HR Analytics: Rubbish In, Rubbish Out

Despite the proliferation of articles and solutions for producing advanced analytics and fancy dashboards, many organisations – both large and small – struggle to produce basic HR reports.

For the HR professional this can be extremely frustrating. On the one hand, we constantly read about “big data” solutions (for processing large, complex, and fast data sets), artificial intelligence (AI), bots (software applications that are programmed to do certain tasks), and machine learning (systems that learn and adapt from patterns in data without following explicit instructions), yet many HR teams cannot reliably produce core data such as headcount, turnover, and demographics. I won’t even mention more complex data such as payroll related costs, payroll accounting, and productivity analysis.

In this article I look at the following topics:

  1. The main reasons why many organisations have poor “HR data”;
  2. Some relatively simple steps that organisations can take to improve the quality of their underlying data (and thereby lay the groundwork for more sophisticated analytics); and
  3. How the design of HR software (HRIS) can help to address points 1 and 2.

Based on my personal experience, both as an HR professional and working with clients, there are a number of common themes, including:

  • Lack of investment in intuitive HR systems, which leads to HR and line managers handling data in Excel files.
  • Use of multiple HR systems (for different processes) that are not integrated with one another, which results in too much manual effort (data entry) and human error.
  • Different areas of the same organisation using different systems for similar processes (usually with different data fields, values, and formats), which leads to complexity and inefficiency in consolidating data for reporting. In larger organisations, this may be the result of mergers and acquisitions, and an inability to consolidate systems.
  • Too much focus on the data needed by the finance/accounting department at the expense of what is needed to manage an organisation, including the people.
  • The use of different systems for HR data and payroll data, which removes the incentive for the main HR system to have complete and accurate data.
  • HR teams lacking quantitative skills and a general interest in data and numbers. The HR profession does not tend to attract people with this passion and these competencies.
  • An organisational culture that has never emphasised the importance of good quality HR data, perhaps because it is seen as “HR data” as opposed to “business data”.

Of course, these themes are often interconnected. For example, a lack of investment in systems may affect the ability of HR and managers to effectively manage data. Conversely, the organisation’s culture or a lack of relevant skills or interest in the HR team may be a barrier to the organisation getting value from a perfectly decent HRIS.


At some stage every organisation finds itself in situation where it has little choice but to improve the quality of its organisational data. It may take many years, even decades, to arrive at that point but the day will surely come. Here are some practical suggestions for when it does:

  • Organisations need to select HR systems that are intuitive to use and easy to maintain. This may even mean trading off on some desired functionality in a bid to keep things simple, or simplifying certain processes (click here to see the Q1 2022 blog on this theme). Some organisations have very little HR software and their HR teams would love a simple solution. Other organisations have very complex (and expensive) solutions that do not, in reality, sufficiently help HR and line managers in their day-to-day tasks.
  • Organisations need to either use a “one-stop-shop” HR solution (of which there are many) or, if the organisation has made the strategic decision to use different/specialist software for different processes (e.g., recruitment, performance, training, etc), invest in integrating your HR systems so they contain consistent and up to date data. 
  • I have been involved in acquisitions and mergers, as well as inherited HR roles where I have been responsible for business units post a merger or acquisition. Whilst it is undoubtedly hard work and fraught with cultural tensions when HR systems are consolidated, doing so is essential if organisations are to be able to produce good data and business insights. Consolidating systems also adds a lot more value when the exercise involves harmonising the data of the different organisations.
  • Thankfully, I am seeing an increasing tendency of organisations to realise (perhaps after many years of push-back on HR directors), that a finance system or a payroll system is not the same thing as an HRIS. A finance system cannot be expected to meet all of an organisation’s human resources needs. Likewise, an HRIS cannot be expected to meet all of an organisation’s finance and accounting needs. Nonetheless, a sensible balance needs to be struck and there are an increasing number of HR software solutions that have been designed to meet the core accounting and finance requirements.
  • By using an HRIS that includes a payroll module or integrating the HRIS with the payroll system, you immediately “up the ante” on the importance of the HRIS having complete and accurate data. This is because if the HRIS contains inaccurate data it is likely to result in inaccurate payroll (payments, tax withholding, social security, pension deductions, etc). Missing mandatory data may event prevent an employee from being paid. Making payroll dependant on the quality of data in the HRIS concentrates the minds of employees, managers, and HR alike.
  • HR directors need to ensure that their HR team has a good mixture of professionals with strong quantitative and qualitative skills, and an interest in numbers and data. Ideally all HR team members would have a good all-round skill set, even if they prefer a role that is less data oriented. It is, however, no longer realistic to think that an HR team/department can be high performing if it is unable to manage data and work with numbers. You need to get your recruitment right and make it clear that a minimal level of data competency and numeracy is expected of everyone in the HR team.
  • Changing – or evolving – an organisation’s culture is probably the most challenging theme to address, and I certainly do not have the time here to do the topic justice. In essence, leaders need to make it clear that everyone is responsible for the quality of organisational data and ensure that there are positive and negative consequences associated with this. For example, HR cannot have good data if employees and managers do not share information with HR in a timely manner. If HR is not receiving timely data there may be underlying causes such as poor or unclear processes, which will need to be fixed. HR teams also need to take pride in the accuracy of their data and very low error rates on processes that require data, such as payroll.

