material supply delays, assembly quality problems and improve production data visibility in real-time.
  • Increase logistics efficiency in picking and reception process.
  • Increase the productivity of planning and material supply teams by automating most manual tasks.

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