Since the First Industrial Revolution, a relentless pursuit of producing more product faster and with higher quality has been the key driver of all change and innovation in manufacturing. So when computer hardware and software systems became generally accessible in the 1950s and 1960s, it’s no surprise that manufacturing was among the earliest – and most lucrative – applications. But as the number of discrete, purpose-built manufacturing software applications has grown significantly over the past several decades, many manufacturers now find themselves asking: “when is enough software enough?”
As quickly and profoundly as computing technology has advanced over the past several decades, so has the environment in which commerce takes place. Since the modern manufacturing paradigm took shape around the mid-1900s, the forces driving competition have grown progressively more demanding: companies have expanded their presence to multiple sites and regions to take advantage of cheaper labor or proximity to raw materials; the supply chain has expanded enormously; and lead-time demands on both the supplier and manufacturing sides have greatly diminished.
To manage these moving parts, companies turned to information management systems early on in order to reduce cost, improve logistics and ultimately, remain competitive. Implementing these enterprise solutions, therefore, was not seen as a choice, but a necessity.
Most of the traditional systems in the manufacturing enterprise software space are complex, expensive and extremely powerful. They are known to require significant intervention from consultants to properly customize and implement them according to a company’s unique business needs. And still, companies must adapt their internal processes to align with the prebuilt workflows and capabilities of the software. Even so, these off-the-shelf solutions offered many advantages to the antiquated, homegrown, company-specific solutions that were the only alternative at the time.
Over the years, the portfolio of commercially available enterprise solutions expanded to address the industry’s ever-changing needs, but also to take advantage of new and more powerful technology. The result was a steady release of software applications that built on the capabilities of their predecessors, starting with relatively simple inventory control (IC) systems in the 1960s, then material requirements planning (MRP) and manufacturing resource planning (MRP II) in the 1970s and 1980s, followed by enterprise resource planning (ERP), manufacturing execution systems (MES), customer relationship management (CRM), supply chain management (SCM), product life cycle management (PLM), and many others from the late 1980s until today.
Traditional enterprise software solutions were not just a passing craze, however, with many having a ubiquitous presence across the industry to this day. In fact, the latest forecast by Gartner predicts that worldwide IT spending on enterprise software will increase from $457 billion in 2019 to $507 billion in 2020 and $560 billion in 2021(1). At a growth rate of 10%, this significantly outpaces that of any other investment category addressed in the study, consisting of data center systems, devices, IT services and communications services.
According to Gartner, the industry currently finds itself at a crossroads when it comes to merging the power of existing practices and solutions with the opportunities that new tech presents.
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“Most companies are caught trying to either cut costs or invest for growth, but the top-performing enterprises are doing both,” said John-David Lovelock, research vice president at Gartner. “A core challenge facing the industry is how organizations can operate as both a traditional company and a technology company at the same time. These ‘and’ dilemmas will drive future IT spending trends.”
Lovelock drew a comparison to the consumer tech market.
“Similar to how consumers have reached a threshold for upgrading to new technology and applications, technology general managers and product managers should invest only in the next generation of products that will push them closer to becoming a true technology company,” Lovelock said.
According to a Strategy+Business article(2), the types of enterprise software initiatives implicated in the Gartner report can be thought of as “big automation” – with big budgets, timelines and goals. These IT initiatives involve traditional software systems like those mentioned above that have long helped companies streamline processes and track data.
However, the article cites findings from PwC demonstrating that despite the automated nature of these systems, many of them still require significant manual processing to gather data from various systems that are dependent on highly structured and siloed databases. If the data is unstructured – which is very often the case – it is virtually useless to these systems.
“As a result,” states the article, “although enterprise IT remains essential to companies’ business operations, many of these systems have reached the point of diminishing returns.”
Despite the robust enterprise software in use by most manufacturers, paper persists across the business. Skilled personnel find themselves spending large amounts of time reconciling data and information from separate sources, often on paper or in stand-alone spreadsheets.
