Why manufacturers struggle to have good, clean data

It is rare to find a manufacturing company that has good and clean data. Why does the sector have this challenge?

Johannesburg, 03 Apr 2019
Read time 4min 40sec
Lance Zikalala, MD, nCoded.
Lance Zikalala, MD, nCoded.

Data is king. There is no doubt a lot of value and currency that can be drawn from cleverly using data. But the concept is older and has always played a role in human society. Whether it was a handwritten ledger or a PowerPoint report, such data contained actionable knowledge that helped decision-makers.

But, something has changed our relationship with data. There's much more of it and that offers deeper nuance. Whereas past models for analytics and statistics were designed to overcome a shortage of information, today the world overflows with big data. Add very affordable modern computing and we can generate much deeper insight at real-time speeds. Even annual reports and employee evaluations are being outmoded by current intelligence.

"The popular saying is that you don't know what you don't know. But that's the proposition of the modern data world... a business has much better access to information," explains Lance Zikalala, MD of nCoded. As a developer and provider of advanced production scheduling (APS) systems, his job is to help manufacturers establish this new level of intelligence that feeds into their planning. But it's a sector that appears to struggle with the new data proposition.

Stuck in the past

The problem is a cultural one. Manufacturing holds a persistent attitude of deploying systems for the sake of having a system. Manufacturers treat these as box-checking exercises: if the system conforms to best practice, that's seen as enough. A belief is created that the systems will simply deliver the results its owners need.

"Systems are often introduced to companies that aren't mature enough to understand their purpose," Zikalala explains. "They don't see the need for human intervention, because they think it's a simple input/output transaction. To put it simply, they think dropping the box and turning it on is enough. They don't realise that to get value out of such systems they have to have ongoing involvement and adjustment around the processes it offers."

In other words, manufacturers often chase technology for the wrong reasons. They fail to appreciate the relationship between technology and business operations.

"That is how they often treat systems: 'As soon as this system has gone live, all our questions will be answered. All our problems will be resolved.' This is entirely the wrong way to manage today's systems."

As a result of this, manufacturers completely miss the significance of roles such as data administrators or data checkers. Yet these represent the very skills needed to create good, clean and actionable data.

Good, clean data

Modern systems are revolutionary only if they have data to work with, yet data is notoriously subjective. It must be handled and formatted with business outcomes in mind. Many companies neglect this relationship, spend heavily on transformational technologies, and then are disappointed by the results. But they caused the problem by not taking data administration seriously.

Good data can only be attained when it is validated and verified by data administrators. This indicates the margin of error, the need to automate data capturing, the understanding of the data capturing staff and the limitations with the system itself. If the data is not validated and cleaned, there is a risk that the business will make decisions using incorrect or bad data.

Zikalala explains: "Picture a scenario where you give your sales staff extra hours because reports indicate that you have an order book of R18 million, yet someone forgot to capture a comma. The order book is actually R1.8 million. The R1.8 million actually means you are behind. You should have been sitting at R2.5 million. In fact, your sales staff were supposed to work additional time. This is a classic example of what could go wrong when decisions are made using bad data."

Many businesses have this situation. Why are manufacturers singled out? A large reason is that the push for better business performance has been driven by customer demands. Manufacturers could leave that pressure with the businesses they supply goods to. So there was little prodding to change.

Today, though, the competitive edge offered by modern systems cannot be ignored. Manufacturers are now required to look into their entire supply chains, which include themselves as manufacturers, their suppliers, their customers, their distributors and their competition. South African manufacturers, which are predominantly SMEs, are particularly sensitive to this change. But they lack the financial muscle to invest in larger systems and assume they can't afford it.

"The lack of maturity in this area creates a vacuum within the manufacturing systems. Many organisations think Level 1 and Level 2 systems are only available to large corporates with large and modern machines."

But this is not true. The digital miracle of scale and affordability is also in the manufacturing sector. Overcoming this barrier is more about culture, about understanding the interactions between manufacturers and their technology systems. If manufacturers hope to get closer to their value chains and modernise their systems, they must look at the data issue. Once they do, the opportunities will be much more obvious for every size business.

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