Why Digital Supply Chain Reality Lags Expectations
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Despite the benefits of a digital supply chain, the electronics industry has been slow to embrace end-to-end data sharing and analytics. Integrating disparate IT systems, data quality, partner resistance and the day-to-day tasks of managing a business are among dozens of reasons implementation has lagged. Moreover, digitalization isn’t serving the supply chain as well as expected, experts say.
“It’s true – we are not making enough progress,” said Richard Barnett, CMO of market intelligence platform Supplyframe. “Why is that? Part of it is organizational change; strategy and alignment; executive leadership and balancing long-arc transformation goals with super dynamic business conditions. And you [have] a global pandemic, which puts everything else on hold while you chase parts. You’re not going to be thinking about your intergalactic supply chain future or digital transformation of the future, right?”
The availability of data is no guarantee of better decision-making, Gartner found — 80 percent of the supply chain is not accounted for in current digital decision models. In fact, slightly more bad decisions were made with the use of digital tradeoff analysis than without and marginally increased the percentage of bad decision outcomes, explained Suzie Petrusic, senior director analyst in Gartner’s Supply Chain Practice. A “good” decision meets the decision-maker’s expectations for supply chain and cost performance.
Half the procurement leaders surveyed by supply chain software provider Ivalua think that the rate of digitalization within procurement is too slow, while 47 percent said existing procurement systems are not flexible enough to keep up with constant change and deal with market and economic uncertainty.
Where digitalization fails
It’s not a technology problem, experts agree. Gartner found holes in the supply chain data digital tools capture. “The fault is not just with technology itself, but rather with the incomplete picture of the supply chain that these digital tools capture,” said Petrusic. “Up to 80 percent of the actual, on-the-ground processes that these technology investments are meant to be ‘optimizing’ are not even reflected in current digital models.”
Supplyframe reached a similar conclusion regarding actionable data. Digitalization is largely focused on enterprise data and may miss information relevant to supply chain decision makers. Most – 80 to 90 percent – of investment is generally pointed at enterprise data sets – capturing the history of customer and engineering behavior and standardizing compliance and documentation practices, said Barnett.
“Millions of dollars being spent every year to make the enterprise domain work with third parties,” he said. “But the reality is that every company in terms of the overall performance is heavily influenced by what’s happening in their ecosystem — what’s happening across their customers and suppliers.”
Only 30 percent of respondents to Ivalua’s procurement survey are “very confident” in the quality and accessibility of their supplier data when it comes to supporting effective procurement. This has a major impact on procurement’s ability to work on strategic tasks as it limits organizations’ ability to make quick, informed decisions regarding their suppliers (47 percent); and prevents organizations from tackling rising inflation and spiraling costs (46 percent).
The shortfalls of supply chain data collection and analysis are only magnified when an entire ecosystem shares data. Most digitalization efforts are driven by customers, which means different things depending on where you stand in the supply chain. Electronics distributors, for instance, are considered customers of component makers but suppliers to OEMs and EMS providers. Standardizing or harmonizing data is the first challenge.
Data disharmony
“When you have all types of machines with all types of protocols and all types of processes […] you have to standardize and harmonize all the data,” said Oren Manor, Opcenter core business director for Siemens Digital Industries Software, during a recent EPSNews webinar. “So that’s definitely a challenge that we see with a lot of our customers — that it’s just not all on the same level. When you try to drill down, you find gaps in the data. So that’s definitely a major issue that we see these days.”
Many companies assume the data they collect from partners has been cleaned or harmonized. “But you find out, honestly speaking, 80 percent of time, you’re dealing with data that is not harmonized,” said Glen Tan, senior vice president of Global Operations at EMS provider Flex, on the same webinar.
“I’ll give you an example,” he said. “My name is Glen Tan. Some people might fill it as G. Tan. Some people write Glen T. Three names, one person. You would see a lot of cleaning up on things like this, right? And then you would have people filling in information that is totally incorrect. And that amount of time is what eats up a lot of the effort.”
Given the magnitude of an interconnected supply chain it’s not surprising there’s been spotty implementation across business partners. Company size is one factor, said Dr. Martin Jun, professor of mechanical engineering at Purdue University. “With the large companies, there have been significant efforts,” he said. “But with the small and medium sized manufacturing companies, it has been really slow and they’re far behind right now. So there needs to be some collective effort to support them, because they can’t do by themselves most of the time.”
Experts note that millions of dollars are expended on digitalization efforts and the benefits should match or exceed those investments. Researching the current state of the industry has provided some clues toward making those investments worthwhile.
This article is written by Barb Jorgensen and originally published on https://epsnews.com/2023/11/06/why-digital-supply-chain-reality-lags-expectations/?utm_source=eetimes&utm_medium=latestnews&_gl=1*d80ca1*_ga*MTU0NzI3NTEwMS4xNjk4OTk0NjQ0*_ga_ZLV02RYCZ8*MTY5OTM0MTY2My40LjEuMTY5OTM0MjE2Ni41Mi4wLjA.&_ga=2.256684047.58351510.1699341663-1547275101.1698994644
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