How to build a stronger data culture in manufacturing

We’ve all heard the statistic: more than 80% of digital transformation efforts fail. Surprisingly, a lack of data is not the main driver of failed transformation efforts. Few organizations find themselves short on data, and new data is coming into systems with every passing minute. The missing link for many manufacturing organizations is a strong data culture.

Having a strong data culture means that the majority of your employees are data literate. Your organization, as a whole, should truly embrace data and the value it brings. Even if an organization is collecting and analyzing data, there may not be an organizational culture that supports using and deploying data within the decision-making process. 

In order for your digital transformation to be successful, your manufacturing organization should have a strong data culture in place before bringing in 4.0 technology. But how can you improve your existing data culture, especially if data doesn’t currently play a strong role across all teams?

Here are five meaningful ways you can improve the data culture at your manufacturing organization.

Emphasize your end goal

Remember that the ultimate goal is using data to make better decisions more often. Focus on the business objectives you’re trying to achieve, identify the gaps, and then bring in the necessary tools to fill those gaps and get you where you need to be. 

Truly democratize data (and information!)

In today’s manufacturing world, it isn’t enough to just collect and store data. Data lakes or data warehouses are not usable to everyone at your company; they do not grant equal access, which continues to put data users into silos: technical or non-technical. 

Using data management technology that facilitates democratization (both of data and of use cases) allows manufacturers to harness the collective knowledge and expertise of all their personnel, instead of narrowing it to only technical teams. The right tools equip process experts across the organization with access to both usable data and the means to use that data, all without writing code.

Here at Braincube, we believe those tools are Digital Twins (for creating clean, usable data), an IIoT Platform (to distribute data equally to all users), and self-service applications (to make using data something everyone can do). 

Identify and address gaps

Start by looking at where decisions are made within your organization. What barriers can be removed for these teams?

For example, most IIoT Platforms can simplify the data cleansing and centralization work for data scientists. This frees them up to have more time to put towards building models or using ML to make discoveries. 

Similarly, self-service analytics tools reduce data barriers required to perform advanced analyses. Removing these barriers makes these capabilities more readily available to other team members at your organization, amplifying the chances that valuable discoveries are made. 

Look at cultural rifts

Understand that not all gaps are technological or related to data architecture. Some of them are cultural.

Maybe teams don’t feel comfortable taking risks or failing. Certain projects may even pit teams against each other instead of encouraging collaboration. 

There may be cultural divides between teams, too. For example, many manufacturing companies see divisions between IT (Information Technology) and OT (Operational Technology) teams.

Most IT solutions require broad implementation strategies to work well on a global scale. OT teams, on the other hand, are usually focused on finding custom, localized solutions that are specific to their own facility. 

While these differences in problem-solving approaches are not surprising, they can make it hard for IT and OT teams to work together at times. Bridging these gaps in working cultures and styles can go a long way towards encouraging a data-driven culture enterprise-wide. 

Leaders: embody the data-led vision

There’s also a chance that, as a leadership team, your company’s mantra and mission don’t embrace a data-decision-making mentality across all departments, teams, and employees. 

This can be a huge shift for many organizations. As a leader, it’s your responsibility to lead the conversation and engage key stakeholders in the vision for a data-led company.

Keep communication channels open. Accept and respond to feedback, even if it is hard to hear at times. Employees need reassurance that they are being heard and understood by leadership. 

If possible, give executive teams the opportunity to learn more about the types of tools and technology being used by your most advanced technical teams. This exposure and knowledge-gathering can help C-Suite leaders better understand their investment and how these tools work. It also helps executive tams understand the long-term value that these tools will bring (as the short-term value can be a bit unpredictable while teams ramp up pilots and learn how to best adapt the technology to specific challenges). 

Conclusion

As data-driven cultural shifts are woven into the fabric of your company, technological investments will start paying off, too. Employees will start feeling truly empowered to utilize the tools they’re given. Executives’ actions—including giving teams resources and responding to feedback—will bolster their support of data-led projects. 

For those companies that are less digitally mature, there are other quick (but long-term) data strategies you can incorporate before beginning your digital transformation journey.

On the whole, building a stronger data culture can excite teams to participate, grow, and collaborate.