Algorithms developed by Talent Alpha, a Polish company that operates around the world, make it possible to engage specialists in projects that match their skills and expand a workforce in a flexible manner. It is a model that can be the source of cutting‑edge innovation in the HR field as well as a driving force for change across the entire labor market.
Until now, organizations looking for adequate IT specialists for their projects, both within companies and from the labor market, have had to spend an enormous amount of time checking employee competencies. Because of this, firms have often been unable to hire the right people at the right time, leaving themselves with unfilled vacancies and unfinished projects. The tech talent gap is now a real problem for companies. It is also confirmed by statistical data. According to Everest Group’s analysis, 86% of organizations consider this gap an obstacle to developing or maintaining their businesses. The fact that more than 40% of HR leaders are unaware of their employees’ skills, and consequently, are incapable of responding effectively to the needs of employers, does not instill optimism either.
However, this problem can be solved by algorithms using AI and machine learning, which analyze the competencies and individual characteristics of candidates for various positions and select job offers that best match their profiles. It enables employers to recruit specialists who can perform specific tasks in the most effective manner. It also prevents employees from being frustrated by projects that are too challenging or too easy to complete and avoids a situation where they may believe that their full potential is not being realized.
A solution that utilizes such algorithms is offered by a Polish company – Talent Alpha which operates around the world. Their platform‑based solution is a touchpoint between employers from different organizations and their employees. What differentiates it from other methods of engaging specialists is that it automates and significantly accelerates the process of finding offers and increases the accuracy of matches.
Talent Alpha founders, 2018: (from left) Szymon Niemczura, Przemek Berendt, Mike Kennedy
The platform operates on a software‑as‑a-service (SaaS) model. It connects hundreds of organizations for which IT competencies are critical. Talent Alpha offers the underlying architecture of its proprietary Human Cloud, which provides on‑demand information about employees and enables employers to find a business associate instantly.
Our company facilitates the free movement of specialists between small and medium‑sized enterprises (SMEs), operating in CEE countries in the IT sector, with international corporations. We solve the problem of employers related to the acquisition of experts with proven competencies while simultaneously supporting the development of SMEs that can share their specialists with large companies. Currently, Talent Alpha operates in a B2B model, so individual freelancers do not have the opportunity to present their competencies via our platform. Maybe it will change in the future.
We also ensure the identification and measurement of a specialist’s capabilities, data‑driven planning, and the use of modern talent management tools, including the flexibility to ramp up or ramp down resources depending on circumstances.
What is the difference between the talent from Mexico and Europe?
Talent Alpha’s platform is constructed in a way that foregrounds the competencies of employees rather than, for example, their origin or gender.
This democratization, which has been built into the system, is a reaction to the trends observed on the labor market that concern the growth of freelancing and the gig economy. The future of work is based on projects, and the shift from headcount to skill count means engaging professionals for tasks according to their strengths. Employees’ hard and soft skills, as well as motivational factors, are much more important than where a candidate comes from. If someone asked me: “what is the difference between the talent from Mexico and Europe?”, I would answer: “the time zone”. Another person, say from the United States, who has corporate experience, would perhaps say: “there are communication barriers when it comes to employees from Mexico, and that is why we appreciate the talent from Europe more”. But when we break down these concerns, the feedback we get shows that Mexicans speak excellent English, in addition to being specialists in their fields, so American employees are able to communicate with them without any problem.
Talent Alpha proves that it is possible to find average, good, or excellent specialists from all over the world, and we can measure the level of their competencies with the use of algorithms. Their age, origin, or gender are of no importance.
Source: Talent Alpha
The pandemic of job mismatch
We aim to digitize the labor market but in a manner that is, for instance, different from LinkedIn, which in a way is a digital copy of a résumé and an employment website.
We want to help employees understand themselves and recognize their skills through an online platform. It is enabled by algorithms that identify the skills and personality traits of an individual. In turn, it “knows” which career path would be most suitable for a given candidate. Personally, what really frustrates me is how many people find themselves in jobs that do not match their competencies or character. As a result, these people suffer burnout, become depressed, and at some point, begin to openly admit that they do not enjoy their positions or the people who they cooperate with. This is another global pandemic we are currently facing.
Our species has arrived at a point in history where we are creating quantum computers, building electric cars, and thinking about flying to Mars. Yet, companies still struggle with digitizing the recruitment process. With the available technology, this task is within our grasp, and we would like to utilize it.
At Talent Alpha, we believe that computers can make better decisions, especially when there are various pieces of data to analyze. No recruiter, even the best and most effective, can do this very well and certainly not better than an algorithm. That is why we have prepared a tool which we are giving to HR professionals. Thanks to this tool, recruiters will be able to systematize their knowledge and recruitment processes, impacting employee productivity and job satisfaction.
