In a fast-moving world, organizations can sustain a competitive edge by developing actionable knowledge from streams of unstructured data. Front-line employees are among the first to observe emerging problems on the horizon, because they’re positioned at the point of contact between an organization and its customers and thus uniquely aware of the early symptoms of impending change.1 To paraphrase Stanford professor Robert Burgelman and Andy Grove, the late CEO of Intel, front-line employees can feel the winds of change because they spend time outdoors where the stormy clouds of disruption rage.2
Front-line employees, then, can offer a true treasure trove of insights to be used in strategic decision-making. Yet, top management teams rarely ask these employees about impending strategic issues they anticipate at the organizational front lines, or for their opinions on how a new product might fare. Many executives therefore deprive themselves of new information that could improve their analyses — and they risk making decisions in isolation within the C-suite echo chamber.
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The Front-Line Paradox
The situation described above is something I refer to as the front-line paradox: Front-line employees are often the first to sense impending change but the last to be heard within an organization. Consequently, many organizations are unaware of the knowledge they already have access to. And each day, organizations are missing out on opportunities or experiencing unnecessary crises because of this paradox.
This paradox is best illustrated by the reality television show Undercover Boss. In each episode, an executive goes undercover as a front-line employee in their own organization. Typically, the executive discovers important problems and is amazed by how much they didn’t know about their own company.
But these undercover bosses aren’t alone in their ignorance of front-line insights. A simple thought experiment can illustrate just how much insight is lost at the front lines every day. Consider a call center with 500 employees, each of whom gets an average of 160 incoming calls per week (640 calls per month), with the average call lasting 380 seconds. This would mean that all 500 employees receive 320,000 customer calls per month, or approximately 33,778 hours of conversation! Typically, decision makers don’t tap into this rich repository of knowledge, which goes to waste on a daily basis.
The remedy is to listen to the front line. Based on my own research, which is informed by recent advances in the field and at pioneering companies, I present a model for using the collective wisdom of front-line employees — the surprisingly accurate forecasts and estimates they can provide — to help executives detect the early symptoms of impending change.3
A New Model for Strategic Decisions
The front-line paradox model distinguishes between the source of knowledge — from either the top management team or front-line employees — and between two different analytical approaches: descriptive and diagnostic, or predictive and prescriptive.4 Together these make up a matrix consisting of four types of analytics that influence strategic decision-making.
Quadrant 2 represents the new approach for strategic decisions, whereas quadrants 1, 3, and 4 represent conventional ways of making strategic decisions and using front-line input. Quadrant 2 suggests that front-line employees should be collectively used as crystal balls and consultants; my own research and that of my colleagues have shown that front-line employees are able to make accurate predictions about an organization’s performance.5 Hence, there is a largely overlooked potential in deploying the front line in this way.
In contrast, many less-successful organizations rely on executives being “oracles” (quadrant 1) using front-line key performance indicators and satisfaction surveys only as input (quadrant 4), which the top management team subsequently analyze and interpret themselves (quadrant 3). This either keeps the organization focused on backward-looking, historical data or leaves it at risk of making forward-looking decisions based on simple and incomplete information. Leveraging the collective wisdom of the front line can remedy both of these shortcomings.
A number of companies have started to realize the potential of the collective wisdom of front-line employees and are turning to them for forecasts or input on important predictive or prescriptive decisions.
