Author Profile Picture

Jamie Lawrence


Insights Director

Read more about Jamie Lawrence

Interview: Mick Collins, Principal Consultant, SuccessFactors


Mick Collins is the Principal Consultant for Workforce Analytics & Planning at SuccessFactors, an SAP Company. In his role, Mick leads a global team and provides consulting services to multiple clients including Fortune 500 firms in the retail, publishing and consumer products sectors. He has extensive experience in public speaking and regularly participates at some of the most important HR events on the calendar. You can follow Mick on Twitter using the handle @mickcollins.

Read the latest SuccessFactors whitepaper, Six questions to ask before moving core HR into the cloud.

1. What precisely is Big Data and what does it mean for companies?

It is difficult to pinpoint an industry standard definition of “big data” but the two that I most commonly refer to are “huge datasets, ranging to exabytes of data, where the data is ever-increasing in volume; the speed of the data in and out of the data set is increasing in both velocity and volatility; and, the data are increasing in variety” (Bersin & Associates, 2011) and one from my SuccessFactors Workforce Analytics colleague, Marcus Joseph, who sees big data “creating an inflection point where changes in technology – and its application to business problems – enables greater depth of insight based on the combination of disparate data sets.”

Simply put, the ability to mine structured and unstructured data on customers, suppliers, markets, products, and people is a huge competitive advantage for those companies that are equipped to apply these insights to real-time business decisions.

2. Where does the fundamental value lie in HR analytics?

For talent management leaders, HR analytics is a game-changer in how large organizations recruit, deploy, engage, and maximize the productivity of their employees. But more importantly, it offers unbounded potential to correlate investments in people to business results.

I often talk about HR’s role – through the management of their human capital assets – as impacting four principal outcomes: generating revenue for the organization, minimizing expenses, mitigating risks, and executing strategic plans (public sector organizations might replace “generating revenues” with “fulfilling their mission or charter”). HR metrics, such as termination rates, offered in isolation of other datasets, have limited applicability to these outcomes and, consequently, are of limited interest to the C-suite.

Instead, every HR executive wants to know “did the money we spend on Talent Initiative X deliver the intended business results, and how much?” That’s where HR analytics is fundamentally delivering value – more than just “big data”, it’s “better data”.

3. Analytics in the HR function is a new concept for many. What new skills do HR professionals need to effectively utilise this data?

I believe that comfort with the end-to-end HR analytics process is a feature of four core skills:

  • Quantitative Skills: The ability to understand and apply data would seem to be rather obvious, given that the foundation of HR analytics is…numbers. However, statistical knowledge will vary by HR role – analysts might be expected to possess greater skill in pure “number-crunching” whereas HR Business Partners should be confident in understanding how data is managed (in systems), how common metrics are defined via formulas, and possess familiarity with basic quantitative terms, statistics, and methodologies.
  • Business Knowledge: As discussed earlier, HR analytics derives much of its value from the application of data analysis to business issues. In simple terms, this can mean identifying which metrics align most closely with business unit goals or using calculating the financial impact of a human capital initiative. Familiarity with the organization’s strategic plan, revenue and profitability targets, growth strategies, and operating risks increases the likelihood that analytics deliverables mesh with business priorities and therefore address the “so what?” question that frequently derails quantitative analysis.
  • Consulting Skills: Common to most HR transformations that take place today is a commitment to becoming a better business partner. To do so require that HR professionals possess internal consulting skills to facilitate stronger, two-way, conversations with line managers, hypothesize the root-causes of current business problems, leverage HR analytics data to design suitable interventions, and measure the results of those programs.
  • Communication Skills: Applying data to business problems means little if the data cannot be positioned effectively for executive consumption and action. Incorporating visualization techniques (info-graphics, etc.) and storytelling increases the likelihood that analytics-driven messages will be received loud and clear.

4. What’s the first place organisations should look when trying to build analytics capability?

There is an obvious answer to this – look to colleagues from other functions to supplement the talent management expertise already possessed by HR.

For example, seek out peers – or training courses – from Finance and Operations (for quantitative methods), Strategic Planning or Competitive Intelligence (for strategy plans, consulting techniques, and functional frameworks, such as revenue maximization and supply chain management, that can be applied to HR), and Marketing Communications (for storytelling and visualizations).

5. What common mistakes do companies make in either adopting HR analytics or building strategies around HR analytics?

Firstly, to over-reach, promising that analytics will “change the way that HR does business”. Building the capability for analytics takes time, and even the most successful organizations will face hurdles – apathy, competing priorities, insufficient technology – along the way. It is important to have a clear, and realistic, vision of how HR analytics can have the greatest impact on specific leverage points – those talent decisions where data-driven insights are most crucial. Trying to apply analytics to every HR activity just isn’t feasible.

Secondly, to assume that “if you build it, they will come” – that by offering HR metrics and analytics to line managers, they will login to a new application, or take time to review the findings. HR analytics is often about winning hearts and minds; be thoughtful about which audiences will have access to the analysis and why/how they will use it, and identify both formal stakeholders and informal champions to support your cause.

6. Proving the value of HR analytics remains a challenge – how should HR go about building a business case for the board?

In my experience, the business case for HR analytics has tended to default to financial calculations of the Return on Investment (ROI), especially when evaluating technology options. This is necessary but insufficient. Instead, start more broadly with assessments of the biggest talent challenges/leverage points your organization faces – now, and in the next 5 years – and how a capability for HR analytics and/or strategic workforce planning might resolve them. For example, if analytics can correlate investments in training to the adoption of critical skills to support a new business model or process and demonstrate the revenue opportunity associated with that model, you have the makings of a solid business case.

7. Is ‘data-driven’ reflective of a certain workplace culture (e.g. transparent, evidence-based) or does the data come first, and then moulds the culture?

The key difference for me is the maturity of the organization. In larger, more mature, firms where the culture is based on many years of accumulated experience, opportunities for culture shifts may be limited. As such, if the organization is not one that values data-driven decision-making, it will be hard to change that paradigm. Immature firms are not necessarily beholden to an existing set of cultural norms and, therefore, may be more responsive to the use of data, especially if it proves to be of competitive advantage.

8. How will the injection of analytics capability into HR affect HR’s relationship with other key functions e.g. marketing or finance?

As I mentioned above, HR can draw on the experience of colleagues across other functions, such as marketing and finance, when building its own analytics capability. I believe that this can only strengthen their relationships, with HR taking a more active role in integrated decision-making processes (ones where talent decisions are on par with product, market, or investment choices). This isn’t the norm today, but could be an exciting vision of the future.

9. What will the HR function look like in five years? Will it be staffed by scientists?

There is no doubt in my mind that scientists will become a staple of HR functions that buy into the notion of an evidence-based organization where data becomes readily accepted, and acted upon; we are seeing that today in organizations where leaders with non-HR backgrounds are being recruited from data-intensive functions and bringing a commitment to analytics with them.

Also, I think that we’ll see more of the “networked HR organization”. For example, the concept of HR analytics data being closely guarded and available only to a small minority of HR staff will change; crowd-sourcing tools such as corporate social networks will be used to disseminate non-sensitive data in order to speed decision-making on the front lines.

Overall, it is an exciting time for HR professionals, for whom a competency in HR analytics is extremely powerful and desirable. 

Author Profile Picture
Jamie Lawrence

Insights Director

Read more from Jamie Lawrence

Get the latest from HRZone.

Subscribe to expert insights on how to create a better workplace for both your business and its people.


Thank you.