Unpopular culture: the top 5 things blocking data culture in enterprise manufacturing

Why can’t an industry overflowing with data embrace being ‘data-driven’? We explore how to overcome what’s standing in their way...

What’s stopping manufacturers from embracing the era of smart manufacturing and becoming fully data-driven enterprises? Amidst digital transformation and industry 4.0, tThey have data – and lots of it. Research found that the average factory generates one terabyte of production data every day, and that’s without factoring in customer and supply chain data. Yet only 1% of that data is analysed and acted upon in real-time, and – as we shared in our latest guide – only 39% of manufacturers had managed to scale widespread data-driven use cases in 2021.

So, what’s getting in their way? Why can’t an industry overflowing with data, and willing to invest in the technology it needs to process it, fully embrace information to become ‘data-driven’?

The answer is data culture – or more accurately, the absence of one.

‘Culture’ isn’t something you can own or buy: it’s a mindset. Data culture is no different, and successfully creating one in your organisation takes time, communication and vision. Technology like MDM or PIM might be an important part of embracing data and getting the best out of the information available to you, but simply buying a data platform will never be enough to develop cultural data change.

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In our guide, Culture clash: Creating a data culture in enterprise manufacturing, we show you how you can develop a strong data culture, and the benefits it can bring to your business. But first, let’s look at some of the biggest obstacles that are blocking data culture in manufacturing – and what you can do to overcome them.

Lack of buy-in at the top

In popular culture, change is a wave that reaches some people sooner than others. You have your innovators and early adopters at the start, then your early majority, late majority and laggards (those people who really, really don’t like change).

If your C-suite aren’t in the first wave, actively driving change and seeking ways to innovate with data, then they should at least be in the second: those early adopters who can quickly see the benefits of data and are ready to share that vision with everyone else.

If your senior team don’t embrace data, no one else will take it seriously. Your data innovators – be it your CDO, CTO or someone else – will struggle to instigate a data culture without this crucial top-level buy in. This is your biggest obstacle to creating a data culture, and the first one you need to overcome.

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Lack of buy-in everywhere else

Between early adopters and the early majority, you have something that cultural academics have dubbed ‘the chasm’. For something to really take off and become part of the mainstream, it needs to cross the chasm: if it doesn’t, it remains a niche interest, not a cultural phenomenon.

The exact same thing can happen with your data culture in manufacturing. The chasm can create a divide, where data change is enthusiastically embraced by the few, but doesn’t cross over to the many: leaving those innovators and early adopters struggling to influence and instigate change without widespread acceptance and appetite for it.

Citing success stories from other companies who have integrated Industry 4.0 practices can serve as persuasive evidence for the sceptics. It's imperative to convey that adopting a data-driven strategy is not merely following a trend but a strategic decision to remain competitive in a rapidly evolving sector. Such an approach necessitates the leadership to not only recognise the significance of data but also to exemplify its integration in the organisation's strategic processes.

Getting over that gap is all about communication and persistence. If there’s resistance, don’t fight it or force it: keep communicating, keep telling your data story and keep selling-in the benefits of data.

Data siloes

There are two types of data siloes: accidental and intentional. Accidental siloes tend to be data that’s been stored by an individual or department, without realising the importance of central data sources (or because a central data source didn’t previously exist). Usually, data quality and data governance initiatives should weed these out and stop them from happening again. The presence of siloes can significantly hamper the potential of advanced technologies like the Internet of Things (IoT) and Artificial Intelligence (AI), which are central to modern manufacturing.

Intentional data siloes are a bit more difficult to manage, as they come from people wanting to control their data and keep it in the formats and platforms that they are used to. Data ownership and accountability is one thing, but keeping it separate is another, and it’s a serious block to cultural data evolution, halting progress and adding complications. Overcoming this type of silo takes, again, strong communication and top-down influence.

Either way, siloes are not conducive to a strong data culture. It means that there is valuable information that isn’t available to the business as a whole. It skews insights and damages the efficacy of data technology.

No ownership or accountability

At the other end of the spectrum, there can be the perception that data is ‘not my problem’: it’s a data issue, a tech issue, a leadership issue. If you want to create a strong data culture, data has to be everyone’s problem, with every single person who handles data taking responsibility for its reliability, accuracy, timeliness, and availability.

The key to overcoming this obstacle is showing what good data quality should look like and explaining what can happen at a business and individual level if it isn’t maintained. As with some of the other points above, it’s about creating understanding and appreciation.

Looking beyond data platforms

Digital transformation of Industry 4.0 requires a holistic approach. Especially one that encompasses AI, IoT, and real-time analytics to fully leverage the terabytes of production data generated daily. Embracing these technological advancements is essential for a true cultural shift towards data-driven manufacturing.

incorporating concepts like digital twins and augmented reality into manufacturing processes shows how technological advancements can transform data culture. This holistic approach to data, combining MDM and PIM with cutting-edge technologies, is critical for manufacturers seeking to thrive in an increasingly complex and data-driven industry.

Colleagues set in their ways

Has your organisation’s attitude to data kept pace with your data reality? In enterprise manufacturing, resistance to change can be common, particularly when it comes to data. Some departments or individuals may have strong ideas of how things should be done, or have been done before, which can make it difficult every time you try to introduce new data practices.

Rather than force change on data naysayers, reframe it. Find out what they are afraid of: the likelihood is that they have legitimate concerns that need to be taken into account. Small changes to data-linked manufacturing processes can have big consequences if they go wrong. If you want to convince people that it’s a change worth making, sell in the benefits that they will see if it goes right.

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Simply having and using data isn't sufficient. A robust data culture, embracing modern data ecosystems and technological advancements, is vital for any competitive manufacturing landscape. Download our guide below to find out how to do it: from identifying pain points (like those listed above) to reaping the benefits, or get in touch with our data experts today.

Download our guide to creating a data culture in enterprise manufacturing

What's in the guide?

  • An interview with René Meijers, Senior MDM Consultant at Stibo Systems, discussing how manufacturers can assess and improve their data culture
  • Our top tips for establishing a data culture
  • How a data culture can benefit your business in the long- and short-term
  • How to spark real change at all levels in your organisation
Download guide