How data can improve managers
Leadership has long been considered a “soft” intuitive skill, while management was considered a “hard” science. But those lines are blurring, and the days of purely intuitive decisions are over. Many leaders are already adopting a hybrid “informed intuition” approach, in which intuitive decisions are based on data. Netflix, for example, combines sophisticated viewer analytics with years of experience exploring new products.
Such uses of computational social science (using processing and data science tools to analyze information about people and relationships) are now essential for business. From marketing and supply chains to strategic decision-making and compliance, this source of innovation helps improve profits, streamline operations and optimize decision-making.
Computational Leadership Science (CLS) is the next evolution, designed to fundamentally improve leadership using simulations, network analysis, AI, and other computational approaches. It sits at the intersection of pioneering science and technology, well-established leadership research and invaluable insights from practice.
This article examines the role of CLS in your organization, how to use it to create business value, and the ways IBM uses it today.
CLS and leadership
CLS enables companies to better anticipate, manage, mitigate and even take advantage of the tidal waves of disruption that their organization will experience in the months and years to come. Here are three examples where CLS provides both short-term and long-term value.
Morale and commitment:
A recent survey of 1,500 CEOs revealed that morale was their biggest challenge. Fortunately, there are CLS resources to co-create solutions with your collaborators. You can use open-ended survey questions infused with “natural language processing” to better understand 1) the top topics associated with morale in your organization and 2) how your employees think you approach them. Then you can use “collective intelligence” technologies to innovate with solutions that boost morale. This form of group decision-making increases engagement and increases your value as a leader.
Monitoring and motivation of employees:
Another concern is remote work and productivity tracking. Here, the increase in CLS intelligence reduces hasty decisions such as setting up excessive employee monitoring systems. You will learn that surveillance technology is a slippery slope that should only be used with extreme caution. A healthy alternative to CLS is to turn virtual environments into fruitful spaces to engage your employees. For example, I’m co-creating an AI-driven system that 1) visually maps who knows what and who works with whom in organizations and 2) quickly assigns the right people to the right job. The former provides a clear picture of existing relationships and how to lead seamless community development, while the latter assigns tasks that are better aligned with employee skills, which has been shown to increase motivation. This helps you reduce employee dissatisfaction while increasing trust, engagement, and other results indicative of great leadership.
Diversity, Equity and Inclusion (DEI):
Many organizations struggle with DEI in hiring, retention, and promotion. Some people are more successful than others at landing top positions – there is a bias against introverts even though they can add more value – and leaders frequently select people they want over people they don’t. need, unconsciously selecting individuals like them based on factors such as race, education, and socio-economic background. Worse still, the majority of employers use “totally meaningless” tools such as the Myer-Briggs type indicator or biased algorithms for processes such as recruitment.
CLS allows you to highlight and remove these biases with industry-leading solutions. My team, for example, combines “conjoint analysis” (a method to reduce deception on reviews) with “reinforcement learning” (an AI approach to optimizing decisions over time) to do better match the real, and not just declared, qualities of a candidate with the organizational qualities. needs, not just wants. The result is a clear, honest and constantly improving selection system based on DEI and performance.
Supervision of CLS teams
CLS should be part of your daily leadership practice. In addition to the six daily leadership questions identified by my colleague, Eric McNulty, you should constantly ask yourself, “How can CLS inform this decision and how can I engage my CLS team?” There is too much data, computing power and analytical talent for a paradigm shift not to occur and for you not to ask these questions. From personal relationship management to strategic decision-making, CLS will have a huge impact on the way you lead.
The team you build, comprised of academics and leadership consultants, as well as data and IT specialists, facilitates the benefits of CLS. They are at the heart of your transformation, so first you need to find a CLS advisor who can help you build and engage your team. This advisor is a specialist in the decompartmentalization of expertise and the management of CLS resources. Think of the advisor as a golf caddy who knows the course and the club you need to use for each shot. For example, part of my work at Harvard’s National Preparedness Leadership Initiative and as a co-founder of HSC Analytics involves understanding how leaders can use AI-informed tools to 1) reduce bias in place of work and 2) increase the pace and power of collective problems. to resolve. Then, as a CLS team, we navigate the course and co-create value.
Advisors also help with issues of explainability and confidentiality. The problems arise when leaders, driven by the speed, efficiency, and hype of AI, make decisions “because the computer says so.” This AI-center approach creates a murky environment filled with cautionary tales. As a result, considerable effort is being devoted to Explainable AI to identify and reduce issues. This gives you x-ray vision to protect against indiscriminate, potentially catastrophic decisions, while retaining the value of the information provided by CLS.
Confidentiality is also a must. There is a significant push towards privacy-protecting technologies, and those of you who use this technology will play an important role in creating a more secure society. This is a great opportunity for you to further establish yourself as a reliable and effective CLS leader.
The key to realizing these game-changing benefits is embracing digital leadership transformation. John Hagel III, author of The journey beyond fear, notes decades of deep interactions with leaders that fear prevents decision-makers from realizing their full potential. Instead, courageous leaders overcome their insecurities about emerging technologies, unfamiliar jargon in the boardroom, or changes in their leadership style. They adopt an opportunity mindset by understanding how CLS improves their performance. That doesn’t mean you have to code in Python, but you should at least dip your toe in the digital water.
CLS at IBM
While systemically integrating CLS with all leadership challenges is a nascent vision, IBM is already connecting the dots in IT. IBM, like many other organizations, understands the importance of identifying employee potential and then creating pathways for development and promotion. Unfortunately, like many other organizations, IBM struggles to find ways to create the best match between high potential and future opportunities. Many uncertainties and significant costs exist in this process. It is very difficult to predict whether an excellent software engineer, for example, will make an excellent chief of engineers, and getting it wrong can hurt everyone in the network – from the person who has been promoted to his subordinates to those in charge of the selection.
Noticing this opportunity to innovate, IBM embarked on a major digital transformation of its overall assessment process. As Sofia Lamuraglia, director of leadership development at IBM, has said, “Recruiting from within is often more cost-effective than bringing in people from outside the organization, as the training and onboarding processes are usually much shorter. In addition to evaluating leaders for immediately available roles, we also wanted to build a strong talent pipeline: to provide our HR community with a go-to resource for future management-level opportunities. »
IBM Leadership Development has combined key psychometric and behavioral measures of effective leadership with their penchant for computational thinking. The result is a digitized platform for global leadership assessment, as well as automated training and micro-learning services tailored to a leadership candidate’s skills, behavior and personality. Early results from IBM suggest the platform is predictive of leadership performance and, better still, costs significantly less than traditional face-to-face assessments.
However, leader assessment and development is only the tip of the CLS iceberg for IBM. At the forefront of the application, they explore when quantum computing will elevate a leader’s decision-making capabilities far beyond traditional computing – the so-called “quantum advantage”. Although still in its infancy, use cases are beginning to emerge for quantum changes in leadership and complex decision-making. IBM, in partnership with JPMorgan Chase, for example, is experimenting with quantum computing to give financial executives an edge in extremely complex areas, such as investment strategies and risk analysis. It is estimated that JPMorgan Chase’s leadership as an early quantum adopter could generate billions for its customers and shareholders before the competition can follow suit.