“Consider the discipline with which companies measure, manage, and grow financial capital. Now think of how they manage human capital. The “most important asset” is largely unmanaged.” Bradley Hall, “The New Human Capital Strategy”.
In today’s world of work, People Intelligence is the new Business Intelligence. I’m not suggesting that it replaces other forms of Business Intelligence, but I am suggesting that it is, at least, as important as other aspects of Business Intelligence. But, why would I make this claim? Ask yourself, what percentage of your budget is “people”?
What is Business Intelligence (BI)?
Business Intelligence (BI) is a discipline that includes processes and methods of collecting, storing, and analysing data from business operations or activities in order to make better, actionable decisions with the aim of optimising organisation performance.
Any organisation can use data to transform operations to optimise performance. Financial services organisations use BI to bring different data together to understand performance metrics and identify areas of opportunity. Commercial organisations use BI to understand customer demand and customer preference. Organisation leaders can track performance and identify the key drivers of performance to improve performance across the organisation.
What is People Intelligence?
People Intelligence (PI), an extension of BI, is about connecting people data with business data to make better decisions for the business. PI includes the processes and methods of collecting, storing, and analysing data from People and Business Operations in order to make better, actionable decisions with the aim of optimising organisational performance through people.
As such, PI is a management tool, not merely an HR tool. PI is not about how well HR does at delivering HR services. It’s not “internal” looking at HR performance. PI is “external” looking at how well the people processes and activities translate into business performance.
PI is about how “people” data can be combined with financial and other data, and leveraged by other areas of a business – any department, any function, across teams, and by employees themselves to understand productivity, engagement, collaboration and more.
Where to Start with People Intelligence?
Very often we find that people data in organisations is disparate, incomplete, and inaccurate. The very antithesis of data to be used for analytical and intelligence purposes. Too much people data can only be found in spreadsheets scattered around the organisations.
So, the first place to start is with finding that data – all of it, or as much as humanly possible – and putting it together in a common database. This doesn’t have to be a computer database, in fact, preferably not at the start.
Data Quality Management defines the following dimensions for good quality data:
- Complete – data meets the expectations. E.g. an employee’s first name and last name are mandatory but middle name is optional; so a record can be considered complete even if a middle name is not available.
- Consistent – data across all systems reflects the same information and are in synch with each other across the enterprise, e.g. Employee status is terminated but pay status is active.
- Conform – data follows a set of standard data definitions like data type, size and format (e.g. date of birth is always in the format “yyyy/mm/dd”
- Accurate – the degree to which data correctly reflects the real world object OR an event being described.
- Integrity – means data is valid across relationships (e.g. HR and Finance) and all data can be traced and connected to other data.
- Timely – information is available when it is expected and needed.
Once you have collected the data, found the similarities, corrected the inaccuracies, discovered what’s missing from the data and have a consolidated database of accurate, up-to-date data, you are ready for the next step of People Intelligence.
Categorisation
There’s no one right way to go about categorisation when it comes to PI. But, what is indisputable is, categorisation is critical for PI if we are looking for better, actionable decisions.
For example. To know that we have an average of 10% staff churn is, at best, interesting. What makes for better, actionable decisions is know that, within that average, we have a staff churn of 15% in our top performers. To know that we have an employee engagement score of 84% is interesting. To know that, in that 84% we have an employee engagement score of below 40% in a particular management area enables us to make better, actionable decisions.
So, how can you consider categorisation. There are a number of ways:
- Age – how many employees are approaching retirement?
- Performance – how many high performing employees are approaching retirement?
- Role Criticality – how many high performing employees in critical roles are approaching retirement age?
- Scarce Skills – how many high performing employees with scarce skills in critical roles are approaching retirement?
- Tenure – how many high performing employees with scarce skills in critical roles that have been with the organisation for longer than 15 years are approaching retirement?
Do you begin to see the value of categorisation when it comes to better, actionable decision making?
These are not the only ways of categorising. In your organisation you might also like to know by some role category. For instance, how many high performing sales people are approaching retirement? Or, how many high performing “product facing” employees are approaching retirement?
The categories are virtually limitless and depend on what information you need to make the better, actionable decisions.
A bonus is, its really easy to do this categorisation once you have your database set up.
Even Better, Actionable Decision-making
Those questions are all well and good but, what about questions like:
- On which category of employee do we get the best return on investment?
- Do we get a better return on investment from training internal employees or recruiting skills?
- What is the financial risk of losing top performers?
- Is return on investment in people increasing or decreasing?
- What leadership qualities produce our high-performing teams?
- What is the impact of employee engagement on customer retention?
These are a very standard management questions. But, they are complex PI questions, especially when you start adding categorisation.
With the correct data, and the correct PI, the answers to these questions all lead to better, actionable management decision-making.
And that is why People Intelligence is, I believe, the new Business Intelligence.