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Why digitalizing manufacturing processes benefits more than just manufacturers

The first Industrial Revolution marked a shift from old ways to a new, more innovative paradigm. Today, two centuries later, the “fourth Industrial Revolution” (also called “Industry 4.0”) marks a similar seismic shift, not just improving on old methods but creating new ones from scratch.

For manufacturers, this transition to a fully digitalized manufacturing process will mean a total transformation of their production and marketing cycle, with developments occurring at an exponential rate. The race to digitalize is already transforming operations, processes, energy footprints of factories, and management of manufacturing supply chains.blog-line-break-01

Why digitalization matters for manufacturing?

The benefits of digitalization, while extensive, can be summarized in a few key factors. 

Digitalized processes can enhance productivity—allowing the adjustment of production processes in real-time to adjust to evolving situations and helping managers make more informed decisions. Smart, IIoT-driven tech can help technicians predict and resolve maintenance issues long before they’re evident—saving time and capital costs.

And a reduced total cost of ownership (TCO) also results from digitalization due to AI-driven increases in efficiency and capacity; lower labor costs; and increased supply chain visibility that translates easily into savings in production volume or delivery timetables.

While the technology that drives it today has only matured in recent years, competition and wider adoption has driven the cost of digitalization down, even as capabilities have increased for Industry 4.0 staple technologies like cloud computing, industrial robotics, Industrial Internet of Things (IIoT), and machine-to-machine (M2M) communications further enabled by 5G.

This only means that digitalization through Industry 4.0 will be more accessible for a wider group of adopters, unlocking more benefits for more people and businesses.

blog-line-break-02Understanding digitalization terms: Industry 4.0, Digital Transformation, Internet of Things (IoT)

The first step to understanding how digitalization can help your specific industry is to understand its most essential concepts. Each of these interrelated terms will reoccur throughout any conversation about digitalizing the manufacturing process: each refers to a distinct aspect of the industry as it changes.

    • Industry 4.0 is a paradigm: the combination of “manufacturing techniques with the Internet of Things to create manufacturing systems that are not only interconnected, but communicate, analyze, and use the information to drive further intelligent action back in the physical world.”

      As paradigms go, this one is pretty broad, even if well-defined: its ideal is embodied in data-driven, AI-powered, networked “smart factories” that leverage data to drive production efficiency and flexibility.

    • Digital transformation is the process of embedding new digital technologies and capabilities into tools and processes, resulting in near-total networking of people, machines and “smart” objects in physical and virtual realms.

    • Internet of Things (IoT) refers to devices that transmit data to each other over the Internet: not just computers or cellphones, but also IP-enabled “things” like smart electricity grids and sensors on the production line. Data collected by IoT allows managers to create and act on insights (for instance, adjusting power demand based on predictive analytics).

Think of IoT as an essential component and enabler of Industry 4.0, and digital transformation is the process of adopting IoT and other hallmarks of digitalization to align completely with the Industry 4.0 standard.

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Common digitalization challenges for manufacturers

Digitalization is a long-term investment and change process. Starting the process with a lack of knowledge or understanding of the commitment involved can lead to the failure of the transformation project. The areas listed below represent some of the most common challenges faced by manufacturers.

strategy01Strategy: 

Lack of a clear strategy at the top can hamper even the most motivated digital transformation initiative. A Celonis survey found that 45% of respondents didn’t know how to start developing their transformation strategy, with 41% of senior leaders believing their digital transformation efforts have been wasted.

People: 

Digital transformation can be a hard sell to a workforce accustomed to certain work practices. As the changes required by digitalization can require a top-to-bottom revision of both processes and personnel, affected employees often push back on the effort. Only a minority of employees tend to take ownership of any digital transformation initiative; a McKinsey report found that as little as 11% of employees in companies with failed transformations were engaged in the process.

Budget: 

Even as corporate spending on digital transformation rises (reaching a projected US$1.3 trillion worldwide in 2020), the budgeting process still gets in the way of CIOs driving digitalization efforts. This comes from conflicting mandates from different departments: CIOs need a flexible budget for digitalization that allows for adjustment to unpredictable factors. At the same time, accountants require more certainty about the spending and outcomes that aren’t available early in the process. This often results in red tape, approval delays, and extensive changes in the plan to compromise between finance and operations. 

Process: 

Integrating Industry 4.0 equipment with existing systems in the digital commerce infrastructure is one of the primary challenges for most manufacturers. Many decision-makers are reluctant to dispose of legacy equipment and programming, given the significant investments in time and expense sunk into them over time. Trying to bridge modern cloud-based systems with legacy solutions can mean more expenditures for customization or the purchase of new tools or programs.

