Technology

Getting Value From Big Data: Engineering a Team for Success

Evidence-based teams are more efficient and enjoy their work more because they share a common set of values.
By Michael Matošin
March 22, 2019
Topics
Technology

Before embarking on an organizational redesign, there is a crucial question that must be considered. What does success mean to the organization? The answer may be any number of things—a hiring target, a set of strategic objectives or an end-of-year financial figure. No matter the specific answer, it should precise and quantifiable. The more specific the definition of success and the easier it is to put a number to this definition, the more clearly an organization can identify how close it is to success.

For an organizational redesign to succeed, leadership must have an appetite for disruption—discomfort must be expected as changes take place. Similarly, communication throughout the entire process is key, so that all employees may be prepared. It is best practice to define key performance indicators (KPIs) early on. These KPIs will act as way markers that guide the redesign to completion.

Taking a more granular approach, it must be recognized that individuals have differing personalities and personal values. Some people value collaboration and teamwork, others thrive on competition and achievement. People out in the world tend to get along better with others that have values that are similar to their own. This is no different at work.

Teams are more efficient and enjoy their work much more when they share a common set of values—these highly synergistic groups are called "evidence-based teams." When existing and potential employees are moved to teams that are evidence-based, workplace productivity and employees’ quality of life increases.

To generate evidence-based teams, more data is always preferred to less. To extract the kind of data necessary for engineering teams, it must be measured directly. One must be strategic in how and what one measures; too much and it may become tedious and counterproductive, too little and insufficient data will be captured. It’s important to strike a balance; measure the criteria that is important as much as possible while being considerate of employees’ time.

At a minimum, it would be great to have the personal values of every individual in the organization. This means eliciting the values of all potential employees and having all current employees sit down and complete an assessment. Measuring values over time (once a year, or once every two years) is even better. This allows companies to track, monitor and respond to changes as they inevitably occur over time. There are a wide range of tests, both proprietary and free, that can help extract this information from employees.

Even more preferred is having data on employee performance that can be cross-referenced with values data. This can be used to define an aptitude metric for what roles best suit individuals with certain values. In time, it can be used for future employee planning by aligning values and competencies. In this way, management knows which employee thrive in which role in advance.

There are times when an excellent candidate must be hired on the spot. There are also times when a candidate is demonstrably not the right fit for the position. These cases are both the rarest and easiest. Evidence-based teams are a useful tool for the messier middle ground.

Suppose two candidates with equivalent skills, education and experience are being evaluated for a single position and only one may be hired. If an organization has profiled its internal values, it can ask the candidates to complete a values assessment to see which candidate’s values align more closely with both the entire organization and the project team that the candidate would be assigned to. All things being equal, the candidate with values more closely aligned with the organization is the better hire.

Now for a more ambitious example. Diversity in the workplace is beneficial for many reasons, both as a social good and as an in-house productivity booster. However, organizations often struggle to sufficiently diversify their workforce.

Imagine that an organization wanted to overhaul its HR processes to increase internal diversity. To do so, it might implement an entirely blind recruitment process; the application procedure would not elicit candidate’s names, gender or address, just education and relevant experience. This is a good start, but one can go further.

By asking candidates to complete a values assessment, their results can be used alongside their anonymously adapted resume to predict organizational fit. Since research shows that personal values are not related to income, ethnicity, gender or sexual orientation, this “blind” approach will be likely to increase diversity. An organization will be reviewing what actually matters about the candidate, without the whole host of social norms that typically surround them.

In essence, an evidence-based team offers another dimension with which to evaluate candidates. Importantly, this new dimension is quantifiable rather than a subjective assessment of the candidates in question.

Evidence-based teams can be used at all stages of the recruitment and team management process. At the hiring stage, diversity can be maximized by leveraging candidates’ values. For existing employees, rapid response teams can be generated on the fly to meet shifting obligations based on precisely what the task at hand needs. By bringing teams together that will gel, productivity is boosted and work is more rewarding. It’s a win-win for everyone involved.

by Michael Matošin

Michael Matošin is a machine learning, data science and computational mathematical specialist at Enstoa. Michael leverages the most up-to-data models and methods to inform key business decisions and drive organizational value. A significant focus of his work is developing predictive models and analytics in order optimize systems and processes to deliver dynamic, best-in-class solutions.


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