Modern technology allows measurements to be taken in so many more ways than was previously possible. The limiting factor is understanding what is possible, and ensuring that the solution is effectively implemented and properly used.
Another limiting factor is the lack of understanding, often at a management level, of the power of AI as a tool to more effectively manage people. A CIPD survey of 2018 of more than 3,500 business professionals revealed that: Only 39 per cent had access to people data for decision-making purposes; Only just over half (52 per cent) were actively using people analytics to tackle business issues.
These numbers should be higher.
If we look at French supermarkets, these are known to be significantly more efficient than UK supermarkets. One of the reasons for this is investment in technology to monitor the business and people performance. One example is how they monitor the performance of their cashiers. Systems have been introduced to monitor the number of items each cashier processes and the speed at which they do so. It is clear that proper labelling and ensuring that customers arrive at the counter with everything labelled (including at fruit and vegetable which customers pack and weigh themselves) will speed up process. The more items a cashier passes, the quicker each customer gets out, and therefore the fewer cashiers a business needs. Ultimately, being able to reduce the number of cashiers by 3 or 5 due to efficiency savings in a line of 20 cash tills is a significant saving for a business. Yet this isn’t necessarily a bad thing for employees – rather, it allows them to be more effectively used – on the shop floor, for example. In an employment environment such as France, where it is very difficult to fire people, these analytics are rather used to motivate employees to do better: the carrot rather than the stick. If performance numbers are published, this means that cashiers can evaluate themselves. Employee reward systems identify the fastest cashier and often this information is made public – in the form of employee of the month panels. Such systems encourage cashiers to work fast. But it also links them to the performance and success of the business. Most people take encouragement in feeling that they make a difference and are contributing to their workplace. So the AI that monitors performance leads directly to greater job satisfaction.Some HR professionals say that data analytics should not be seen to be linked to boosting performance. One wonders: why not? This should be part of an overall approach to extract the best an organization and its people can produce.
Clearly AI can be used to automate processes to avoid errors or omissions. Fewer errors and omissions mean people feel more successful, in control and able to focus on important matters. Examples include processes that ensure all employees’ paperwork is up to date, work permits, passports, relevant registrations, critical continuing education, first aid certificates, insurance deadlines, renewals. The list is endless. Similar but probably higher up the “sophistication ladder” is monitoring gender diversification, numbers of languages spoken. Understanding staff turnover patterns generally and by departments or across similar departments in different locations can be very valuable. Why for example is staff turnover in an office in Manchester twice that of another office in Plymouth? If employing a large number of people of a particular faith in one location, what is the pattern of attendance during a period of important religious festivals and how does one manage that? All such processes can be automated to better inform and to increase business efficiency and anticipation.
Effective Use of Information
This becomes especially important when moving into more sophisticated use of human capital analytics. This involves having effective systems which gather relevant information that is important to enable an organisation to leverage its people’s potential and value. Having gathered the information, the key is how to use it. Too often data remains buried and its content or conclusions are not fully used or fully understood. Yet ultimately, the enhanced use of AI should enable better HR and business decisions to be taken. Introducing such systems takes a commitment from the top because it will require a top-down buy-in and understanding of the processes and systems required. IT, HR and senior management will need to work hand-in-hand to identify what they need, identify desired outcomes and the likely impact of successful implementation. Listing the benefits to be achieved is helpful:
1. Better understanding of your people
2. Better information about your people and their performance
3. Better communication with your people
4. Better administration of your business
5. More accurate performance measurements
6. Moving beyond the workforce – better information gathering about your market, your business community and clients
Achieving each of the points above would undeniably assist any business to make better decisions and to manage itself better, and therefore likely result in it being more successful. Relevant information can be collated and harnessed using data analytics which can assist with identifying problems and suggesting solutions and leading to better informed decision–making. The technology exists, so the question is whether more businesses are prepared to take on the challenge that the technology presents. They should.
Interested in data analytics for HR? We recommend Mission Critical HR Analytics Summit 2019.