Internal betting markets, now soaring in popularity, are one example of such input used for predictive purposes. For instance, Best Buy asks front-line employees to forecast how retail sales will be affected by certain events, such as the number of gift certificates that will be purchased close to Father’s Day. Their collective forecasts, it turns out, are often more accurate than official forecasts.6 Twitch (a part of Amazon) has taken this logic a step further by helping its employees to become better forecasters by offering training to help them get more comfortable with numerical thinking.7
Other organizations have focused on collective prescriptions from the front line. For instance, the Spanish clothing company Zara uses input from its front-line employees to decide which clothes to produce; store managers around the world order only the merchandise they believe will sell in their location in the short term.8 Technology company Rite-Solutions, ahead of its time, built an internal market where employees propose new ideas and solutions, which subsequently become “stocks” that can be traded in an internal electronic betting market that mirrors the stock market.9 The Rite-Solutions initiative aligns with co-founder Jim Lavoie’s fundamental belief that “no one is as smart as everyone.”10
Lessons for Executives
What all of these pioneering companies share is the adoption of innovative business practices to leverage the collective wisdom of the front line and, as a result, gain a competitive edge. Of course, doing so is not as easy as it sounds: It requires substantial changes to the culture, processes, and mindset of an organization.
Front-line employees need to reflect on their day-to-day interactions and hone their ability to separate the signals from the noise when making predictions and prescriptions. For top management teams, the transformation is often more pronounced, requiring a substantial change in mindset: Just as it’s dangerous to drive a car forward by looking in the rearview mirror, it’s similarly dangerous to make forward-looking decisions by looking backward into historical data. Executives need to let those who are in the best position to see what’s ahead take the driver’s seat.
Leveraging the collective wisdom of your front line requires both mining and minding data. Excelling at both requires the right tools for data collection and analysis, and the right training. Employees need training in the science and art of forecasting; executives need training in intellectual humility to recognize their own limitations, and data training to understand and use the collected insights.11
Ultimately, the front line can provide input for decisions, but executives need to consider trade-offs and consequences and maintain full accountability for the decisions made. It’s been said that the front line is the bottom line.12 Yet, as the front-line paradox reminds us, few organizations live up to this adage. The new management model presented here offers a first step in addressing this challenge. Now go out to your front line and start listening.
1. C.L. Pedersen, “Using the Collective Wisdom of Frontline Employees in Strategic Issue Management” (Ph.D. thesis, Copenhagen Business School, 2016).
2. R.A. Burgelman and A.S. Grove, “Strategic Dissonance,” California Management Review 38, no. 2 (January 1996): 8-28.
3. J. Surowiecki, “The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies, and Nations” (New York: Anchor Books, 2004).
4. The typology of descriptive, diagnostic, predictive, and prescriptive approaches originates from data science, where it is very popular, as illustrated in publications by IBM such as “Descriptive, Predictive, Prescriptive: Transforming Asset and Facilities Management With Analytics,” PDF file (Somers, New York: IBM, 2013).
5. For relevant studies on using the front line to make performance forecasts, see Pedersen, “Using the Collective Wisdom”; C.A. Hallin, T.J. Andersen, and S. Tveterås, “Harnessing the Frontline Employee Sensing of Capabilities for Decision Support,” Decision Support Systems 97 (May 2017): 104-112; and T.J. Andersen and C.A. Hallin, “Global Strategic Responsiveness: Exploiting Frontline Information in the Adaptive Multinational Enterprise” (New York: Routledge, 2017).
6. D.N. Thompson, “Oracles: How Prediction Markets Turn Employees Into Visionaries” (Boston: Harvard Business Review Press, 2012).
7. D. Hernandez, “How Our Company Learned to Make Better Predictions About Everything,” Harvard Business Review, May 15, 2017, https://hbr.org.
8. E. Brynjolfsson and A. McAfee, “The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies” (New York: W.W. Norton, 2014).
9. J. Lavoie, “The Innovation Engine at Rite-Solutions: Lessons From the CEO,” The Journal of Prediction Markets 3, no. 1 (2009): 1-11.
11. D. Whitcomb, H. Battaly, J. Baehr, et al., “Intellectual Humility: Owning Our Limitations,” Philosophy and Phenomenological Research 94, no. 3 (May 2017): 509-539.
12. See, for example, B. Benjamin and E. Sopadjieva, “Engage Your Front Line to Increase Your Bottom Line,” Forbes, Oct. 9, 2017, www.forbes.com.