Article: Four Tips for pursuing digital transformation in manufacturing

Four Tips For Pursuing Digital Transformation In Manufacturing

Forbes Business Council publishes article by Actify CEO Dave Opsahl

CEO at Actify, Inc., helping manufacturers to build some of the world’s most complex and advanced products.


Digital technology has changed and will continue to alter the landscape of business, engineering and manufacturing. But the shifting needs for designing, producing and servicing products are complicating efforts to improve processes and business results, thus making a digital transformation strategy difficult to manage.

Executive leadership, especially within engineering and information technology domains, is constantly bombarded with messages highlighting the need to understand concepts like “digital twin” and “digital thread.” How can a manufacturer increase the chances that its digital transformation strategy will have the desired impact on the performance of the enterprise?

As the CEO of a company that provides visualization software to manufacturers, I have a few suggestions:

Ensure your chosen solutions understand product data.

Discrete manufacturer data is unique among the types of data exchanged between enterprises. All enterprises must deal with documents and transactional data, but these representations are well understood and supported. Because your information assets include 3D models and 2D drawings with information hidden within those files, ensure the solutions you choose know how to interpret that data and provide it within the context of the role of a specific user. While a given solution might not be the system of record for certain data, it must have the ability to reference the data in that system.

Consider ‘unbundling’ technology applications.

In Consumption Economics, authors J. B. Wood, Thomas Lah and Todd Hewlin made the case that the vast majority of IT solutions contain large amounts of features that, though paid for, are either irrelevant to the needs of the customer or are too difficult to use productively. As they have for decades, many companies today continue to adopt a strategy of monolithic solutions or platforms that put a value on how they solve integration challenges by offering something to address a particular role or workflow.

But sometimes, these packages aren’t the most effective at solving a specific problem. With improvements in data integration being driven by digital thread initiatives, I believe now is an excellent time to consider best-of-breed choices and employ purpose-built solutions for various functional roles. However, because my company specializes in purpose-built solutions, I know that it’s also important to note that pursuing a best-of-breed strategy isn’t without risks.

These risks can be minimized if you know they exist. One advantage platforms offer is a bit of a bargain with the devil. In exchange for saving you from the cost of doing the integration between applications, their rigidity and scope can set you up to become “captive” to that vendor, which is not a particularly resilient situation. A good approach is to constrain the scope of integrating best-of-breed applications in two ways:

  • First, limit the scope of the data to be integrated. Avoid the temptation of believing that all data available has to be exchanged between applications. In practice, the required touch points are not all that many.
  • Second, focus your organization’s data exchange or integration efforts around industry standards. Avoid crafting a dependency on any one vendor’s way of defining a proper data model.

Prioritize centralizing visibility.

It has been said that 90% of all data that exists has been created in the past two years. Manufacturing is no different, and the challenges this brings can be monumental. Knowing what data matters, making it available when it is needed without having to search for it and providing it at the right time is critical.

With few exceptions, the data needed to support a workflow will live in multiple systems of record. Solutions exist that establish “systems of reference,” where the needed information is presented in real time and provide clear, unambiguous visibility to executives, program managers and operational roles throughout the enterprise. (Full disclosure: My company provides these types of solutions.)

With the technology that’s available today, such as web services, accessing information that lives either in an on-premises application or a cloud service has become easier than ever. Yet, many companies still employ practices and processes that rely on manual efforts to pull data from multiple dissimilar applications. Or, what I’ve observed is even more common in moderate-sized organizations, data used for purposes of visibility is presented in the form of spreadsheets or slide decks. The amount of effort required to gather and present that data is often a full-time job. Worse yet, the data is frequently out of date or just plain wrong.

Today, with web technologies, it is straightforward to establish dashboards that visually present any necessary information to support a process. The data might live in another application, but it is presented in the necessary context.

This is also a companion strategy to unbundling. Large software solution vendors are almost always driven to expand the user base of their applications to increase revenue from each customer. By using a “system of reference” approach, you can provide visibility through a consistent user experience, even when the point applications from which data is being pulled are swapped out.

Don’t confuse activity for progress.

One of the biggest challenges manufacturers face is having the necessary visibility of the impact their digital transformation strategies are having on the business. Too often, what is measured is activity, not progress. Much like good marketers focus on the customer journey and look for tent poles of inefficiency, operational leaders in manufacturing need to do the same. Effective management of a digital transformation strategy relies on choosing the right metrics and being consistent in taking measurements and assessing progress against goals. That takes time and a clear understanding of the objectives of the enterprise.

Digital transformation isn’t impossible and doesn’t have to be intimidating. Just be smart about your choices, and don’t be fooled into taking on more than you need.

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