• Chris Donovan

How to Leverage Data to Enable Industry 4.0 Manufacturing

The stage is set. Companies that adopt a data-driven approach to doing business are outpacing their competitors. How comfortable are you with your technology strategy?



Overview:

  1. Why is data making so much noise and why should you care?

  2. Barriers to becoming a data-driven manufacturer

  3. 5 steps to enabling a data-driven manufacturing company

  4. Conclusion


Why is data making so much noise and why should you care?

When the pandemic hit in 2020, the whole world came to a standstill. As businesses closed and people were forced to stay home, the only way for companies to survive was by going digital. You saw it all - Zoom meetings, virtual coffee, and more. But something way more important was taking root and coming full circle in a very meaningful way - data science.


Because everyone was suddenly online, for the first time in the world’s history, businesses could see patterns in their customers’ purchasing behavior in a way like never before. Ecommerce opened opportunities for clever data analysts to derive models for demand, buyer intent, and much more.


This information gave manufacturers insane god-like situational awareness. As expected, many manufacturers have since begun turning to a data-driven model that focuses on data as an unbiased common source of truth and basis of decision-making. As data is collected at all points in the value stream and carefully analyzed, insights are drawn to drive change, innovate new products, and fuel sales.


These new tools helped manufacturers navigate the pandemic and are playing a central role in helping the industry realize the benefits of the 4th Industrial Revolution. To this end, every manufacturing executive needs to spend time discussing these basic objectives and must actively seek ways to implement them:

  1. Leveraging data and analytics to maintain a competitive advantage

  2. Managing data from all parts of the value stream as a business asset

  3. Using analytics to implement modern Lean practices

  4. Fostering a top-to-bottom data culture

  5. Becoming a data-driven manufacturer.


Barriers to becoming a data-driven manufacturer

Access to talent and technology are not the main reasons why many manufacturers fail to become data-driven and having a business intelligence solution does not automatically translate into the intelligent use of data.


A 2016 survey revealed that 50% of Americans trust their gut more than evidence when deciding what to believe. A lot of people still favor intuition over facts. Getting rid of this bias is key to eliminating the pushback you might experience when trying to implement a data-driven corporate culture in your business.


According to a NewVantage Partners study, “people, business processes, and culture, ” are the main blockers to becoming “data-driven.” And manufacturing is all about processes. Change is hard, and it's standard human behavior to resist it. You need to come up with creative ways to address this.

Let’s face it, people will always be people. We don’t like change. But change is inevitable. As Gartner stated, “Data can only take an organization so far. The real drivers are the people.”


5 steps to enabling a data-driven manufacturing company


1. Get the leadership team on board

Leadership buy-in is a critical first step to getting the ball rolling. The people at the top need to take the lead. Good ideas succeed when supported by senior management. This is the primary reason why our work at L2 Brands- a decorated apparel manufacturer in Pennsylvania - was so successful.


When Satya Nadella became the CEO of Microsoft, he introduced a data culture at the company. His directive provided the stimulus that made Microsoft the leader in data analytics and business intelligence today.


In his historic blog, Satya said, “The opportunity we have in this new world is to find a way of catalyzing this data exhaust from ubiquitous computing and converting it into fuel for ambient intelligence. This fuel will power improved experiences, understanding, and interactions. When these devices around us gain the capacity to listen to us, respond to us, understand us and act on our behalf, we enter into an entirely new era. The era of ambient intelligence.”


When top management adopts a data-first approach, the people under them find it easy to adapt to the new culture as there is no pushback from the top. Get your leadership to start demanding a data-focused approach to handling meetings, reporting, and day-to-day business decisions.


Becoming a data-driven manufacturer is a transformational process - a journey. And like any journey, you need someone to point the rest of the crew to the True North. This is why leaders are so crucial to the success of this process.


2. Develop a clear data strategy

What are the key “pain points” impacting your efficiency? What are the data “use cases” that will drive specific and substantial value for you? These are key questions that needed to be explored.


Before you spend money or put together a data management team, you need a solid data strategy to guide your data acquisition, management, and utilization.


This is where most companies get it wrong. They buy data analytics products and use them in silos to execute specific tasks. It's not enough, and the results do not warrant the investment. For example, the marketing department may purchase a packaged off-the-shelf solution to manage their work, but their data is not shared with the production team. The production then has to search for information on their own.


There is a whole ecosystem to factor in. If each team in the value stream has a separate tool with independent data that’s not shared, this actually creates more work for everyone and doesn’t translate into any useful value for the business. This leads to the third point.


3. Understand your value stream and identify data use cases

Always keep the end in mind. Your value stream provides you with a complete overview of your operations from idea inception to production, sales, and customer service.


As you continuously review and refine your value stream, you will identify gaps that can be covered using data analytics and business intelligence. This process will yield data use cases that will propel your organization forward and enable you to realize the benefits of your data strategy across the whole organization.


4. Foster cultural transformation

The real drivers of a data culture are the people. Make deliberate moves to get everyone involved. Go beyond providing training and access to tools and data. Encourage your staff to explain their decisions using data.

When you require your teams to design their decision-making process based on analytics as a common source of truth, you are building their capacity to be accountable. This framework guarantees they will utilize data more effectively.


5. Set organizational goals

Changing your corporate culture is not easy. One gigantic undertaking will not deliver the results you seek. An agile approach with well-prioritized milestones will help you achieve more.

At Adaptive, we call this the Lean-Agile Digital Transformation. We designed and perfected this approach and have deployed it to deliver data analytics and business intelligence solutions always with a careful balance between costs and benefits.


Conclusion

It has been five years since the Economist published an article declaring to the world that data has replaced oil as the most valuable resource. The economic changes of the past few years, and the COVID19 pandemic, confirm the truthfulness and significance of this fact.


You cannot put off becoming data-driven. Partial digitization of some of the tasks in your value stream is not enough. As your competitors adopt a data-driven approach to doing business, your ability to remain competitive and continue to delight your customers depends on you effectively leveraging data to derive valuable business insights.