Background image: Prioritizing People

Prioritize People when Digitally Transforming Your Manufacturing Operations

Digital Transformation of manufacturing operations is top of mind for most manufacturing leaders as what’s needed to stay competitive in the market. The manufacturing environment is ripe with underutilized data that can be used to make faster and more informed decisions and actions. Organizations that have successfully implemented and executed a digital strategy at a plant or enterprise level are seeing strong double-digit improvements in productivity, quality, lead time, on-time delivery and inventory.

However, only 25% of manufacturers have scaled digital systems at an enterprise level. Most of the other 75% are still defining their digital strategy or stuck in “pilot purgatory”.

If the results of a successful digital transformation are clear and technology solutions are readily available, what is holding manufacturers back from realizing the value to be had?

The answer is that digital transformation is truly a paradigm shift for the organization. While the tendency is to focus on the technological enablers, organizational adoption is an often overlooked, critical link between having the right technology and achieving a step change in operational productivity. Here are four realities a manufacturing organization must address to be successful in a digital transformation.

From top to bottom, employee roles are going to change.

At the core of digital transformation is the enablement of employees to achieve their individual and organizational goals more efficiently and reliably, and that only happens when those employees significantly change how they conduct their day-to-day work. With the influx of readily available data and information, the roles of both front-line employees and managers will need to change to achieve greater productivity.

As systems are connected and processes are digitized, many information-based tasks that were once done manually by manufacturing associates and team leads, such as data collection and reporting, become automated. This is an opportunity to evolve the roles of those employees from repetitive tasks to more analytical and problem-solving work. However, if an employee typically spends many hours a week collecting data and building reports, natural responses to this change include hesitation to use digital tools or fear of reduced job security if not addressed directly.

Digital transformation enables decisions to be made much faster - even in real-time. However, if all those decisions are still made by a small number of operations managers, a manufacturer may end up with an information and decision-making “bottleneck,” significantly reducing the potential value of the technology. How decisions are made and at what level will change. A culture that embraces digital is one where all employees, including manufacturing associates, are empowered to make real-time decisions relevant to their role and act accordingly. This can be quite the change in management style for many experienced managers and executives in manufacturing. A culture of “democratized decision-making” is needed to achieve higher levels of agility and productivity.

Implement a proactive change management strategy to engage all impacted employees early in the change process, incorporating employee feedback into the solution design and implementation, and building change champions amongst employees to advocate for the change. A robust change management plan helps bring employees along the transformation journey and minimizes change detractors.

New technologies create new talent needs.

When implementing digital technologies, new skill sets in Internet of Things (IoT), data science and cybersecurity are required. Demand for these skill sets has increased far faster than supply, making it hard to find new talent, especially in many locations where manufacturing resides. In addition to partnering with industry and technology experts, manufacturers should consider upskilling their existing workforce for sustained adoption and continuous improvement of digital solutions.

A common misconception is that data analytics always require data scientists. While that is the case with advanced analytics, such as machine learning and AI, a data-driven culture means that competency in data analysis tools and methods needs to be pervasive across the company. Manufacturers typically already employ process-driven, analytical people. With the right training and development, these same employees can become resident data analysis subject matter experts.

When employees combine new knowledge of data analysis with their existing knowledge of the processes and machines, they can quickly be at the forefront of a digital journey. Reskilling and upskilling an existing workforce contributes to long-term improvements in employee engagement and retention, increased cross-functional collaboration, and adoption of modern technology trends.

Beyond explicit technical skills, employees need to be skilled at diagnostics and problem solving using the data now readily available to them. Employees that were previously only data gatherers are instead being asked to problem-solve based on new data-driven insights. Organizations need to make sure their employees are ready to learn and grow to take advantage of these opportunities.

Functional groups that need to work together can have different priorities.

Without a doubt, the convergence of Information Technology (IT) and Operational Technology (OT) is driving the tremendous opportunity that digital transformation brings. But that does not mean existing IT and OT teams are always on the same page. OT and operations teams are focused on improving the productivity of the plant – making more product for less cost. On the other hand, IT is typically more focused on sustaining enterprise platforms and mitigating cyber risk. These do not have to be mutually exclusive priorities, but without a cohesive and collaborative approach, including the right organizational design, it can feel like an uphill battle the whole way.

Competing priorities can also result from how projects are funded. OT teams are often focused on solving problems in one plant and sometimes even incentivized to compete against other plants within the same supply chain network. IT teams may be more interested in a scalable solution that benefits all plants but are not able to fully fund a project.

The success of digital transformation is dependent on effective collaboration of both IT and OT teams. OT teams bring the manufacturing process expertise and knowledge of where the data is born. IT teams ensure that the enterprise platforms and requisite network infrastructure are reliable, scalable, and secure. Organizations must determine how to align the objectives of both IT and OT teams supporting digital transformation initiatives.

Consider formalizing initiative teams dedicated to digital transformation with leads and subject matter experts from both IT and OT functions. These cross-functional teams, funded jointly between Operations, Engineering and IT, would collectively define initiative objectives, collaborate on implementation plans, and be the change champions across the organization. They should have a common group of executive stakeholders, read out progress together, and be rewarded together.

Organizations in a digital world need to adopt a faster pace for learning and change.

Manufacturing and automation projects are often high capital expenditure investments with long project timelines, where a mistake can be extremely costly. Digital initiatives should not be seen the same way. Instead, they are opportunities to iterate rapidly based on lessons learned and to leverage agile development methods to implement new functionality. This necessitates a culture where each iteration becomes an opportunity to learn and continuously grow. Core attributes of “learning organizations”, a concept popularized by Peter Senge, include systematic problem solving, experimentation, and knowledge transfer.

Systematic problem solving incorporates generating a hypothesis, testing that hypothesis, and using data, as opposed to assumptions, as the basis for decision-making. A minimum viable product (MVP) approach can be used to quickly test a hypothesis and generate data to evaluate the solution’s efficacy. When using a common enterprise platform, an MVP can be scaled across the enterprise quickly once deemed impactful.

Promoting experimentation is key for pursuing continuous improvement using digital technologies. Ensure your organization leverages an incentive system that favors a degree of risk taking, where employees, trained on how to conduct experiments using digital technologies, feel that the benefit of introducing change outweighs the potential costs. This requires strong executive leadership that is reinforced through change enablement coaching on a regular basis.

For a digital solution or use case to provide its full impact, it needs to be scaled effectively across the enterprise. Learnings from the first implementation must be shared in detail with other plants to enable this scale. Consider a Center of Excellence where manufacturing process and technology subject matter experts support or drive the first implementation and take those learnings for subsequent implementations in other plants.

Bottom Line

For digital transformation to create significant, lasting results, the organization will need to address disruption in terms of role changes, new talent development needs, revised organizational structures and an urgency to adopt a faster pace of change. A strong strategy around organizational and people transformation efforts must be a key accompaniment to any successful digital transformation

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