Digitizing Subject Matter Expertise Part 1: Why Data Isn’t Enough

Note: This is the first blog of a three-part series that examines subject matter expertise as part of digital transformation. Digitizing this subject matter expertise is critical for companies that want to implement prescriptive, agile operational processes, such as maintenance. The term for doing so is called digital knowledge. Digital knowledge is the discipline of encoding human subject matter expertise and data from across silos, digitizing these insights, and then driving them into relevant decision flows. Analytics  are key tools for digital knowledge, though many companies are on the front end of using them this way.

Digital transformation has become a strategic roadmap for many businesses. Nowhere is this more evident than within Fortune 500 companies operating in complex, global industrial markets. These include oil & gas, shipping, and manufacturing.

For these large organizations, transformation isn’t just about technology; it’s about evolving beyond 20th century business practices and leveraging disruptive innovation to survive and thrive in data-driven economies. Profitability, safety, customer satisfaction, operational efficiency, environmental stewardship, and more depend upon companies’ ability to digitally transform their businesses, and do so faster than their competitors.

Data Is Everywhere, But Isn’t Enough

There is no lack of data to draw upon for digital transformation. Large industrial companies have a long history of collecting data, whether through systems or manually. Now, technology has broken down many barriers that have stranded data in siloes. A wealth of historic performance data can be more readily accessed. Interconnected equipment, devices, systems, and organizations are generating, collecting and sharing volumes of real-time data.

However, many industrial companies continue to struggle to apply their data to digital transformation. The volume, complexity, and speed of the data often overwhelm them. Value is delayed, limited, or, in some cases, never realized. Often, pilot projects with data resemble more traditional rip-and-replace application upgrades, where progress is painstaking and benefits take years to surface.

These struggles are due, in part, to organizational assumptions that some combination of data, data lakes, algorithms, and analytics engines are solutions in and of themselves. In ARC Advisory Group’s view, that is rarely the case, particularly for Fortune 500 industrial companies that must deal with the largest data sets imaginable. Data and the supporting technology are needed components for digital transformation, but aren’t enough.

Knowledge Is Key, But Remains Hidden

A mission-critical competency—subject matter expertise— is often missing from the digital transformation equation. Human expertise drives the value within the data and ensures benefits are achieved in a timely manner and realized continually. It does so by determining what the data means and how, where, when, and why insights should be applied. Ultimately, human expertise optimizes the value of transformation and ensures accuracy and speed of its execution.

By providing the necessary context, expertise enables companies to apply insight specifically to achieve ideal outcomes: process efficiency, profitability, performance, safety, etc. However, this human expertise is often hidden from the organization; tightly locked up in cultures of tribal knowledge or stranded, as is the case with most unstructured data.