Data: 

The gap between unrealistic expectations and the practical realities of using (and managing) the big data sets that come with digitalization can cripple the transformation initiative at the outset. Many CIOs might enter the process associating machine learning and AI with “magic”, not realizing that these are tools that suit very specific goals. As a result, they may start the transformation process with unrealistic expectations that no implementation can reasonably address, leading to disappointment all around.

blog-line-break-04How can manufacturers begin the digitalization journey? Where to prioritize?

With so many moving parts, digitalizing one’s facilities to Industry 4.0 standards can be messy and expensive. Knowing where to start is half the battle won. 

Strategy:

Digital transformation should take direction from a broader business strategy—it cannot be the end in itself. The consensus from a recent BCG study defined a winning strategy as “a clear vision backed by a set of strategic imperatives and quantified business outcomes, linking digital to the overall business strategy and sustainable competitive advantage”: something that only 40% of respondent companies were able to pull off.

People: 

To get increased buy-in from all stakeholders, you need to give a concrete meaning to the digital transformation effort. “Employees must understand what it is they need to support before you can drive buy-in and adoption,” explains change management consultant Jeff Skipper.

The question “What will a successful digitalization effort do for them—and the company?” should be answered in a meaningful way—through a demonstration of how an employee might benefit in their day-to-day work, for instance. “Give them a target they can identify with and aim towards,” Skipper suggests.

Budget:

Operations and finance departments must reach a consensus that dispenses with traditional budget approval and funding requirements without compromising the need to see cost-effective results down the line.

Peter Bendor-Samuel, CEO of the research firm Everest Group, suggests taking an iterative approach to the transformation process, taking a page from the Minimum Viable Product (MVP) workflow. “Instead of having a detailed road map upfront... break a project down into a series of gates,” Bendor-Samuel explains. “Develop a detailed plan only for the range of where the company currently is up to the next gate. And associate funding per gate.”

This iterative approach allows leadership to gather confidence and renew commitment as they move from one gate to the next. “Despite the many unknown factors at the outset, they can control risk by funding the journey flexibly, gate by gate,” Bendor-Samuel says.

Process: 

Decision-makers must review how each existing project or process will function in a post-transformation setting. If it’s not possible to replace legacy systems completely, decision-makers can opt for middle-road options like fully automated migrations that use refactoring technology to adapt legacy code and data to the newer technology.

“Fully automated digital migration allows organizations to pursue legacy modernization at their own pace,” a Deloitte paper on legacy modernization explains. “Refactoring a legacy application, for instance, can deliver ‘quick wins’ by reducing potential risks and improving IT efficiencies.”

Data: 

A clear, actionable strategy (see the first point) can help bridge the gap between unrealistic expectations and achievable outcomes. This allows the organization to use big data in a focused, results-oriented manner. A McKinsey survey found that companies that narrowed their digital transformations in this way were 1.7 times more likely than others to report that the transformation’s results had surpassed expectations.

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Data on the move, from factory to store

With all these moving parts working in concert, it’s child’s play to leverage Industry 4.0-collected data beyond the factory floor. 

data01Plans may expand in scope beyond IoT sensors and robots to cover even e-commerce digitalization in the future: thanks to digitalization, the IoT and e-commerce can work together seamlessly.

Data collected from digital commerce platforms can tell planners what products are preferred and what locations receive the most demand—allowing manufacturing facilities to adjust their operations to adjust to these changing realities. It can also provide insights on customer buying journeys so manufacturers can work towards creating more personalized experiences

IoT technology has matured enough to blur the lines between manufacturing and sales: GPS or RFID monitoring can help track deliveries and inventory, giving customers additional peace of mind; manufacturers can also proactively provide consumables or spare parts based on data collected by IoT sensors on customer premises.

Down the line, manufacturers can coordinate with their customers to provide personalized B2B service for the latter’s clients, who can order effortlessly through headless e-commerce infrastructure that works on any touchpoint.

blog-line-break-06Improving outcomes beyond the factory floor

More manufacturing decision-makers are learning that digital transformation towards Industry 4.0 benefits everyone. While increasing efficiency and quality on the production line in the short term, digitalization also affects downstream functions like e-commerce—improving outcomes not only on the factory floor but in customers’ experiences as well.

According to a “The State of Digital Innovation within Manufacturing” report by Copperberg and Intershop, 55% of manufacturers will invest in a digital customer in the next 12 months. Having a single portal for customers to oversee and manage their services can create better, more personalized experiences to optimize their buyer journey. 

Successful digital transformation requires both a considerable investment in infrastructure and a thorough change in mindset. Bringing both to a successful resolution is part of what Intershop does; if you’re ready to digitalize your manufacturing floor and reap the benefits, request a demo now.