Since leaving my role as Chief Strategy Officer (and prior to that Chief Operating Officer) at BEworks - a boutique management consulting firm focused on applying behavioral science insights and methods to business and policy challenges - I’ve had the opportunity to explore, study, and have deep thoughtful conversations on the intersection between two areas that have fascinated me:

• Human Potential – How do you quantify it? What is our maximum potential and how do we know when we’re operating at it? How do you hire for high potential and what do you pay for it? How do you help people reach their max potential?

• Mental Models – What are good mental models? How do you use them to solve problems? How hard is it to change/replace existing belief systems?

Through my research, it’s clear that some environments seem much further ahead in answering these questions (e.g., major league sports and the army) and other environments have made surprisingly very little progress (e.g., businesses and governments). The most common argument for this gap by the latter group is the complexity of operating under multiple short- and long-term competing objectives with resource constraints (money, people, time) versus the more singular focus (e.g., win a championship, win a war) and seemingly less resource constraints that these other groups have. As someone who understood this argument well given the many hats I had to wear during my time at BEworks, I can both empathize and still say that it is an imperative that businesses do better to be more strategic versus reactive when it comes to thinking about our people and how we make decisions within our organizations. The increase in employee turnover, the rise of the gig economy and fractionalization of work, the popularity of digital apps and trackers that drive better personal performance outcomes (online education, meditation, health) suggest that employees are moving faster than organizations to be better selves and generate a greater return on their skills, knowledge, and abilities.

To start - the quote by Sarah Travel, GM at Benchmark, that “7s kill companies” formed my thinking that the biggest hurdle facing companies and governments from being more optimized like their sports and army counterparts is that we’ve built systems that allow employees that we would rank as 7’s (on a 10-point scale) thrive:

• We say we our people are our assets, but we don’t value or think of them in the same way as other assets. Instead, we value and manage them as an expense, leading to hiring for today (plugging the hole of yesterday’s challenges) versus more strategic hiring outcomes that consider employee lifetime value, team composition, and the optionality/opportunity for the future – all of which is done in the sporting world (e.g., rebuilding teams). Consequently, our organizations can become purgatories for those whose skills, knowledge, abilities were once coveted but have diminished over time as we’ve failed to align their growth and development trajectory with our strategic business objectives.

  Fortunately, economic and financial models such as Utility Analysis (Boudrea J.W., 1988) or Human Capital Development Contribution (Holton, E.F. and Naquin, S.S., 2004) already provide a good starting point for how to think about measuring employee lifetime value and total contribution of workforces.  These models aren’t intended to be exact science but decision aids – helping organizations to describe, predict, explain, improve decisions, and ultimately be more strategic on their people decisions.  On the flip side, I’ve been fascinated with how we can combine these models with other frameworks (brand, company culture, turn over rates, compensation models, etc.) to determine how companies can be more attractive for high potential employees, i.e. the 8’s and above.   

• I have had many conversations with organizations about their hiring process. I’m happy to see there is less convincing required these days for organizations to take a more structured approach to their hiring process to reduce bias – including standard assessments, structured interviews, work samples, panel interviews. Unfortunately, when you look under the hood on the execution of these practices, you ultimately see new challenges and biases being introduced (e.g., un- or ill-defined measures, higher hassle costs for candidates, unfair starting points). This may explain why we don’t seem to be moving the needle much on merit, diversity, and tenure. There are second, third order effects to everything we do – organizations need to take a more systems view of the interventions and processes they implement to understand what problem they are solving for. Alternatively, we just end up where we started – hiring 7’s and missing out on diamonds.

  For example, I worked with a company to implement 3 assessments that measured cognitive ability: numerical-, verbal-, and abstract- reasoning. Ability assessments provide a standardized and structured way to evaluate candidates for general mental ability. The concern however is that practice and familiarity can create an unfair starting line for candidates, and potentially lead to false positives (people who score better as result of practice) and false negatives (people who would have scored better if they had the same level of practice). Although it's important to ask these questions/concerns - I advised that we step back and understand the problem that we’re trying to solve for. First, we don't really care about the score on each individual test - what we want is a holistic view of someone's intelligence. This is also not a competition – we were not selecting for the top scoring candidate. Given this, people who do well (either through practice or not) are less of a concern because practice, and applying a learned strategy (to perform better) is exactly what we want. The real concern then is the false negatives - are we missing out on good candidates because of increased hurdles they face, such as novelty (seeing these tests for the first time) or test anxiety. To reduce this concern, we designed an email that was aimed at reducing "novelty" and test anxiety by providing both tips on strategy on how to excel on these tests and practice questions. The onus was now on the candidate to do as much prep or as little prep as required to get the best outcome - which is no different than a job in which you provide someone the tools to succeed, they absorb, apply, and perform.

