More Than 100 Days: The Realistic Analytics Journey
A recent report from the IBM Smarter Workforce Institute, “Starting the Workforce Analytics Journey: The First 100 Days,” detailed a 10 step process of how to take 100 days to set up an analytics-enabled HR function.
In reality, it’s how to take 100 days to plan your Workforce Analytics Journey.
Here is the timing of their 100 days:
0-30 days: Setting your direction
- Articulate your objectives
- Define your governance model
- Get a quick win (although it says to do this within 100 days)
30-60 days: Defining your approach
- Know your data
- Know your technology options
- Know your partner options
60- 90 days: Growing your capability
- Identify roles and responsibilities
- Complete your business plan
- Build momentum
Beyond 90 days: Implementation
Why We Shouldn’t Randomly Pick 100 Days
According to Bersin by Deloitte, it typically takes one to two years for a company to build an HR analytics team. In my experience, Bersin’s estimate is accurate and in some cases, optimistic. I have seen it take longer in companies whose data quality is so poor that they have to take a step back to address their data before they can move forward. Most companies that only have a few data quality issues can build this function within two years.
For some companies whose data is fairly accurate, they may have a distrusting culture which will make their journey longer. The distrust I mention is a distrust of HR, its analytical capabilities and its data. It happens more than you think. The quickest solution to this one is sometimes to move the analytical portion of HR out of HR and to merge it with analytics in Finance or Operations.
As an example, suppose you present a chart that says you have 7800 employees. Further in your presentation, you show age distributions which show 7752 employees. In a distrusting culture, the HR Analytics team will always have to explain the missing 48 employees.
Is this a data issue? In this case, no. This company has employees in European companies where privacy laws mean that employees do not have to provide their ages, etc. While the data is entirely accurate, the company culture means that the analytics team has to spend extra time to explain discrepancies that we data folks dismiss as a normal (and valid) occurrence. As another example, we could pull one data set today, another tomorrow and our reports won’t match since employees come and go from the roster.
IBM selected 100 days since some companies give senior level executives 100 days to show impact, or at least to have a plan to do so. While some analytics leaders are in the senior ranks, most are not. The selection of 100 days seems entirely arbitrary.
A Better Way
I think there’s a better way to plan your HR Analytics function with a method that will be better customized to your company’s needs, especially for the vast number of companies that have smaller HR teams. As many of my readers know, I am a former mathematician and engineer. With that, comes a mindset of a more practical nature and the urgency to get things done.
Here are the basics of my approach.
- Where are we today?
- Where do we want to be in the future and by when?
- How will we get there?
Where Are We Today?
To an engineer, implementing HR analytics is an improvement project and with all such projects, we begin by assessing the current state. It’s good to look at a typical HR Analytics road map when you do this.
- Are we primarily in the reporting stage?
- Do we already have good data governance?
- What are the skill sets we have access to today? Where are these skill sets?
- Which tools do we already have inside our company that we can leverage?
- Do our internal customers trust our data? Do they trust us?
These are just a few of many questions you can ask in your self-assessment. Some of these questions are useful in preventing you from spending money on new tools / skills when you may have them already, even if they are in another area of the company. You shouldn’t select tools until you know the business questions you need to answer (In the next step).
Where Do We Want to Be in the Future and By When?
Next, we need to determine our desired future state(s). Here are a few sample questions:
- What are the urgent business questions that we are not answering today?
- What skills and tools are needed to assess those problems?
For the future state, it is often good to seek opinions outside of your company as to what is possible with HR Analytics. I have had experience with companies who cannot envision the higher end of analytics enough to be able to know if it will be of value to them. I’ve seen more than one company consider themselves “done” in HR Analytics as soon as they create a metrics dashboard. To them, this was HR analytics. Speak to other analytics leaders who have travelled the road before you, network at conference events and research online articles of how others have used HR analytics to benefit their company.
In reality, you may have multiple future states. You may have a description of where you would like to be in 1 year and another in 3 years.
How Will We Get There?
Only when the desired future state is known, can you begin to plan your specific road map of how to get there and the associated timing.
- Are your most urgent business questions in the category of predictive analytics or can they be answered with visualization tools?
- What are your greatest barriers to moving forward?
- What are the gaps we need to close?
- What skills do we need when?
The above questions are just a few but they allow you to prioritize items like the skills you need and the types of tools that go with those skills. It also allows you to avoid hiring skill sets that you won’t need for another year. Some companies have hired statistical skills only to discover that they won’t need statistical analyses for at least another year. Their priorities are currently elsewhere in the analytical spectrum.
Realistically, getting to a firm plan may take you more than 100 days to establish, present, and get approved before you can move forward. That’s ok. It depends on where you are today and your company culture. It takes a lot of research, communication and relationship building to gather the information you need to form your plan.
Until next time,
Tracey is one of the “Top 50 Global Influencers in HR Analytics” and presents at conferences in the U.S., Canada and the U.K., primarily on the topics of analytics, continuous improvement and Strategic Workforce Planning. She holds degrees in Mathematics, Engineering and Business and has over 25 years of experience in the areas of Human Resources, Supply Chain and Engineering. She is the author of “Strategic Workforce Planning: Guidance & Back-up Plans” and “HR Analytics: The What, Why and How.”
You can find Tracey on the web at: www.numericalinsights.com
“NI Magazine: Numerical Insights for HR”
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