Digital HR services, previously available only to corporations with big data and budgets, are gaining popularity among small and medium-sized businesses (SMEs).
Digitalization of the HR industry in the conditions of a shortage of employees
The state of the HR services market in SMEs can, in fact, be described as an initial stage of development. Despite the fact that the digitalization of HR processes started back in the 2010s, it is only now beginning to become widespread among SMEs.
Absolute Reports estimates that the global market for HR software and services reached $22.4 billion in 2022 (for comparison: the global business software market as a whole amounted to $474.6 billion). In the coming years, according to analysts, the HR-software segment will show an annual growth of 11.47% and by 2028 will reach $43.0 billion. Acumen Research & Consulting gives a more optimistic estimate: $62.5 billion by 2032 with an annual increase of 9.9%.
Estimates of the Russian HR technology market are few, but trends are generally similar to global dynamics. According to TAdviser, the Russian segment of software for personnel management and services for its implementation and support in 2022 amounted to 29.2 billion rubles. At the end of 2023, growth was predicted to 32.1 billion rubles, with a stable dynamics of 10% of annual growth.
Unlike previous years, when the demand for HR solutions was formed mainly by large companies (58% in 2023), in the coming years, analysts call small and medium-sized businesses an important growth driver, which has finally turned to the advantages of automation of personnel management.
The key reason for this interest is the widespread shortage of personnel, which forces companies of any size to be much more attentive to the issues of hiring, retaining and stimulating employees. SMEs that do not have the limitless resources of large businesses are calling for help from HR analytics, predictive HR management, mobile HR applications and other advantages of IT solutions in the field of HR for preserving of personnel and business survival.
HR solutions for SMEs: supply and demand
After the departure of a number of Western vendors, some niches have formed in the Russian market of HR services and systems, for example, solutions similar to SAP SuccessFactors, covering the full life cycle of a company employee.
Today they are gradually being replaced by the latest domestic developments, including those with AI elements. Despite some nuances with licensing, these decisions are perceived positively by Russian customers, including among SME companies, mainly due to a decrease in the affordability threshold.
In general, for the convenience of analyzing the general situation in the Russian market, it is more convenient to divide HR services and solutions for SMEs into two conditional categories.
1. Administration and corporate digital documents processing (CDDP). This category is relevant for any company. First of all, we are talking about personnel CDDP with the ability to sign documents online for remote workers. This also includes solutions that support compliance with labor law rules in their functionality.
Already, the situation with software of this category in Russia is very favorable. There is a huge number of services for the turnover, signing and storage of all types of personnel documents that are required to interact with employees.
All these functions are implemented in numerous offers of CDDP, and SMEs here have a choice in a wide price range – from ready-made complex turn-key HR integrations to point-to-point implementation of individual HR services (for example, electronic signatures) into the IT contour of the company.
2. Personnel management and development. This category includes solutions for automating the chain of processes from hiring an employee to his dismissal, including attracting talent, adapting, setting goals, training, incentives, development, professional well-being and building a talent pool.
Solutions of this class allow you to draw a continuous line through the entire life cycle of an employee. An integrated approach provides a significant economic effect, consisting of reducing costs at all stages of the process, faster closure of positions by suitable people and reducing employee outflows.
It is this class of HR services that begins to use or is already actively using machine learning, neural networks and other options for AI technologies.
Until recently, all this was available mainly to large companies with a staff of 5,000 or more people.
Services as an ecosystem: from corporations to SMEs
The time comes when own HR solution, made for internal corporate needs, reaches a certain level of maturity and completeness. In some cases, after refinement, such HR products enter the market and become available to other companies.
This, in particular, happened with the Pulse cloud HR platform, which was originally created for the needs of Sberbank’s internal ecosystem.
As competition increases and prices decrease, powerful analytical solutions in the field of HR become economically viable for medium-sized businesses with 200-250 employees and even some small businesses with special characteristics.
Small business, where management and personnel officers practice a “family” personnel culture, when there is an opportunity to communicate personally with each employee, is also forced to look closely at IT services for HR. Along with labor shortages, the difficulty of hiring and the motivation to retain employees, small companies are pushed by modern realities in the form of a remote or hybrid work model.
AI in HR services – reality and prospects
Competition between digital HR solutions is a powerful incentive for the introduction of AI functions in existing and new products. Services previously focused on large companies will increasingly take into account the needs of SMEs and the specifics of their work with personnel.
Precedence Research analysts estimated the global AI market in the field of HR at the end of 2023 at $559.85 million with a forecast of growth to $2.1 billion by 2032 and an annual growth rate of 15.77%. Implementing AI in HR is expected to give employees personalized opportunities to improve productivity and reduce costs. AI will help with the processing of data such as job descriptions, results reports and training materials.
