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When we see high profile leaders in government and industry that promise to increase efficiency, the automatic association could be that the efficiency of the workforce is equal to cutting jobs. But that rarely is the case.
The layoffs through the board are not, in themselves, an efficiency recipe. In fact, they could lead to exactly the opposite: loss of high performance or critical talent.
That said, efficiency is having a moment and for a good reason. Companies are being beaten by a new technology, changing tariffs, marking productivity and inflation. In these uncertain times, finding ways to obtain more of its people is a matter of survival.
In essence, efficiency is a nuanced, but absolutely critical concept. Too many companies do not understand and measure it. Obtain more with fewer requests thinking differently and use data differently, with a little help from AI.
This is how companies can take advantage of the data to increase the efficiency of the workforce in the right way.
Related: 6 transforming methods to increase the efficiency of the workplace
1. Start with why
Before a company does something in the name of efficiency, you must see the overview. The key question: What problem are you trying to solve?
Efficiency means different things for different businesses, after all. A furniture manufacturer can have the objective of producing as many chairs as possible, while another decides to focus on the quality of the quantity.
But too often, the de facto objective of efficiency exercises becomes cost reduction. Having 10% of its employees can generate short -term savings, but in the long run, it is demanding difficult to cut its path to better results.
Replacing high potential talent can cost a business up to three times the salary of the outgoing worker. When companies take into account the total cost of recruitment, training, competition time for new employees and loss of productivity, reduction in the size of the height that arises as the least effective path.
Related: 4 ways in which leaders can increase efficiency in the workplace
2. Understand the people and resources you have
Even after working in People Analytics for more than a decade, I am still surprised how many organizations are in the dark about their own workforce. Many large companies fight equally to obtain a precise count of permanent and temporary employees in different business units.
Meanwhile, companies continue to define employees in terms of rigid “roles” instead of thinking in terms of “skills.” Someone’s work title could say “customer service representative”, for example, but their set of underlying skills includes product knowledge, people’s skills, technical knowledge, etc.
At a time when technology is changing work overnight, intelligent companies increasingly use AI skills to catalog employees and combine them with new and evolving roles. Instead of dismissing that customer service representative, for example, they are rescuing and changing talent to sales or business development.
This approach produces clear dividends. In addition to having more than double probabilities of placing talent effectively, skills -based organizations have approximately 50% more likely to improve processes that maximize efficiency.
3. Connect people with commercial results
There may not be a more important and past way to improve the efficiency that this: unite people and commercial data.
People’s data are all information about what employees do, such as their performance and contributions. Commercial data are treated as They work: metrics such as sales figures, customer satisfaction and profitability.
In so many companies, this information is still Silad. HR data is trusted from people, while finance, operations and sales and marketing accumulate commercial data. Only when a company broken those silos combining people and work data emerge a real image of their employees.
Here is an example of Cartier’s real life, the luxury jeweler. For its hundreds of stores worldwide, the company integrated data from people and point of sale. That allowed him to see what locations were working better than others, in addition to the history training of each store manager. Knowing which sales training obtained the best results, Cartier could apply it where necessary to improve efficiency.
Compared to its average peers, high performance those are 400% more productive. That rises to 800% for managers, software developers and other complex roles. By identifying adequate people at the right time for proper work, a company can avoid dismissals in general that could end up reducing precisely the wrong people.
Related: 12 unconventional ways to boost employee productivity
4. Democratize access to data and ideas
It is difficult, if not impossible, improve efficiency if you are flying blind. To make the right decisions, people and performance data must be accessible, not only for VP, but for first -line managers who make key hiring decisions.
This is where so many organizations are unfortunately short. The historical data of the workforce have been jealously kept or buried in spreadsheets and dispersed in multiple systems. Even basic questions require weeks of waiting, sometimes months, so that analysts exceed numbers. Meanwhile, managers have a leg to trust intuition to make talent calls sensitive to time.
Making better decisions requires democratizing the data of the workforce, while preserving privacy and security, and that is where AI is demonstrating a blessing. Do you need to know who your best artists are by location? What managers are more effective? How do you compare the participation of employees with the reference points of the industry?
The new ia tools unite data in disparate systems, extracting ideas in seconds. Dense jargon and spreadsheets are replaced by simple English explanations. And like a human analyst, the best tools make informed suggestions about what the next steps could have the greatest impact.
5. Review the results and adapt in real time
Efficiency is not a unique exercise. At a time when colleagues are affirmed with commercial conditions that change rapidly (rates? There are no rates? Your assumption is as good as mine), the planning of the workforce cannot simply be an annual event.
The best tactic here is to adopt a continuous approach to assess how many workers your organization needs to support growth, guarantee profitability and achieve objectives.
The new dynamic analysis tools help companies do exactly that. When tracking the workforce plans against what is happening in the field, they allow management to make real -time adjustments, so the forecasts are constantly updated. These tools also help human resources and finance to reach the same page by reviewing the planned, planned and real costs and the correction of the course when necessary.
Another example of real life: Providence Healthcare recently found ITELF by observing the billing in key roles. Using adjustment data to make predictions, he was able to identify a group of employees where the organization would at least reach the equilibrium point paying more to stay, and, in some cases, he would simply save money.
By using the estimated billing costs and calculating the cost of adjusting wages in specific groups, Providence saved approximately $ 6 million a year.
Nor are these results unusual. Adopt a more dynamic approach to workforce planning is worth it. In a study, companies with a solid planning of the workforce increased productivity by up to 25% of approximately two years.
For companies in the unpredictable commercial climate of today, improving the efficiency of the workforce is a very real priority. But simply cut and burn can create more problems than you solve. An approach backed by data, with some help from AI, is a safer path towards efficiency gains.
