Market leaders in all industries generally consider the implementation and integration of technology related to Industry 4.0 as one of their key strategic priorities. This is reflected in the way that many companies try to position themselves at the forefront of technological developments such as Big Data, Artificial Intelligence (AI), the Internet of Things (IoT), Robotisation, Additive Manufacturing, Augmented Reality, Virtual Reality, Digitalisation or Cloud/Cyber Security. There is a common understanding that these breakthrough technologies have the potential to deliver competitive advantages in relation to operating cost, quality, Lead Time, product customisation and customer service.
Quality indicators are one of the fundamental aspects of business performance that can be positively impacted through the use of these technologies. Quality improvements can encompass metrics in relation to finished goods, raw materials, process adherence and data integrity. Companies tend to expect a sustainable competitive advantage following the implementation of these technologies within their business. Nevertheless, the capability of many companies to execute the integration of these technologies effectively is lacking due to several reasons:
- Most companies do not have a clear implementation strategy. In many instances, business units work on different isolated initiatives, which are managed and implemented independently without a clear execution model. This approach results in a failure to take advantage of existing synergies between different technologies, incorrect investment prioritisation (the major challenge in the progression of industry 4.0) and the ineffective planning of resource capacity.
- An accurate analysis of the return on investment is not always undertaken due to a lack of technical knowledge or reliable information. In many cases implementing a project in this area requires a considerable investment, therefore an accurate return on investment analysis is crucial to assist in objective and unbiased decision making.
- Many companies have not reached a level of maturity and standardisation in their processes to successfully apply the full potential of the technology. A lack of process clarity at the starting point of implementation may lead to critical mistakes such as investment in areas with little or no short-term impact, or the automation of non-value-added activities. Some examples of low maturity implementation are:
- Robotisation of processes that retain a high level of inefficiencies, with uncontrolled non-quality sources and a lack of standardisation.
- Implementation of Big Data or Artificial Intelligence tools in processes with not enough data depth or reliability, which will generate models with limitations.
- Digitalisation without the guarantee of integration between systems. This can cause scattered information, increasing the probability that information is outdated or incoherent.
- Lack of internal knowledge regarding the technologies implemented. This generates a challenge to the sustainability of the new technologies and can lead to negligible performance benefits obtained from their application. The engineering team who lead the implementation, as well as the day-to-day users of the systems, should all be trained and competent in the use of the new tools and technologies at a level which reflects their needs.
- Inadequate change management systems. The implementation of new operational systems with a high impact on work collaboration, requires a flexible organisation with a great ability to adapt to change and manage processes. We see many failures arising from resistance to change and a lack of agility and flexibility within organisations which are not prepared for such change.
In response to the points mentioned above, the proposed implementation roadmap should begin with an Industry 4.0 strategic planning phase with the following steps:
1. Establish the long-term strategic goals of the organisation (5 years) and short-term deployment initiatives (1 year), based on the market conditions, competitors, suppliers, customers, investors, etc.
2. Based on these organisational goals, perform a detailed analysis (Value Stream Analysis) of the main value chains of the organisation. In this analysis, the current level of maturity of processes is assessed with the goal of implementing the new Industry 4.0 technologies. A selection of the most adequate technologies for each case is carried out along with the identification of pre-requisites for implementation.
3. Based on the detailed analysis of the operations, different implementation scenarios are created, including the analysis of the return on investment. This enables the comparison between scenarios which supports effective decision making.
4. Establish a detailed prioritisation and implementation roadmap, adopting a holistic approach where implementation is considered as a whole project and not as a series of isolated initiatives. This implementation roadmap considers technology synergies, the ideal sequence of implementation, and the preparation of the organisation for change. There is a focus on the optimisation and standardisation of processes, as well as the ongoing capability to deliver effective training and retain agility to market changes.
5. For each of the initiatives defined in the roadmap, an indicator is established to measure their contribution to the defined strategic goal defined for the project. This ensures the top management of the organisation is directly involved and committed to following up on the initiatives defined.
6. Create an effective monitoring system for the implementation, which eliminates bottlenecks and allows for agile decision making, involving the top management. Technology evolves so quickly that if you are unable to create rapid implementation cycles, it is highly likely that you are already making implementation decisions for outdated technologies and not the technologies of tomorrow.