Most organizations have learned how to share data tactically. They’ve put technical infrastructure and processes in place so that they can easily transfer data when necessary to comply with regulations, execute transactions, or provide a service. But far fewer companies have begun to explore the opportunities created by a more strategic approach to data sharing.
In today’s digital economy, business leaders need a data-sharing strategy to pursue novel digital solutions — and move in new business directions. Strategic data-sharing practices allow an organization to share data quickly and with control for specific opportunities with specific partners, and to share it repeatedly, with an emphasis on value creation. As strategic data-sharing practices mature over time, purposeful, fast, and creative data sharing becomes the basis for business model innovation and the resulting payoffs.
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Energy management and industrial automation company Schneider Electric is a case in point. It uses its internet of things platform to share data with its business customers in order to discover and deliver energy management solutions.1 In 2016, company leaders saw IoT as a significant opportunity to develop new products and services based on the monitoring and analysis of connected assets. Along with the data-sharing platform, they developed a tool to collect both structured and unstructured data about the company’s products in use at a customer site, drawing on sensor data and maintenance logs. Using a dynamic risk monitoring algorithm, the tool detects operating risks and their sources, and it allows facility managers who purchase the product to manage the performance of assets themselves or use a Schneider Electric service center.
1. J.W. Ross, C.M. Beath, and K. Moloney, “Schneider Electric: Connectivity Inspires a Digital Transformation,” working paper 417, MIT Center for Information Systems Research, Cambridge, Massachusetts, May 2017.
2. R.W. Gregory, O. Henfridsson, E. Kaganer, et al., “The Role of Artificial Intelligence and Data Network Effects for Creating User Value,” Academy of Management Review 46, no. 3 (July 2021): 534-551; and R.W. Gregory, O. Henfridsson, E. Kaganer, et al., “Data Network Effects: Key Conditions, Shared Data, and the Data Value Duality,” Academy of Management Review 47, no. 1 (January 2022): 189-192.
3. “Sustainable Hospitality,” Schneider Electric, accessed Dec. 19, 2022, www.se.com.
4. J. Rodriguez, G. Piccoli, and B.H. Wixom, “Increase Data Liquidity by Building Digital Data Assets,” research briefing XXI-11, MIT Center for Information Systems Research, Cambridge, Massachusetts, November 2021.
5. B.H. Wixom, “PepsiCo Unlocks Granular Growth Using a Data-Driven Understanding of Shoppers,” working paper 439, MIT Center for Information Systems Research, Cambridge, Massachusetts, December 2019.
6. B.H. Wixom, G. Piccoli, I.M. Sebastian, et al., “Anthem’s Digital Data Sandbox,” working paper 451, MIT Center for Information Systems Research, Cambridge, Massachusetts, October 2021.
7. F. Lucini, “The Real Deal About Synthetic Data,” MIT Sloan Management Review 63, no. 2 (winter 2022): 11-13.
8. “Anthem Digital Data Sandbox Public Dictionary: Version 2.0,” PDF file (Chicago: Matter, n.d.), https://matter.health.
9. Wixom, “PepsiCo Unlocks Granular Growth.”
10. “PepsiCo and Walmart Claim Top Spots in Kantar PoweRanking,” Kantar, accessed Dec. 7, 2022, https://cdne.kantar.com.
11. For more information, see P. Weill and S.L. Woerner, “Dashboarding Pays Off,” research briefing XXII-1, MIT Sloan Center for Information Systems Research, Cambridge, Massachusetts, January 2022.
12. B.H. Wixom, G. Piccoli, and J. Rodriguez, “Fast-Track Data Monetization With Strategic Data Assets,” MIT Sloan Management Review, July 29, 2021, https://sloanreview.mit.edu.
13. Wixom et al., “Fast-Track Data Monetization.”