And while the overarching purpose of these core systems is to establish consistency, standardization and centralization of control, they are often too rigid and unwieldy by nature to support microprocesses, dispersed operations, quickly changing conditions, or the many other complex and unique situations that today’s manufacturers face. In the following ways, once virtuous traditional systems are showing their flaws.
Despite their challenges and pitfalls, large-scale systems will continue to play a significant – albeit changing – role in modern manufacturing, particularly due to the massive amounts of invaluable data they produce and store. The key for companies will be to find ways to put this data to good use.
Now is the time to take a hard look at the traditional notion of the core manufacturing tech stack. It’s not about abandoning core solutions, but rather leveraging an emerging class of intelligent, additive solutions that are able to fill gaps and extend digitization to the edges of the operation where manual, paper-based work instructions, operating procedures, quality assurance and control documentation, and final production records are still common.
In its “Exponential Technologies in Manufacturing” report(3), Deloitte calls it “the transformational edge,” and for good reason – it’s where the greatest transformation can take place in terms of productivity, efficiency, innovation and talent.
According to the report, Deloitte substantiates the idea that incremental, relatively small investments are delivering much greater returns, stating that “…focusing a larger portion of energy and resources at the transformational edge may help manufacturers capture innovation opportunities, grow faster, be more agile, and unlock novel forms of value for long-term prosperity.”
In fact, the report cites findings from Harvard Business Review suggesting that when it comes to innovation portfolios, a 70% investment made in core areas only stands to return about 10% in 3-5 years, while a 10% investment made in transformational areas can return upwards of 70%.
This concept of “small automation,” or the fast implementation of smart, flexible and adaptable technologies – such as machine learning, predictive analytics, natural language processing, digital production records, etc. – to fill gaps in current tech ecosystems, can improve the productivity of individual processes by 80-100% and overall function by 20% or more(2). The ability to economically solve problems at the team or even task level, according to the Strategy+Business article, marks a significant change in business technology.
Ultimately, a focus on smaller, faster and smarter approaches to replace paper-based and hybrid processes results in faster time to value, minimizes the disruption to operations and perhaps most importantly, eases the behavioral and cognitive barriers that make people resistant to change(4).
LNS Research(5) agrees. An ongoing study of the industrial software market and yearly discussions with hundreds of industry practitioners has revealed a common and simple theme when it comes to jumpstarting digital transformation: “find a starting point.”
The good news for the many companies that have a mature tech ecosystem in place is that the investment is not for naught. As the Strategy+Business article explains, small automation cannot replace big automation – nor can small automation function optimally in its absence. Instead, small automation relies on new technologies to build on the foundation of data and standardized processes that large-scale IT initiatives have established over many years.
Many companies feel that since they have implemented powerful enterprise systems, they are a digital operation – they’ve achieved digital transformation. Yet the vast majority of today’s manufacturers still use paper or stand-alone systems to fill digital gaps in their existing tech ecosystems. And as long as that remains the case, companies will continue to miss opportunities and fall further behind the competition.
So, when is enough software enough? The answer is clear: when there is no longer a need for paper in manufacturing.
1. Gartner Says Global IT Spending to Grow 3.7% in 2020. Gartner. 2019.
2. The New Automation Is Smart, Fast, and Small. Strategy+Business. 2018.
4. The War on Paper: A Corrective Action Plan for Going Paperless. MasterControl. 2019.
Beth Pedersen is a content marketing specialist for MasterControl, a leading provider of cloud-based quality and compliance software for the life sciences and other regulated industries. Beth has over a decade of experience in the enterprise software space, writing technical and marketing documentation for companies such as Microsoft, Novell, NetIQ, SUSE and Attachmate. Her areas of expertise include quality management, manufacturing operations, batch record management, Lean Six Sigma, and digital transformation. Beth has a bachelor’s degree in life sciences communication from the University of Wisconsin-Madison and a master’s degree in digital design and communication from the IT University of Copenhagen.