The Employee Engagement Algorithm

Management

One of the biggest headaches of any organization is, without a doubt, the necessity to equip itself with the best professionals in the market. This means, as well as finding the right talent, also retaining the most outstanding and the potentially most sought after employees by our competitors.

It is only in the US where the estimated cost of replacing a worker is said to exceed 20% of the salary of that person – and in some cases, up to 100% – while in countries like Germany, three in every ten employers estimate the economic impact of a bad hire at over 50,000 euros. Therefore, the preoccupation of companies to keep their ‘crown jewels’ is now up to 28% greater than it was only six years ago.

Conscious of the problem, some of the global providers of software for HR services, such as ADP, Cangrade, Ceridian, ClearFit, Cornerstone, Jobscience, Knack, Lumesse, Mercers, Silkroad, SumTotal and Workday, have recently developed solutions that combine two of the most popular socio-technological concepts: Big Data and Employee Engagement.

In essence, their aim is to help the companies concerned with talent to answer questions of this sort: What potential candidates possess the values ​​of the organization? What attributes do our best teams share? Who are the real leaders and internal influencers? What levers make our workmates feel happier and comforted at work?

The science of big data, or rather, Smart Data, is about identifying behavioral patterns, and correlations, and developing predictive models from groups of preexisting data, in order to better address issues such as turnover, productivity, diversity and the commitment of our staff. It aims to basically expand the business intelligence analytics of companies, where the only tricks that have been available till date are a rigid scheme of competition, and a set of perks that motivates only the least creative employees.

It is not a trivial issue: connection with internal partners, as we always say at Territorio creativo, is more than just an engine for creativity, innovation and business. It is the reason behind who we are, which inspires us to seek a more inclusive work culture, and to always surround ourselves with the best people.

What advantages does Smart Data bring to our organizational culture?

The main advantage of Big Data is that, in addition to the historical view that it offers to conventional analytics – in which only 6% of HR departments are considered ‘excellent’ – it provides us with predictive intelligence and allows us to optimize costs in all areas.

  1. Detecting trends in the labor market: What kinds of profiles are those organizations similar to ours demanding? What differentiates a ‘millennial’ candidate from a professional of the previous generation? Why did nearly half of the employers interviewed by CareerBuilder in 2013 plan on hiring people without previous experience in their sector, in order to train them directly?
  2. Defining competencies: Who offers the best performance in our company and what makes them stand out? What are their educational backgrounds, ages, and professional experience? Data associated with performance indicators can help us to identify what aspects we must look out for when seeking other employees, and to predict how the potential candidates meeting these characteristics will perform.
  3. Identification of key behaviors: We talk about personal skills that, regardless of prior training or career experience, make some of our partners better able to resolve conflicts, to push their ideas forward or inspire their teams. Enterprises such as the Instituto de Ingeniería del Conocimiento (IIC) (i.e. the Institute of Knowledge Engineering) – which included, among other agents, the Autonomous University of Madrid – have developed solutions that enable the evaluation of the degree of collaboration, cohesion and internal socialization (Article in Spanish) of the staff. Undoubtedly, this is where much of the engagement, and the fit i.e. positions best suited to the people within the culture of an organization, is determined.
  4. Solving organizational inefficiencies: How much time is effectively dedicated to innovative and collaborative tasks that increase the satisfaction of our staff? How can teams determine which meetings require a more active presence than others? What activities are best suited to each person? How can we graphically represent the internal indicators to encourage transparency and identify areas for improvement, as proposed by the company SmartDrive?
  5. Development of incentives: What do our employees expect? What is it that, if faced with a seemingly stronger offer from another company, makes them follow us? Is it money, responsibility, autonomy, or social benefits? This will be crucial for knowing what kind of incentives or rewards should be set in place, and how much money it would cost us to implement them. According to the consultancy, Towers Watson, 33% of companies already carry out internal surveys on their employees, in order to calculate, for example, their capacity to retain them. Or, as Google did, to measure how much talent is capable of withstanding a free program of massages and gourmet meals.

65% of the HR professionals interviewed by SilkRoad recognize that the lack of integration between their daily activities and automated company systems generates a critical loss of competitive intelligence. Solving this problem requires not only technology, but above all, the will and determination to execute a transformation plan in this area.

There are three basic tips that, to that end, should be taken into consideration across the entire company:

  1. Start with the problem that you want solved, before accumulating information: The important thing is to understand what we want to solve, and what factors inherent in our organization encourage or discourage, for example, the retention of talent. Otherwise, we run the risk of getting lost amidst massive amounts of data.
  2. Clean, tidy up and clarify information: 80% of the work in a good Big Data project requires discarding duplicates, useless, or irrelevant data. Which of them actually tells us if our turnover rate is higher or lower?
  3. Surround yourself with good analysts: They do not necessarily have to be scientists or computer specialists. What is valuable is having statistical domain, and thus, enough of a sociological and cultural background to read and properly interpret the data.

Putting ‘data sciences’ at the service of Employee Engagement does not solely consist of gathering raw data. In fact, it is, in many cases, about collecting information that we will never use. Mainly, the key aspect in all of this lies in understanding what lies beyond this data, or how to combine it with the qualitative knowledge that we are provided with on a daily basis in the organization. It is, above all, for knowing what questions we need to ask in order to receive the best answers. The first of these, which will mobilize much of our engagement, asks who we are and why we do what we do.

And right there, without a doubt, is where people always have the last word.

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