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IoT and Digital Engineering
Bringing Together IoT and Digital Engineering to Create Rich Experiences
Highlights
- Manufacturers are looking for new business and operating models that will improve their profit margins, meet rising customer expectations, achieve regulatory and sustainability compliance, and adapt to the ever-evolving technology landscape.
- They are under constant pressure to make investments with a clear return on investment in a stipulated timeframe.
- We recommend a comprehensive approach for manufacturers to identify, realize, and maximize business value from their Industry 4.0 initiatives.
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Industry 4.0
Manufacturers are leveraging Industry 4.0 technologies to drive operational efficiencies.
However, measuring the business value of those technologies is difficult, as there is no systematic approach to do so. Ever-evolving technology is disrupting the way manufacturers run their businesses. Across the manufacturing value chain—production planning and control, asset maintenance and inspection, or logistics and inventory management—the impact of technology disruptions such as the recent advances in AI and generative AI (GenAI) are being felt.
To respond and adapt to these disruptions, manufacturers have been leveraging Industry 4.0 technologies to drive operational efficiencies, adopt new ways of engaging with customers, and operate in an ecosystem model across the value chain. When it comes to technology adoption, the big challenge CXOs face is not about use cases for technology adoption but how to approach, adopt, and scale Industry 4.0 technologies. They struggle to find answers to questions like:
- How do we avoid pilot purgatory?
- How do we measure the value and ROI of Industry 4.0 initiatives?
- How do we scale Industry 4.0 capabilities across plants?
- What are the industry best-practices to follow?
Measuring business value is quite subjective as it involves estimating the value of intangibles such as safety and sustainability in addition to tangible value that has a direct impact on cost savings or revenue. The lack of systematic approaches to guide enterprises toward successful adoption, measurement of key performance indicators (KPIs), and people and change readiness make the task daunting.
Navigating uncertainties
To realize the full value from their Industry 4.0 investments, manufacturers need to address multiple challenges.
The Industry 4.0 revolution and technologies such as the internet of things (IoT) have empowered manufacturers to improve their operational efficiencies and move to new business models, including servitization. They have accelerated research and innovation, driven speed to market, improved worker health, safety, while helping businesses meet their sustainability goals. In other words, manufacturers are better prepared to respond to change.
But often, manufacturers are oblivious to the full value of Industry 4.0 initiatives. An electronics contract manufacturer, which had more than 50 in-flight projects across more than 100 sites, had limited visibility into the business value that these projects yielded and the additional investments needed. While some pilots gave them the intended business value, scaling them across sites was a challenge. Figure 1 highlights the typical challenges manufacturers face while embarking on their Industry 4.0 journey. Unless such challenges are mitigated, business value and the ROI from Industry 4.0 projects will remain elusive. The question is, how do we overcome them?
Figure 1: The challenges manufacturers face on their Industry 4.0 journey
The winning recipe
To solve these challenges, manufacturers need to adopt a structured approach.
It will ensure a smooth adoption of their Industry 4.0 initiatives, yielding the intended business value.
Here are six steps that we recommend manufacturers to follow:
1. Value discovery: The first step is to take a top-down approach and identify their vision and objectives from Industry 4.0 and then combine it with a bottom-up approach of understanding their current challenges, needs, and aspirations. Manufacturers should reassess their current projects, objectives, and key KPIs being used; benchmark them with industry practices; and prioritize them in terms of accelerating or sustaining the pace and re-evaluating investments. The value discovery will identify current digital maturity and gaps along with digital capabilities and use cases.
2. Identifying KPIs and baselining: Next, manufacturers must map KPIs against use cases (both tangible and intangible) and their baseline data. Most commonly, they encounter challenges in identifying the right KPIs which can be addressed by:
- Standardizing methods of measuring a particular KPI: While it is a standard practice to report consolidated values at the larger organizational level to the leadership team by taking inputs from individual plants, we have observed differences in formulas used across plants, which lead to misreporting. For example, two different plants of an automotive original equipment manufacturer (OEM) measure the operational performance rate (OPR) of cars produced using two different formulas. Because the two plants use two different formulas to calculate the OPR, they both report a discrepancy in the volume of cars or build volume. To prevent such differences in reporting, manufacturers must standardize the measurement of KPIs.