AI tools such as chatbots are already helping to increase employee engagement through communication with colleagues, career data collection and benefits. Companies can flexibly adapt their HR policies and create an attractive work environment to motivate employees.
AI-powered robots can conduct interviews when recruiting mass staff. AI solutions are also good at optimizing the system of incentives and rewards, in establishing feedback with employees, monitoring and improving corporate culture.
AI systems can also create targeted surveys, similar to the “360 degree” HR technique, to assess staff. The only difference will be that instead of exhausting, but rare long questionnaires, the employee will undergo unobtrusive “homeopathic” micro-surveys a couple of times a day. Their goal is to find out indirectly the attitude of one employee to another in order to build a scheme of interaction – a kind of “heat map of relations”.
A ready-made HR ecosystem is able to make predictions based on the provided data set, as well as generate data independently to improve the operation of its algorithms.
In addition, a certain effect in terms of working with personnel can be ensured by the introduction of AI solutions that, at first glance, are not at all related to HR. These include robotization as well as various auxiliary AI services for automating routine. They involve employees and thereby increase the attractiveness of the workflow.
Deterrents
Despite the positive mood of analysts, administrative skepticism still retains in the SME segment about digital HR services and their payback with fairly high investments. For this reason, the management of many companies is still in no hurry to invest in such innovations.
However, in the conditions of working in the candidate market, the loss of an experienced employee can be much more expensive for the company, which will entail the inevitable downtime. Hiring professionals will need time to find a suitable candidate, train him and adapt in a team. In addition, there are situations when the departure of one specialist leads to a whole series of layoffs – an experienced and proven expert often takes away the whole team to a new project, and this can already pose a real threat of existence for a small business.
Therefore, trying to keep a specialist or at least foresee his possible departure is much more profitable. HR services with AI help to understand in advance that an employee is uncomfortable and try to eliminate the problem with material or other tools and incentives.
To do this, the AI performs an impersonal analysis of all business communications of the employee, for example, for the emotional coloring of messages, the speed of response to requests and other psychological nuances of the state of the team members.
The second major problem is the lack of data. In large companies, it manifests itself in terms of quality, and starting with medium-sized enterprises, sometimes we are talking about insufficient data. Broad analyses, such as retention and motivation tasks, require more quality data. SMEs will have to spend a lot of time and resources, sometimes significantly exceeding the value of the desired result.
Nevertheless, the task of tracking changes in the usual efficiency of an important employee is quite solvable within the capabilities of medium-sized companies. As practice has shown, even a relatively small amount of information is enough to generate the most important parameters, such as assessing the employee’s effectiveness and predicting his burnout.
An example is a project implementing a technology solution in an IT integrator with about 500 employees. With a pilot survey and modeling on “historical” data, AI was able to “guess” the dismissal of 70% of employees who actually left the company over the past three years, as well as identify systematic gaps in the missing data system. After closing these gaps and running the system for more than a year, the company was able to prevent the departure of more than 10 important employees in a timely manner, which generally recouped the costs of the implementation project and subscription.
In addition to the two main deterrents, mistrust of data privacy protection, as well as compatibility issues with existing systems, remain. But this issue is relevant for all companies and organizations, without exception.
What’s next?
Already in Russia, there are developed cloud HR services at the ecosystem level. They enable SMEs to launch their own personnel project with a small budget and, in case of positive results, scale it into a full-fledged platform with a full set of HR services.
There are also universal HR solutions that are available to some small business profiles. If we talk about talent management systems, we can highlight HRbox, My Team, Mirapolis, Pulse from Sberbank, and People Hub from VK.
All of them practically close the chain of needs from start to finish. There are also many solutions available on the market that close individual blocks of HR tasks, such as training, adaptation, recruiting, and the like.
From the point of view of the further development of the Russian market of HR services with AI support, along with the offers of large vendors, we should expect the emergence of specialized startups with their own unique products. In terms of financing IT startups in the field of AI, everything is going well in the country. Grants, which are quite sufficient for product development before the beta or release candidate stage, are allocated by both the state and laboratories of large organizations.
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In conclusion, I would like to draw attention to the fact that Western analogs, if they were now available, would hardly have a significant impact on the general situation in Russia without general improvement. The point is in the regional specifics of such products, since, for example, computer models of employee burnout for the same USA will not work in Russia without serious adaptation of at least language models, not to mention the main algorithms.
By Alexander Embaturov, Head of Information Systems Implementation and Development Department, DataRu Consulting