Despite popular belief, internal recruitment teams don’t tend to suffer from a shortage of data. From payroll insights to candidate source information; there’s a great deal of insight that can be gleaned from standard activities to help benchmark your function and inform business decisions.
However, without understanding what data you actually need to collect, interpret and share with the business; it’s easy for a data ‘strategy’ to be purely reactive. This tends to involve the business requesting information on an ad-hoc basis which can result in an inaccurate and inconsistent representation of the function’s performance. It also does nothing to help raise the profile of internal resourcing as a trusted, value-add business partner.
Following a Resourcing Think Tank, run in partnership with AXA, earlier this year we are pleased to share 7 steps that talent acquisition leaders should follow when implementing a compelling recruitment data strategy.
1. Map your key stakeholders
First thing’s first, who needs to be involved in your recruitment data strategy? Make sure you’re talking to the right people from the off; it will save you time in the long run. Whether you’re engaging with Finance, the Board, your recruiters or hiring managers, make sure you’re talking to the business in their language to ensure everyone is bought-in and on the same page.
2. Link your recruitment data strategy to the business’s strategy
Once you’ve identified your stakeholders, it’s important you understand what data they want to see. What does the business want to achieve through a data strategy and what measurements will help your function evidence its value? It’s also important to challenge some of the business’s data requests by asking the ‘so what’ question. For example pushing back and saying ‘okay you want this data, but what are you going to do with it when you have it?’ and ‘how does it tie into the wider strategy?’.
3. Run a data-gap analysis
You should now have answers to both the ‘who’ and ‘what’ questions. The next step is figuring out the ‘how’! Where are you going to get the data from? Start by mapping out your systems (HR, payroll, finance, recruitment etc) to understand what data you already have available. You’ll then need to devise a plan for gathering and recording the remaining data-sets. Perhaps there’s scope for customisation of your existing systems or perhaps you need to enlist the help of a third party to collect and store this intel.
4. Devise a plan for data accuracy
There’s no point implementing a reporting strategy if the data you’re analysing isn’t accurate. It’s crucial that you have a plan for ensuring the ongoing quality of your data. Some organisations perform a monthly audit to ensure data integrity. This might involve analysing a segment of your data to check for indescrepencies or anomalies, correcting these errors and then understanding why they’re there in the first place.
5. Keep it simple
The trap many recruitment professionals fall into when designing a data strategy is over-complicating it. This can cause your stakeholders to switch off and can hamper your chances of success in the long run. Simplification is key. Between 3-4 dashboards that your stakeholders care about is enough. The data has to be digestible for it to be impactful.
6. Define your recruitment data communication strategy
How are you going to present the data back to the business and your key stakeholders? What medium(s) will you use; meetings, presentations, newsletters, online dashboards or portals? And how frequently are you going to share your updates and insights? Whatever communication plan you implement, the dashboards / graphs should tell most of the story without needing too much additional commentary supplied by you.
7. Start small and evolve your data strategy over time
Once the business and your key stakeholders are used to receiving and using the bite-sized data insights you’re sharing, they’re likely to develop a thirst for more. Now’s the time to add trending, averages and data-relationships etc. to your dashboards. Again, start simple and add layers of complexity to your data strategy only when the business is ready.