Implementing enterprise data management in industrial and scientific organizations

Description

As industrial companies go through their digital transformations, they’re finding that their biggest challenges are not purely technical; rather, they’re related to the historical cultural (and organizational) divides that separate parts of their value chain and the different ways in which each part of the organization has managed its data. In industrial companies, it’s common to find that the IT Department was only responsible for a small part of the company’s data: the finance system, HR system, procurement and supply chain. All of the operational data and planning data for each facility or factory—including the industrial automation and control systems that generate sensor data—are unknown to the central IT Department and managed in the facilities under the line of business. And each facility may manage their data differently. (Certain industries like upstream oil and gas, mining, and pharmaceuticals often also have a third distinct category of data, technical and scientific data, that is managed by another group again.)

To achieve the expected business value from digital transformation, these companies need to integrate data from all these data islands, instill a new enterprise-wide culture around data (including its management, its value to the company, and its potential uses), and create a new organizational structure that recognizes the different data competencies across the organization and brings this knowledge together in the most effective way—while still retaining data stewardship in the line of business.

Sun Maria Lehmann and Jane McConnell describe the situation that industrial companies find themselves in, detail how they have approached this challenge with the creation of an Enterprise Data Management Group, and share organizational patterns that can be used to establish a forward-looking data management organization that learns from past expertise while supporting this cultural change around data.