Designing and Developing Analytics-Based Data Products

An increasing number of companies are creating products that combine data with analytical capabilities. Creating an effective development process for these data products requires following well-established steps — and adding a few new ones, too.

Reading Time: 18 min 


Permissions and PDF

Thanks to several waves of innovation in recent decades, the rise of information and technology is one of the dominant features of the current economy. The expansion of the information economy that began in the mid-1990s included enhanced hardware and software capabilities, abundant broadband Internet access, and increasingly widespread use of the Internet. These developments helped spur the creation of new products and industries and drove a significant increase in data resources. In an important 1996 article published in this journal, “The Design and Development of Information Products,” authors Marc H. Meyer and Michael H. Zack previewed the impact of these changes.1 (See “Revisiting ‘The Design and Development of Information Products.’”)

The past 20 years have brought several reconfigurations of the information and knowledge economy, as enhancements in computer processing and storage capabilities, new software and communication technologies, and the evolution of wireless broadband and mobile computing have taken hold. Technological breakthroughs have driven exponential growth in e-commerce and the emergence of a digital economy with vast data assets. The changes have been accompanied by ongoing attempts to make sense of all the data through the use of analytics.



1. M.H. Meyer and M.H. Zack, “The Design and Development of Information Products,” Sloan Management Review 37, no. 3 (spring 1996): 43-59.

2. P. Rotella, “Is Data the New Oil?,” April 2, 2012,

3. Organisation for Economic Co-operation and Development, “Data-Driven Innovation: Big Data For Growth and Well-Being” (Paris: OECD Publishing, 2015).

4. J. Howard, M. Zwemer, and M. Loukides, “Designing Great Data Products” (Sebastopol, California: O’Reilly, 2012).

5. T.H. Davenport, “Analytics 3.0,” Harvard Business Review 91, no. 12 (December 2013): 64-72.

6. Organisation for Economic Co-operation and Development, “The App Economy,” OECD Digital Economy Papers, no. 230 (Paris: OECD Publishing, 2013).

7. The three types of analytics are described in detail in T.H. Davenport and J.G. Harris, “Competing On Analytics: The New Science of Winning” (Boston: Harvard Business Review Press, 2007).

8. J. Bunge, “Big Data Comes to the Farm, Sowing Mistrust,” Wall Street Journal, February 25, 2014.

9. A. Hagiu, “Strategic Decisions For Multisided Platforms,” MIT Sloan Management Review 55, no. 2 (winter 2014): 71-80.

10. Meyer and Zack, “Design and Development of Information Products.”

11. Ibid.

12. One CEO creating a data product in the health care industry told us, “We tried agile [referring to agile product development methods], but it was too slow.”

13. E. Ries, “The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses” (New York: Crown Business, 2011).

14. D. Barton and D. Court, “Making Advanced Analytics Work For You,” Harvard Business Review 90, no. 10 (October 2012): 78-83.

15. Bain & Company, “Using Data As a Hidden Asset,” August 16, 2010,

16. E. Dwoskin, “Startup Factual Knows Your Commute, and Much More …,” Wall Street Journal, Dec. 10, 2015.

17. Meyer and Zack, “Design and Development of Information Products,” 46.

18. D. Kiron, P.K. Prentice, and R.B. Ferguson, “The Analytics Mandate,” May 12, 2014,

19. A. McAfee and E. Brynjolfsson, “Big Data: The Management Revolution,” Harvard Business Review 90, no. 10 (October 2012): 60-68.

20. B. Zeidler,“6 Ways to Extract Customer Insights From Social Conversations,” February 2015,; and T. Rajpathak and A. Narsingpurkar, “Managing Knowledge From Big Data Analytics in Product Development,” white paper, Tata Consultancy Services, Mumbai, India, 2013,

21. B.H. Wixom, “Cashing In On Your Data,” research briefing, MIT Sloan Center for Information Systems Research, Aug. 21, 2014,

Reprint #:


More Like This

Add a comment

You must to post a comment.

First time here? Sign up for a free account: Comment on articles and get access to many more articles.