We have tried to design PeopleWeek in a way that helps organisations to have clean and complete employee (personal and professional) and organisational data. Other HR software may have similar features. Even if your organisation does not have an HRIS, some of the design principles used by PeopleWeek would help you to better manage data in an Excel spreadsheet or “DIY” database. Here are some examples:

  • Use dropdown lists rather than free text fields: Avoid data entry errors and the proliferation of unnecessary data values, for example, job titles, contract types, absence types, cost centres, department names, pay elements (for payroll). A classic example is that you want to run a report based on job titles but 10 employees performing more or less the same role all have slightly different job titles;
  • Explain what different data fields mean: It may not always be obvious what a field means. An example is that sometimes HR get confused about the differences between “original employment date”, “continuous employment date”, and “employment date”. A simple explanation in the UI of a system (or in a spreadsheet) can eliminate the errors;
  • Use an HRIS that contains a payroll module* or can be easily integrated with your payroll system that is used to calculate payroll and generate payslips.
  • Control who can create new values in the HRIS: In many organisations, HR (and even managers) are free to create new values such as contract types, leaver (termination) reasons, work locations, department names, cost centres, job titles, training types, grade levels, etc. By controlling who has system admin rights to do this, you can eliminate such data “pollution”. When combined with the use of dropdown lists, it is even more effective;
  • Hard code rules in the system: By creating simple system logics or rules you can avoid human error. Examples are linking departments to a pre-defined cost centre, mapping pay types to pre-defined monetary values, and work permit expiries triggering an “invalid data” value;
  • System generated reminders: Notifications or alerts are a great way to remind employees, their managers, and HR to take specific actions on time, thereby keeping data up to date;
  • Easy workflows: Processes that avoid unnecessary (too many) steps and walk you through a complex task (e.g., transferring an employee from one entity to another), greatly reduce error rates;
  • Use Date Pickers: Something as simple as a date picker tool helps to avoid human error entering dates and confusion between date formats;
  • Make fields translatable to help with reporting: Often systems and spreadsheets are unable to identify that data contains repeated (the same) values but in different languages. If a system allows values to be translated into multiple languages, you can generate smart reports that recognise two values that look different are, in fact, the same (e.g., “Male” and “Homme” or “Marketing Director” and “Marketingleiter”).

*PeopleWeek has a Payroll Data Management module that is customised for each country’s payroll requirements.


Quality data is the starting point – the foundation – for value-adding analysis, metrics, reporting. This is what all organisations and their HR teams should be, and usually are, striving towards. However, it can feel like a distant reality. Without doubt it takes time to go from “rubbish in, rubbish out” to “quality in, quality out”. Nonetheless, I know from experience that it is achievable by addressing the root causes of an organisation’s poor data quality and using smartly designed HR software to make data management easier.

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