HR Analytics

HR ANALYTICS –
PART OF HR’s DIGITALISATION TRANSITION

HR Analytics is currently one of the hottest trends in the HR sphere and a natural part of the HR function’s digitalisation process. Interest in this area is growing very quickly. Many functions and departments have long been using Business Intelligence and Analytics, but HR has usually not made as much progress in its digitalisation process. HR Analytics helps HR to a stronger position, making it easier to ensure its voice is heard in the company’s top management.

The aim of HR Analytics is to give the organisation the ability to analyse HR data. It is also possible to connect HR data with some other type of operational data or external data in order to understand contexts, see trends, identify deviations and create a unified image of the operation. It is even possible to predict events with the help of new technology. The analysis should quite simply be able to encompass everything from group and company level to department and so on. The consumers of this data are the company’s executive management, managers and, not least, HR. Interest in HR Analytics has seen a considerable rise in interest in recent years and there are multiple benefits and application areas!

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SEVERAL DIFFERENT APPLICATION AREAS

The basis of an HR Analytics solution is often the data from the HR and salary system and it encompasses analyses based on the company’s personnel and managerial structure. Classic key performance indicators such as the number of employees, FTE (full-time employees), hours worked, number of sick and healthy employees, personnel turnover, average salaries and salary costs distributed according to parameters such as organisation, position and form of employment are common in HR Analytics. HR organisations would benefit considerably from being able to conduct analyses in additional areas! What you want to measure and analyse depends largely on your operation’s orientation.

Workforce Analytics

Used for analysis of parameters such as personnel costs, productivity, personnel requirements (short- and long-term), staffing levels and recruitment needs.

People Analytics
Used to measure and predict the effect of HR programmes and initiatives. For instance training, health and welfare, talent and career strategies, organisational changes, business intelligence events or financial results. By correlating these with parameters such as stress levels, performance index, motivation index or personnel turnover, you quickly gain a better basis for taking decisions (analyses in this area are also known as Talent Analytics).

Payroll Analytics
Payroll Analytics is analysis of salary data. It is used to predict and proactively solve challenges relating to salaries and benefits. It is also possible to create KPIs for efficiency and quality with regard to salaries in order to measure process efficiency.

Compensation and Benefits Analytics
Analysis of competitiveness and the cost of the company’s total offer, such as fringe benefits, bonuses and pensions. It is also possible to chart salaries based on competence, age, gender, salary gap, pension costs and prediction of salary costs in the long and short terms.

CHALLENGES OF HR ANALYTICS

One of the reasons why more companies do not work actively with HR Analytics is that HR data is often found in several different source systems. For instance in Salary, HR, Time Reporting, Travel Expense, Staffing Systems and Benefits Portals, or in various kinds of surveying tools and systems that the companies use. In larger companies or corporate groups it is not unusual to have different HR solutions and for data to be stored in multiple systems or databases. With today’s Analytics solutions it is possible, with relatively easy methods, to bring together data in a data warehouse and in this way collate data and permit analysis. The next step is to correlate and conduct analyses together with other data, for example from business, CRM or order systems.

Today many HT functions work in an obsolete way with a lot of manual Excel processing or via simple analyses in existing systems. As a result, a lot of relevant data is ignored because it cannot be handled manually, and there is a considerable risk of error. Manual analyses also tend to require rather a lot of work and only provide an instantaneous snapshot image of what is relevant for the current week, month or department, for example.

HOW TO GET UNDER WAY WITH HR ANALYTICS

The first step is to create an image of what you want to analyse in order to be able to supply the operation with new insights. It is by no means sure that we will see all the correlations in this first phase! One important part of this step is to define all the performance metrics and the dimensions from which you want to conduct the analysis. Agreeing on definitions within the operation is often a bigger challenge than you might be inclined to believe, but it is an important basis for a successful start.

In the next step it is time to choose your Business Intelligence tool. Many companies have long used their BI solution for budget and planning work, analysis of data from business systems and/or prediction of stock and order status. It is common for salary and HR data to be included in the analysis, but it is not driven by HR. If your company currently works with a BI tool, the step up to HR Analytics can be simple!

Now it is time to create a data warehouse or to complement your existing data warehouse so you can get more out of your company’s HR Analytics work. A first step is to collect and structure HR data so you can once and for all ensure that key performance indicators, reports and analyses are updated when new data is added. You do this by gathering data from various data sources. Examples of such sources are Salary, HR, Time Reporting, Travel Expenses, Staffing Systems and Benefits Portals, or various types of surveying tools. The data in a data warehouse not only provides an instantaneous snapshot image of the current status, it is structured in such a way that you can break it down, look for connections and perform analyses in a wide variety of ways without first having to collate the data. It turns out that many companies invest a lot of time in collating data, when instead an operational data warehouse speeds up this work and makes it much more efficient. By adding a data warehouse it is easy to combine HR data with data already found in the data warehouse, for example production volumes and financials, and it is also possible to input such data.

The final step before you are up and running with HR Analytics is about visualisation of data and making it more easily accessible. Once a data warehouse is operational it is time to start analysing. The analyses and key performance indicators that the company wants to monitor on a regular basis are often presented on a dashboard. A dashboard is a visual and user-friendly display featuring those key performance indicators that are important to the person reading this information.

HOW CAN ADVECTAS HELP YOU?

Advectas helps decision-makers at all levels to take better decisions based on data-driven insights. For us business intelligence is about much more than just gathering together and visualising data with the help of various tools. We have therefore brought together specialists from all areas relevant to the business intelligence sphere representing everything from data management experts and data science specialists to management consultants.

Our unique competence is the interplay between human being and technology – when the balance between responsibility and roles, processes and cultures is at exactly the right level. We also serve as an independent partner for our customers in the choice of IT solutions and business intelligence tools.

Advectas’s strategy is to work together with those suppliers who are at the very forefront of their respective areas as regards development, maturity and market presence. We also offer various service packages, for instance in the form of training, support and management. In addition, we can assist customers with comprehensive outsourcing of various functions in business intelligence and data science.

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