You can't drive a car looking in the rearview mirror, and you shouldn't drive an organization solely on backward-looking metrics. The coronavirus, the black swan of 2020, has made this exceedingly clear. As organizations navigate uncertainty, the technology-led use of our collective intelligence provides the opportunity to predict and respond to unclear issues with speed and accuracy.
In a matter of months, the coronavirus forced the world to its knees, blindsided the global economy, and pushed even the most sophisticated healthcare systems to the verge of collapse. Beyond the chilling health numbers, the economic collapse has been swift and severe.
Against this backdrop, organizations are navigating unchartered territory and dealing with a situation as unexpected as the pandemic requires adopting new solutions to address new problems. In many ways, COVID-19 has been an unanticipated catalyst for technology adoption across the world (consider Zoom, the teleconferencing company, surging to a market value of $59bn).
In an uncertain, remote, and above all digital reality, the wisdom of employees – the collective intelligence – presents itself as a core resource for organizations looking to respond fast to uncertainty and new circumstances. The intuition of employees can be a powerful tool in predicting how markets will adapt.
Harnessing knowledge and intuition from employees with technology can help leaders understand their organization and future better. A wealth of evidence points to the value of this, often untapped, collective intelligence. An array of studies depicts how aggregating employee knowledge (especially from the frontline) can lead to accurate insights about the future of business before such information even begins to flow up the hierarchy (Hallin et al., 2017). It can help companies act proactively and in lead-time.
Complex questions cannot be answered reliably by one or a few people. For example, firm performance depends on the complex interplay of many factors. Knowledge about these factors is spread throughout the organization. We can think of the prediction problem as a picture puzzle where different people hold different pieces.
Some examples make the above points more tangible. Hewlett-Packard found that revenue predictions from employees outperform official forecasts 75% of the time (Chen & Plott, 2020). Similar findings were made in case studies from both Ford and Henkel. Ford achieved a 25% lower error in sales predictions and Henkel a 22% increase in accuracy of sales predictions by using employee predictions (Cowgill & Zitzewitz, 2015).
Second, collective intelligence does not only relate to quantitative and 'hard' metrics in an organization. Today, several companies use employees to generate collectively qualitative insights, that is, new ideas and solutions to existing or future problems. For example, Deutsche Telekom made 11,000 ideas leading to projected cost savings of €116m from employee-generated insights. The author of "The Art of Creative Thinking," Rod Judkins, recognizes that the best ideas are seldom among the first thrown on the table or from the "creative department" in the organization.
Coupled with the recent advances in natural language processing and machine learning technology, we are better equipped to handle large amounts of 'soft' data and turn it into actionable insights. Google, AT&T, Lego, General Electric, and many more have all experimented with collective intelligence and using employee wisdom, and for excellent reasons… Let's think a little about why collective intelligence is such a powerful resource.
It is said that the average employee makes 35.000 subconscious decisions a day and interacts with multiple stakeholders. These experiences lead to a wealth of sensing, intuition, and tacit (hidden) knowledge about the world, the business, the customer. Further, these employees are often the first to pick up unfiltered and early signals from the market. Yet, the research identifies that organizations are notoriously bad at using this level of emotional intelligence. It is estimated that a company only really has access to 10% of organizational knowledge and mainly explicit knowledge. Tacit (hidden) knowledge is a dormant resource that often never leaves the heads of employees and influences key decisions.
In line with the above, it is no secret that employees increasingly want to be heard. Business leaders face a workforce asking for, and prioritizing, more inclusions and influence. For each passing day, knowledge workers account for a more significant share of the workforce, and they, along with other employees, expect to be heard. 80% of millennials say that inclusion is essential when choosing an employer (Deloitte, 2019) 56% say that they have suggestions for improving company practices (Tjan, 2012). Still, a whole 34% do not feel heard!
There is much to be gained for companies that put the distributed intelligence to work and begin to listen more to employees. Mindpooling, the knowledge of employees, customers, or other stakeholders operating at the periphery of an organization, enables access to altogether new data-points that can diagnose the future of the firm. For boardrooms, CxOs, managers, and team-leaders, being equipped with the collective insight of employees grant the opportunity to respond quickly to disruptions like COVID19. The ideas enable organizations to mitigate adverse impacts and discover opportunities arising from the crisis more quickly. As work becomes remote and increasingly digital, pooling employees' minds appear the solution to several organizational challenges.
Importantly, business disruptions have become the norm. This means that organizations cannot lead to looking in the rearview mirror. We need more insights into the now and tomorrow rather than yesterday. With it, we can minimize threats and leverage opportunities. In light of the pandemic, the traditional notion of work has been challenged. A new normal is emerging. Organizations need to be fluid, agile, and above all, proactive. In this environment, speed is vital. At Mindpool, we are on a mission to facilitate a future of combined human intelligence and computers for smarter decision-making.
 Said by Robert Kaplan and David Norton in their work on the Balanced Scorecard.