•  Lastly, if we start doing the above, we need to help employees (our players) help themselves reach their max potential. We need to rethink training and developing our people, moving away from modes of learning that we know have limited effectiveness such as workshops and online courses to more action oriented and purposeful practice. How many of us “wing” important presentations or scramble when we’re required to make important decisions. It’s time to rethink development of people similar to how the sports world and army does it through better coaching, better training modules that incorporate the best science, and leveraging technology to provide better fidelity and more personalized and accessible feedback to help people overcome slumps and cross plateaus to continue growth.

  “The MVP Machine” written by Ben Lindbergh and Travis Sawchik talks about the transformation of baseball, moving away from moneyball 1.0, which was focused on using data to spot talent that others missed to moneyball 2.0, which has a more noble intention of helping develop the underdeveloped. Ben and Travis write about how players and teams are leveraging technology and science to help train faster and better (e.g., the use of high speed cameras to help pitchers learn new pitches faster or the unconventional use of weighted balls to improve pitching efficiency and reduce injury). These changes shifted how teams saw their player – moving from a fixed mindset of inheriting talent to a growth mindset of developing talent further and faster (taking the best of the best even further). Imagine if we could do the same for certain high impact skills at the organization level – a path that I’m exploring with others across 2 fronts - communication and model based decision-making. 

Covid-19 has shown us that traditional models of doing things can be broken and re-built to be better, faster, and fairer. Shopify’s CEO Tobias Lutke recently said “we’re a team, not a family” and Netflix’s CEO Reed Hastings said “we’re like a pro sports team, not a kids recreational team.” I think this framing / positioning of how we think of people and teams within an organization is an important one to getting all of us to think differently about our people. And this is not because I think employee/employer relationships should be quantified and transactional (as may be perceived in the sports world), but because I think viewing employees like high performance athletes shifts how both employers and employees think of each other. It forces employers to invest in their workforce to achieve and compete at their max potential - investing in better and the right talent (diversity), better managers (coaches), training and development (practice), data and analytics (feedback), perks and privileges (rewarding and retaining talent). It forces employees to think about their skills, knowledge, and abilities as competencies to maximize and help their “team” win. Moreover, with this shift, factors like merit, diversity, equity become a necessary by-product versus a forced end-state.  

These are some of my initial thoughts and areas that I’m looking to explore through a new venture that I’ve started - Human Elevation Lab (“HUELLA”). HUELLA, which serendipitously and appropriately mean mark or footprint in Spanish, defines well what we’re trying to do – leave a mark on how companies build, grow, and develop their workforce. We combine our advanced analytics, design, and human capital expertise to develop cutting-edge tools and processes that help organizations select and elevate their talent for maximum performance. If you are interested in exploring this further or following my journey – please email me at dhushan@huellagroup.com or follow us on linkedIN where I’ll continue to post my thoughts and learnings on helping companies and employees maximize their performance.

Dhushan Thevarajah is the Founder and CEO of the Human Elevation Lab ("HUELLA"). A company that was borne out of Dhushan's own journey to elevate and reach his potential - both physically and mentally. He saw how simple shifts in his mental models and leveraging technology to make the "invisible" visible helped him achieve faster and further.  Combining this experience with his work experience of building and leading teams, designing decision tools to help model and inform choices, and fighting the daily fires across the functions of finance, HR, operations, and strategy of a growing company, Dhushan saw an opportunity to support companies shift their financial and mental frameworks and apply better decision tools for their talent acquisition and growth strategies. In turn, helping workforces reach their maximum potential.

Previously, Dhushan was the Chief Strategy Officer and Chief Operating Officer at BEworks, the world’s first commercial consulting team dedicated to the application of Behavioral Economics to real-world challenges. His blended interest in behavioral science and data analytics brought a more evidence-based and metric-driven approach to these roles. Dhushan also led multiple consulting projects in the banking, insurance, loyalty, and software industry, tackling diverse behavioral problems such as closing the gap between consumer intentions and actions, designing incentives and measures to drive key behaviors, and building training programs to optimize for learning and sustainability. Dhushan holds an M.Sc. from Queen’s University, where he studied and published work on the neural basis of strategic decision-making and holds an MBA from the Rotman School of Management.