Data offers employment agencies new opportunities for growth
Data is expected to become the most important asset of an employment agency within the next five years. Data analysis at digital competitors, such as online work platforms, is already firmly anchored in their business models. To compete with these parties the temporary employment sector should focus on data analysis too
The Netherlands and UK have most agency workers
The importance of temporary agency work differs considerably within Europe. The Netherlands, where 4.4% of the workforce is employed as agency workers, heads the list in Western Europe. Around 4% of the workforce is also employed as agency workers in the United Kingdom and Spain. By contrast, the figure for Italy is less than 1%. Even though temporary agency work is more common in one country than another, data analysis offers new growth opportunities for all countries.
HR services will increasingly be based on data
Through automation and digitalisation, more and more internal data is becoming available in the temporary employment sector. Within the next five years, HR services will thus increasingly be based on data, which will become an important asset for employment agencies. Data offers staffing agencies new growth opportunities, for example in online recruitment, gaining better insight into their customers’ wishes and improving the efficiency of their business processes. It also leads to new data-driven business models.
The Netherlands and UK head the list in temporary agency work
Share of agency workers in total workforce (20–64 years) in Western European countries, 2019
To make the best use of data analysis, staffing agencies first need to:
- Use automation and digitalisation in both the front and back office.
Data analysis can then be used to:
- Work more efficiently by optimising internal processes.
- Provide additional services to the customer, such as customised advice.
- Developing new data-related services, as a complement to current revenue models.
Four steps to a data-driven organisation
Automating, digitising and optimising internal processes is relatively straightforward. Comparison with the degree of complexity and return.
Step 1: Automate front and back office
An employment agency’s work largely consists of repetitive administrative tasks, such as registration, timekeeping and invoicing. To remain competitive in the future, the sector will need to automate and digitalise these processes as much as possible to not only compete with online platforms but also to reduce costs and tap into new revenue streams. Most temp agencies have almost completed this first step and now use an automated payment and invoicing system (back office), sometimes linked to an online recruitment system (front office). The second step can be taken on this basis: performing data analyses to make the business processes more efficient.
Step 2: Efficient ways of working
1 Data-driven recruitment
The candidate database is one of a staffing agency’s most important and differentiating assets. Recruiting suitable candidates is an ever greater challenge as the labour market becomes structurally tighter. With an online recruitment system, you have a much wider reach, including internationally. Various digital job boards and social media channels such as Facebook and LinkedIn are also often used to recruit candidates. These channels are mainly used by people finding their way around the labour market. Data can support analyses in several ways, including who clicks on which vacancy, which medium produces the best candidates, how to reach a candidate at the right time and where, for example, to find candidates who are not actively searching.
2 Digital matching of supply and demand
With an online recruitment system, supply and demand can be matched more and more digitally using artificial intelligence. This is faster and cheaper than if a recruiter does it manually. The time and costs between the initial interview with a candidate and their placement with a company can therefore be slashed. Recruiters also have more time to spend on other value-added tasks, such as providing high-quality advice to companies on HR services.
3 Dynamic pricing
Online platforms such as Uber and Booking.com work with algorithms to match prices as closely as possible to supply and demand (dynamic pricing). Earlier ING research shows that the temporary employment sector still seldom uses dynamic pricing despite a tight labour market. This is despite the fact that data analysis pinpoints where there is a shortage or oversupply of a certain professional group, so you can automatically adjust rates accordingly.
4 Improving productivity
Based on data analysis from the front and back-office systems, the productivity of both recruiters and agency workers can be measured and then improved. Important KPIs for recruiters include speed and placement costs, while for agency workers, it is mainly about maximum employability and minimum absenteeism. For example, data can be used to see how many hours someone is working and how long their contract still has to run.
YoungCapital – Differentiating by service
“Self-service is becoming more commonplace, and this development has been partly helped by the coronavirus pandemic. Five years ago, companies were still not receptive to self-service, now more so. We are responding to this trend with our online platforms: YoungOnes and YoungCapitalDirect. As this also gives us more insight into what our clients do or do not want to do themselves, we can then adapt our services accordingly. While it’s still mostly ‘one size fits all’ at present, we can start personalising based on data. The revenue model then moves more towards a model in which the rate depends on the desired service based on the principle the more you do yourself, the lower the price will be.”
Transition from staffing agency to HR service provider
Services that temp agencies provide to the client
Step 3: Customised advice
1. From reactive to proactive
The added value of employment organisations increasingly lies in providing high-quality advice. New insights can be obtained through a targeted search for data patterns and connections. The client (user undertaking) can thus be advised in various areas helped by data analysis. For example, which legislative changes affect staff and how the temporary workforce can be planned more intelligently. Increased absenteeism can also be brought to a company’s attention and reduced. Another form of customised advice is the proactive e-mailing of anonymous profiles, in compliance with privacy legislation, to companies that expect a peak in demand for personnel in the short term. For example, based on weather forecasts, the demand for restaurant staff will increase when the weather is good.
