Knowledge generation: Creating more and better insights
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The Center for Strategic Services
The Center for Strategic Services is a specialized division of TNS that provides a suite of customized marketing, consulting and analytical services aimed at helping our clients improve the quality of their tactical and strategic marketing decision-making. Using conceptual and analytical innovation, the CSS provokes thinking and triggers strategic conversations within client decision-making units, helping them leverage and advance along the Knowledge Value Chain, moving from data to insights to knowledge to understanding.
Gaurav Bhalla, Ph.D.
Executive Vice President, Center for Strategic Services and Corporate Strategy
cheap hotel in EdinburghWith over 25 years of experience in management consulting, marketing strategy consulting, brand management, sales management and corporate strategy, Gaurav Bhalla has worked with a diverse set of clients in the healthcare/pharmaceutical, technology, CPG, financial services and telecommunications sectors in Asia, Europe and the USA. He has provided consultation for some of the largest brands and has also held line positions with P&L responsibilities. In addition to his many research papers published in leading marketing, marketing research and statistics journals, he has served as an adjunct professor at Duke University's Fuqua School of Business.
Almost everyday the Marketing Research profession is exhorted to provide more and better insights by those that use MR results as input to their decision-making calculus. However, mere exhortation is like advising a track athlete who aspires to win the 100 meter gold medal at the forthcoming Athens Olympics to run as fast as she/he can. A company interested in generating better and more insights would be better advised to focus instead on the dynamics of knowledge generation. The Knowledge Value Chain (KVC), adapted from the Information Systems field, is a useful framework for understanding this dynamic.
The Knowledge Value Chain
The KVC is characterized by five elements.- Data
- Information
- Insight
- Understanding
- Knowledge
- Data needs to be ordered and analyzed to generate information.
- Information when subjected to a variety of external contexts, such as customer/consumer demographics, industry/category characteristics provides insight.
- Insight validated by the insights of others, other than oneself or outside of one's company, produces personal understanding.
- Knowledge accrues over time as one's understanding is supported or refuted by either personal experiences or in some cases the experience of others whom we trust and who are relevant and credible.
Experiment with different inputs and processes
The utility and contribution of MR to challenge existing management beliefs and facilitate ongoing strategic conversations within companies can be enhanced by experimenting with different inputs and processes within each progression of the value chain identified above.
A few illustrations follow:
- Transforming data to information: Selecting and using the most relevant and appropriate statistical tools to draw meaning from the data; also experimenting with alternate conceptual frameworks, such as utility maximization or optimization vs. satisficing (good enough), or accommodation (deliberately settling for something not the best).
- Moving from information to insight: Seeking context-dependent explanations; such as evaluating results in the context of Ethnicity, Commitment, Hedonism and other consumer values for more concrete and specific explanations. Another example could be exploring the decision-making behavior of individuals in corporations by themselves or as part of groups.
- Turning insight to understanding: Marrying primary survey data (whys) with data contained in marketing databases; coping with marketplace variety and complexity by building variety and complexity within MR and Marketing departments (different types of people with different backgrounds who would see, interpret, and think differently about identical data).
- Evolving understanding to knowledge: Re-examining discarded information – for example, not just studying repeat buying, but also repeat buying and switching; revising existing labels and expectations – for example, do satisfied customers always generate more value for a company; updating beliefs – for example, optimum attribute bundles will always result in greater preference.
Go beyond the conventional tool kit
As corporations demand more and better insights, understanding and knowledge, the MR function will need to go beyond its conventional toolkit of data collection and analysis.
In the short-term, greater opportunities for demonstrating the value of MR to the corporation lie in focusing on the last three stages of the KVC. This focus can be achieved only if appropriate investments are made in:- Hiring different skills in the MR function;
- Integrating the MR function in the day-to-day decision making dynamics of the corporation; and
- Moving the function away from a project (task) orientation to an information program (decision making inputs) orientation with knowledge generation as the key goal.
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