- Standardizing source systems for data: To illustrate why it is important to select the correct source system and its data point to measure KPI values, consider an automotive OEM, which generated its management report at the end of a shift across its manufacturing sites. The report covered information about the number of vehicles produced and was accepted by the sales team. The OEM’s plant one used a manufacturing execution system (MES), while plant two used legacy facility monitoring systems. The data reported from plant two by the OEM’s senior management reported a discrepancy. It was observed that only the MES system provided the right data on the status of the vehicles.
- Identifying and measuring intangible business benefits: To measure the true impact of any digital intervention, manufacturers must identify the intangible benefits of those interventions. For example, predictive maintenance typically reduces machine downtime, improves productivity, and reduces the cost of maintenance, all of which are considered as tangible benefits. Since predictive maintenance prevents unexpected equipment failure that leads to accidents, it also increases safety on the shop floor, thereby boosting workers' morale. These are instances of intangible benefits. Measuring intangible benefits significantly impacts a manufacturer's revenue. For example, accidents and absenteeism cost manufacturers $1,000-$1,200 per month, whereas fewer injuries reduce absenteeism, and in turn, improve worker health and morale, costing manufacturers an estimated $400-$600 per month.
3. A business value framework: A KPI value framework, also illustrated in Figure 2, can measure the business value of Industry 4.0 use cases. For example, the KPIs impacted in a predictive quality analytics use case are scrap, first pass yield, and overall equipment efficiency (OEE). By baselining the KPI value and then estimating the KPI improvement on implementation, we can assess the financial impact of the use case.
Figure 2: Framework to measure the business value of KPIs
4. Cost governance: Manufacturers must allocate budgets for Industry 4.0 initiatives spanning opportunity discovery to industrialization, which are typically drawn over one to three years. The costs typically include build costs such as design, proof of concept, and more; cost of integrating different applications; infrastructure costs; annual maintenance costs (AMC); and license costs for third-party software—all these costs contribute to the total cost of ownership (TCO) for a use case.
Once the business value and TCO is available, manufacturers can prioritize use cases based on ROI from lowest to highest. Prioritizing these use cases based on ROI must be done through a governance forum involving all stakeholders. They must create and set up a transformation office (TO), which can govern, review, and measure business value and workforce change adoption, and keep track of these activities consistently.
5. Pilot site assessment and deployment: Prioritizing use cases based on ROI only will not yield the right business value. It’s also important for firms to understand which sites are ready for a minimum viable product (MVP) or pilot implementation in terms of infrastructure, master data, people, or change readiness. For this, they must perform a pilot site assessment, where they can rank sites or groups of sites, which will give them the maximum business value. We recommend the following parameters to conduct a pilot site assessment:
- Infrastructure readiness in terms of meters, sensors, servers, network, and more
- Master data readiness for each use case
- Integration readiness
- Team readiness such as availability of key personnel and roles
- People change readiness, whereby the current workforce has the skills to adapt to new ways of working
If a firm is not able to realize business value, then the firm’s transformation office should re-evaluate the use case and take necessary course corrections.
6. Scaling and sustaining the momentum: To realize exponential value, we believe the following considerations will be helpful for manufacturers to scale and sustain a use case solution across sites and geographies:
- Site readiness assessments covering infrastructure, master data, fit-gap analysis for process and assets, and people change readiness
- Grouping sites into sprints for parallel solution deployment
- Configuring the use case solution
- Testing and training
- Industrialization and business-as-usual (BAU) support
- Validation and incrementally measuring business value
- Continuous innovation
The next horizon
The advent of Industry 5.0 complements the advances made in Industry 4.0.
Organizations must embrace the ethos and values of Industry 5.0, such as human-centricity and sustainability in their manufacturing and supply chain processes, during their Industry 4.0 journey itself. Technological advancements such as GenAI are redefining the ways of working and are disrupting organizations as they build on the AI continuum. An organization’s transformation office plays a significant role in driving through this transition with right governance while nurturing the innovation process.