Source: Talent Alpha
Introducing a new working model to the market
When we first met with our potential customers in 2018, we listed several measurable effects and optimizations that implementing the Talent Alpha platform could bring to their companies. For example, we showed how much recruitment costs would be reduced or how much employee satisfaction would increase in a company. We also presented hard data, for example showing that we can identify and select prime candidates ten times faster than the competition. Thanks to our Talent Genome model, which uses natural language processing algorithms along with AI and ML technologies, we identify and measure over 3,500 unique technical skills, cognitive abilities, personality traits, motivators, and social skills.
During our first presentations, there was no meeting after which a potential client would not be enthusiastic about our idea and would not want to implement it in their own company. However, after meeting us, the client would have to participate in several gatherings within their organization and convince other departments about the merit of implementing such a model. Then, the client would usually step back, and we would receive feedback saying that the company needed more time to settle on introducing such an operation.
This meant that it took longer to implement the concept than we had originally anticipated. After market research, we thought it would only be a matter of a few weeks before we could swing into action. However, such projects were finalized much later than we could have expected, and in fact, we are only now reaping the rewards of those initial discussions and collaborations. Today, we are aware that change does not happen overnight as the talent management model we present is innovative. In the companies that we work with, it is both often unclear who should be cooperating with us and how the implementation process should begin.
Source: Talent Alpha
Personalized cooperation offer
At Talent Alpha, we believe that everyone has the potential to become an expert in a given field, provided they are allowed to utilize their talents − and those talents can be either innate or developed over years of practice in a particular professional discipline. To ensure that everyone can make the most of their potential, we create a digital representation of a person’s unique Talent Genome. To do this, each candidate is asked to complete psychometric tests and an assessment of their technical skills.
Then thanks to the Human Cloud, the employer receives insight into both the hard and soft skills belonging not only to the candidate but also to the entire talent pool of the organization. By indexing a set of employee competencies, companies can match their specialists to a specific project or decide to implement initiatives, either raising or changing the qualifications of the workforce. Data obtained through Talent Analytics can also support an external recruitment process.
For example, one international company looking for data engineers decided to utilize Talent Science and AI/ML systems of our platform to sift through the candidate base and identify potential employees. Using technical skills data and psychometric assessments made by Talent Alpha, we delivered a talent analysis report, classifying candidates in terms of the job description we received from the company. Within just a few hours, we provided the client with the most promising applications, and they could carry out interviews with an already verified list of candidates.
Sooner or later, we will prove it works!
Even before the pandemic emerged, we started talking to a large technology company that wanted to expand its workforce but had trouble recruiting. They were looking for someone externally who could immediately join a project that was already in progress. We introduced our Talent Marketplace, which would allow the company to benefit from professional assistance right away. The company enthusiastically gave the project “the green light”. However, from the moment when the company enthusiastically embraced its realization − through all implementation elements, conducting workshops with employees, to the moment when the first employees, acquired from the Human Cloud appeared − the process took about eight months. The company remains a satisfied customer with whom we continuously develop our cooperation, yet this initial stage was a time‑consuming process.
It is also worth mentioning the story of our product implementation in Novartis, which had an understanding that introducing a new model of talent management is challenging. For this reason, the company decided to create an individual unit to streamline the process. It does not mean, however, that we did not encounter any obstacles. Changes in large corporations tend to be difficult, and although the management team loved our idea, surprisingly, the employees were not so keen on it.
Our first challenge was the HR department which regarded the collection of employee and candidate data to implement Talent Alpha’s solutions as just an additional burden. So, we adopted a “let’s show it works” attitude and carried out the process, minimizing the workload on the client’s side. It included digitizing the process of gathering employee data (along with candidates), informing employees on an individual basis about omitting some factors while assessing their competencies, such as gender, age, or origin. To our delight, we received very positive feedback from employees at this stage, who gladly took the technical and psychometric tests. Within a few days, more than 200 people were successfully “digitized”. Their profiles were then compared to the profile of an ideal candidate, which we compiled together with the management. The decision‑makers quickly knew who to meet and discuss further development paths within the company, which employees they ought not to consider, and which candidates they should hire. As a result, the company was able to acquire the desired talents much faster. By implementing Talent Alpha, Novartis completed a hiring process that usually took several weeks in just a few days, providing an average of 30% more information about each candidate including psychometric data.
At Talent Alpha, we are currently focusing on the IT sector because we understand it better than any other industry. The key to our solution is a deep understanding of the skills that enable a professional to use their competencies successfully. But if our algorithm receives complete information about the types of skills and competence levels for a particular role in a specific industry, we hope that our platform will be available for other sectors.
The new talent management model might change the entire labor market while improving its efficiency, and we believe there is no turning back from that.
