Written by our guest blogger: Lyndon Sundmark, MBA People (HR) Analytics Consultant / Data Scientist
If Workforce/HR/People analytics truly have the potential to both reinvent and transform HR practices and business outcomes, the wakeup call might end up being the impact of HR and the organization not benefiting from that potential.
Consider the following:
- Your own performance as an HR department and as an organization may be limited – comment provided in the Google people practices article above :
- ‘The basic premise of the “people analytics” approach is that accurate people management decisions are the most important and impactful decisions that a firm can make. You simply can’t produce superior business results unless your managers are making accurate people management decision’
If you aren’t collecting the data, measuring, and doing the analysis – how do you know you are producing superior results?
- Your own competitiveness may suffer. One of the more annoying trends impacting HR these days, for some, is the ‘justifying your existence’ as HR in your organization. Annoying particularly because it often feels like an organization thinks it can get along without HR and HR practices. In reality of course it can’t (any more than it can do without finance and accounting etc.).But the reality may be that it can get its HR activity done without ‘You’. Are ‘You’ doing it better than the alternatives (contracting it out, reorganizing to create’ shared services organizations’, etc.)? Do you know? How do you know? I suppose the only thing worse that ‘justifying your existence’ is not even being given the opportunity to ‘justify your existence’ before restructuring decisions contract it out. If part of the picture of People analytics is HR process improvement analyses, and as an organization this isn’t built into being part of your HR operations, it would be difficult to show your competitiveness. This isn’t just an issue for HR but all organizational operations. Some organizations have the view that if you are not in direct delivery of the organization’s overall product or service – you are not part of the core business- as if organizations could operate without organizational infrastructure that keeps the organization operating smoothly. The other mistake I think organizations make here is that they may demand ‘justify your existence’ without those who are demanding having any data to prove that the alternatives are any better either. The point is HR significantly helps its circumstances when it knows and can show its internal competitiveness through metrics and show it compares to other organizations by benchmarking. And proactively doing this, ahead of an executive ‘ask’.
- The means to have a ‘data driven’ approach isn’t new– but the execution of it and visibility of it is likely more recent. The basics to have ‘data driven’ HR: the HR function and practices, the ability to create and store data, the existence of statistical packages for analysis has been around for over 35 years in some form. The willingness to recognize this and have it become part of the DNA of what we do in HR and how we do it is what is new. This is probably an area of HR that has needed recognition for quite some time. The above Google People practices described are one example of this and its recency.
- The current provision and use of HR metrics where it does exist and occur can sometimes be ‘insufficient’. I am a strong believer in the provision AND use of metrics. But insufficiencies can exist in both provision and use. In fact sometimes the provision affects the use.
- The technology exists and is used in many organizations to create the HR metrics – data warehousing and business intelligence tools. Dashboards are created. And yet often the data is simply reviewed and no targeted action taken. Sometimes it’s because the metrics are not generated in a way that allows for the slicing and dicing and further analysis inside the organization. When that happens, there is no means to analyze the problem internally and take some targeted ‘data driven’ action. We get the use for ‘benchmarking’ (external use) right-comparison to other organizations, but we don’t get the internal picture right.
- Being able to ‘take action’ implies that you are able to ‘interact’ with your data. There are many powerful visual tools that are emerging for use in data analysis and slicing and dicing in real time on your metrics. This interaction is often critical for ‘what if’ types of questions and analyses. However, where there can sometimes be an insufficiency here is knowing ‘what to pay attention to’ in the data. Part of what to pay attention to is based on what questions you are asking. But part of it is also using statistics, statistical tools and statistical analysis to determine what is statistically significant. This is important because we can create and process so much data that it can be easy to drown in it. And if we drown in it, it’s unlikely we will be able take targeted action as well.
There may be other reasons for this being appropriately perceived as a wakeup call as well. The above are just a few thoughts that come to mind.
How Might HR Respond To This?
I suppose part of the answer to this question is based on whether you accept the premise that the Google People Practices are based on and that you want a ‘data driven’ approach to managing people at work:
The basic premise of the “people analytics” approach is that accurate people management decisions are the most important and impactful decisions that a firm can make. You simply can’t produce superior business results unless your managers are making accurate people management decisions.”
If you don’t agree with the premise and that you don’t see the need for managing people in organizations as needing to be data driven, it’s unlikely you will see this as a wakeup call and feel a need to respond. Ultimately that is every organization’s and HR practitioner’s decision and choice.
If you do decide that this is relevant to you personally as an HR practitioner or as an HR function in an organization, or as an organization in general, then I think there are many things that are conducive to moving in the direction of leveraging analytics to make ‘data driven’ people management decisions.
Here are some thoughts:
- Start reading, researching and staying on top of developments in this area. Understand how this might apply to your specific specialty with in HR if you are a practitioner. Understand how this might apply to your operations if you are an HR leader. Be aware that much of the terminology and ideas are still in flux- and grow as the discipline grows. My own personal sense is that this is still a ‘leading’, ‘bleeding’ edge of HR activity and practice. As such, the definitions and practices are likely to be in flux and evolve over a period of time. What impresses me about the Google example above, is that it is refreshing, exciting and challenging. It is a real life example of actually bringing visibility to ‘data driven’ people decisions. Google will eventually be one of a number of examples as more organizations see the potential and start taking steps in a ‘data driven’ people management direction.