2. From employment agency to HR service provider
Besides recruitment and providing customised advice, employment organisations are moving more towards performing HR services, unburdening companies of as much of their HR responsibilities as possible. For example, they can take over part of the HR services for the temporary workforce – from organising it and acting as an intermediary to coaching. This process turns the flexible worker into a full partner supported by the employment agency throughout their career. In this case, data analysis is used to help the flexible worker adjust, where necessary, for instance through training or education.
Randstad – Sustainably employable
It’s not only at Randstad that we’re working on automation, but our customers are too. This also affects us because, in some cases, customers need fewer staff, or staff with different skills. To reduce the mismatch in the labour market, it’s therefore important that flexible workers continue to develop themselves. By using data analysis, we can empower customers, for example, by looking at what knowledge and skills are required now and in the future. Based on this, we can support flexible workers throughout their career, for instance with training or education, or to coach them into other work. The ultimate goal is for everyone to always be – and remain – relevant in the labour market.”
Step 4: New revenue models
Data-driven revenue models
The most advanced form of data analysis is new data-driven revenue models, such as customised analyses – data-as-a-service (DAAS) – to which companies can subscribe. Customer data is thus becoming an increasingly valuable asset. One option is to set up a benchmark so that companies in the same sector can compare their business and staff performance with each other. Other options include providing average salaries for each sector and producing CVs, both at a fee. After all, data analysis shows a staffing agency which CVs are the most effective.
Brainnet/Pro Unlimited – Data as a service
“Accessing, analysing and using data are becoming increasingly important in HR services. The US MSP service provider Pro Unlimited is one of the market leaders in data combined with HR services. As Pro Unlimited recently acquired Brainnet, we have access to global HR data that we can use, for example, to provide paid benchmark summaries to our clients. Clients thus gain insight into average rates per job, per city or per country, education levels, qualifications and job profiles, among other data. Based on these insights, organisations can anticipate the future better and further optimise their workforce.”
Still a world to conquer
Discussions with various employment agencies reveal that although the majority are interested in data analysis, it is not yet commonplace within the sector. Most agencies are working on steps 1 and 2, which focus on automating and digitalising the front and back office and making processes more efficient. These are the most accessible steps. The more advanced steps towards a data-driven organisation – customised advice and developing new revenue models – are still in the future for many employment agencies. A whole world waits to be discovered here.
The more complex the step, the fewer staffing agencies do it
Schematic representation of the number of companies that have taken the steps towards a data-driven organisation, measured by complexity.
Obstacles to performing data analysis
Many staffing agencies are not yet actively engaged in data analysis because working with data involves various challenges:
- One of the main challenges that many staffing agencies face is an outdated infrastructure, which makes it difficult to connect different systems.
- Data quality is also important. Good input is a prerequisite for good analysis and matching. Effective online recruitment requires the existing database to be continuously enriched with new and standardised data, so it remains up-to-date and relatively easy to analyse. That takes a lot of time.
- Data is often located in different departments in an organisation, which often work in separate silos. Data analysis has more added value if search queries can be applied to all available data.
- Knowledge of data analysis in an organisation is often lacking, including because of the many possibilities. While digitalisation is often just a side issue these days, it will be one of a company’s main assets in the future. As a result, not all possibilities are used optimally.
- Laws and regulations hamper digitalisation because regulations are often not standard, but custom-made.
- Finding good data analysts is a challenge as the market is small.
Customisation is the future
As recruitment can largely be done digitally, whether or not through an online platform, employment agencies are expanding their services more towards HR. The added value lies more in providing customised services, through new business models or otherwise, which facilitate both customers and agency workers as best as possible. This will be needed if tight labour market conditions return and the legislation on flexible work is amended.
Customised services offer scope for better profitability
Customised services could also offer scope for better profitability for the sector than is now the case. Because of stiff competition, profitability is currently between 5% and 10% on average. Instead of a price war with a race to the bottom, customised service pricing is based on high-quality services that support higher margins.
Tips for getting more out of data analysis
- Ensure that you have a good software system, for both the front and back office, which also connects with each other so fewer manual tasks are needed.
- Ensure that the corporate culture focuses on data.
- Make someone responsible for the digital strategy.
- Hire a data analyst. Good data analysts pay for themselves.
- The quality of the data depends on the input. This is why it’s important to standardise as much as possible.
- You don’t have to develop everything yourself. This requires a lot of time and large investments that often don’t pay off. For smaller parties, in particular, there are now many software systems on the market that you can use.
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