- Take claim to HR analytics as part of the HR domain. This isn’t a situation of ‘no’ decision being made. You make a decision either way- to either see HR analytics as part of HR and taking ownership and control of it, or have the risk of someone else taking ownership of it at some point. (That may or may not be HR). Some organizations make an argument it should be in a Finance area. I personally find that ludicrous. Finance often knows no more about the context of HR than HR does of Finance. Ownership should be in the area that has the domain knowledge. Organizational politics sometimes dictate otherwise. Take claim regardless of where you are in implementation or robustness.
- See Workforce/HR/People Analytics simultaneously as both a separate discipline within HR and also as a core HR knowledge requirement at a basic level for all of HR. Some portions of this might require extensive separate knowledge by a specialized group in HR, and yet at the same some parts require a base understanding by all HR practitioners of what it is, why it is important, and a general sense of how it could/should be operationalized in your specific discipline within HR.
- See your ‘hands on’ use of the technology to do this as both an extension of who you are as an HR professional and as a tool for increasing your competitiveness. Understand that because it is data driven, the hands on use of technology in HR is not optional but rather a requirement. Data driven means interaction with and exploring your data. In seeing HR and IT evolve over the last 3 decades, I have come across many situations where some HR practitioners have seen HR as non-technical, non-quantitative, non-data related. Or in some cases, even when they see the ‘data’ aspects of it, they think if it involves data it’s a non-professional or non-managerial function. I believe this is a wrong view of data and technology. As an HR practitioner at any level, understand that your competitiveness is partly a function of applying technology wherever you can effectively to do what you do better in HR. If you want HR to move into being data driven- technology needs to have hands on use.
- Be smart in your use (or not) of prepackaged vendor analytics software solutions. Don’t assume that if your current HRIS package has an ‘analytics’ feature, that that necessarily is valuable or means anything. Depending on what is provided it may or may not. The concern with ‘pre-packaged’ solutions is that they by their nature presume to know the data driven people decisions that exist and the questions that need to be asked. That may not necessarily be the case. Hands on interaction with your data through statistical tools, with your knowledge of your business and HR issues is much closer to the intent of Workforce/HR/People Analytics.
- Increase your knowledge of statistics and statistical analysis. Understand that to extent that analytics often makes use of and needs to make use of advanced analytical tools, this typically implies statistical tools and statistical analysis. This in turn implies that you have an understanding of statistics and the how to use statistical tools and programs to do advanced analysis. One of the difficulties, I saw over many years is that in business diplomas and degrees, if statistics was taught as part of the curriculum at all, it was usually an elective taught by a science faculty. Often then, the examples how statistical analysis could be used in a relevant way were sketchy at best, because the examples were often directly scientific. For me personally, I did not understand the relevancy of statistics and statistical analysis until it was taught as applied ‘Business’ statistical analysis. Then the applicability of it for use in solving business problems became visible for the first time. ‘Context’ is everything. Statistical analysis is not only relevant but imperative in improving how we do what we do in HR. As HR practitioners, if you don’t already have a background in statistics and the use of statistical packages, this is critical to having People Management decisions being conducive to being data driven. Access to statistical packages these days is no obstacle. The R statistics software package on the internet is free, and is available for installation on Windows, Macintosh and Linux operating systems.
- Possibly change your paradigm of HR. For many HR practitioners, HR is often seen as strictly the set of practices and methodologies used in HR that form the HR function in an organization (a series of silos and a top down orientation). In that paradigm, practices and methodologies are what they are irrespective to any connection to organizational outcomes, and they don’t have to be justified. You often see examples of this on blogs and discussion groups where the merit of a particular approach is touted – but it is done without any discussion of its use being tied to evidence on wider organizational outcomes. What may need to change for some organizations is seeing the entirety of HR in a service process model paradigm. One way of understanding this is to put the ‘vertical’ silos of HR on their side horizontally. If we borrow from the quality improvement world, think of SIPOC ( Suppliers- Inputs-Process-Outputs-Customers) See the entirety of HR silos as really the provision of ‘services’ to customers. To the right are customers. Those customers have expectations of the outputs (services). Those services have processes that exist that allow the services to be provided. The processes in turn have inputs. These would be to the left. The inputs in turn come from suppliers. The processes may or may not be working well. They may not be producing quality service output. The efficacy of any specific HR approach, practice, or methodology is also partly a function of the degree to which organizational performance is enhanced by its use (customers more satisfied with services provided). We then cannot talk about the merits of one approach over another, without also tying it to organizational outcomes. Data driven? –YES.
As I have suggested in the above, I believe Workforce/ HR/ People analytics are still in their early stages of use and terminology in HR. Even with that being the case, what is at the heart of the use and terminology for this is ‘data driven’ decision making. ‘Data driven’ goes beyond simply producing metrics. It is:
- Being able to take a HR issue or question, understand what data exists around and available for that decision, understand what statistical analyses or summaries are useful to answer that question, presenting that data as part of the decision and decision making process
- Understanding for our existing metrics, why we produce them in the first place and what questions they were intended to answer.
- Being able to take overall metrics, measures, and data and be able to slice and dice understand underlying relationships.
- Making a decision as HR professionals to be ‘data driven’. As I mentioned earlier in this article, the ability to generate datasets of HR data and availability of applying statistical tools has been around for at least 35 years. The technologies have changed and have become more robust, and the amount and scope of data has increased over that period of time. The tools and data needed to do this are not necessarily an obstacle.
Google is indeed doing some tremendously exciting things in their People practices. They have taken the bold move to increase dramatically their ability to be ‘data driven’ in their HR practices. And they will likely continue to see payoffs for their decisions.
I guess the key question is- how will Workforce, HR, People Analytics impact you and your organization?