30 09 2014
door Inostix

The HR Analytics Journey at Sears Holdings: interview with Ian O’Keefe

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Picture: The famous Sears Towers

In one of the active HR Analytics Linkedin Groups, we ‘met’ with Ian O’Keefe, Head of Talent Analytics and HR Reporting at Sears Holdings Corporation (headquartered in Hoffman Estates near Chicago, US). Curious as we are, we asked Ian for an interview and present to us the Sears HR Analytics general framework and to give us some insights in the roots of the HR Analytics function at Sears, an overview of several analytical projects, the required expertise for HR Analytics and his personal advice to HR professionals on how to start with HR Analytics. It has evolved in a great interview and we are delighted to be able to present Ian on the iNostix blog. Thanks a lot for your kind support, Ian! Here we go with the interview…

 

 

Ian, can you introduce yourself please?

Ian new pic

Picture: Ian O’Keefe

I am a Business Transformation and Analytics leader with 15 years of experience leading global initiatives and delivering analytic insights to Fortune 100 organizations. In June of 2013, I joined Sears Holdings Corporation as the Head of Talent Analytics & HR Reporting. I began my career as a management consultant with Deloitte’s Human Capital practice and then joined a boutique org effectiveness consultancy in the Omnicom Group, before going on to establish my own practice. After 10 years of management consulting, I joined American Express and split 5 years between Global Human Resources as well as Global Business Transformation.

I’ve worked across a variety of business settings, industry verticals, and have functional experience in Human Resources, Operations, Finance, Procurement, Technology, Marketing, and Sales. Over the years, my work has covered qualitative and quantitative analytics, organizational effectiveness, business process re-engineering, systems implementation, cost take-out, corporate restructuring, change management, and project management. So my organizational perspective tends to be fairly broad and end-to-end. I have a BA in Psychology from the University of Virginia and am currently pursuing a MSc in Predictive Analytics from Northwestern University.

When and why did you start working with HR analytics?

I have always been interested in human dynamics and the intersection of people, process, and technology within corporations. And I’ve always felt that HR as a function and a provider of services could do more to quantify value added to the organization, to help people succeed, and to drive better business outcomes. So when I got the call in early 2013 from Sears Holdings Corporation and learned about HR Analytics within the context of an enterprise-wide transformation, I saw an opportunity to bring all my prior experiences together in a new and innovative way. I jumped at the chance.

What is your focus with HR Analytics at Sears and why?

I’m fortunate to lead a very talented team that can work up and down the entire analytics value chain. We handle everything from processing thousands of ad hoc operational reporting requests per year to delivering a small number of high-impact advanced analytic initiatives. Our work covers a workforce of over 220,000 employees and billions in annual labor spend. One of the most important things we do every day is to make sure our HR Business Partners and Line Leaders have the workforce data and talent insights they need to make decisions that make a difference. We do this through a number of reports, dashboards, scorecards, and self-service tools of which you can see an overview below in the People Dashboard.

Is there a difference in the approach between the holding and the local level? 

Yes, as you can see in the dashboard below, there’s one People Dashboard for the entire company. At Step 3 though, each business unit tailors their own People Dashboard to their needs.

 

Slide1

 

During our first chat, you also talked about your portfolio prioritisation approach.

Yes, correct. The other critical piece is our portfolio of strategic initiatives, which we prioritize and score according to:

  • enterprise-wide impact and
  • data complexity/maturity (see below in the portfolio prioritisation chart).

Lately, we have been looking into predictive attrition factors among our top talent segments, patterns in engagement data and leadership layers, as well as the relationship between internal social media usage, talent outcomes and business metrics.

 

Slide2

 

Any HR or Business results you were able to achieve with HR analytics?

Our team has done deep analysis to help the enterprise upgrade talent pools and realize stronger ROI from specific talent segments. Here are a few examples:

  • Drive decision making: One example is how we have systematically honed our monthly “people dashboard” to include metrics that drive measurable decision-making by our HR Business Partners and BU Leaders (especially decisions that impact under-performing talent segments).
  • Predictive drivers of attrition: Another example is how we have used logistic regression models to understand predictive drivers of attrition (especially among top-performing talent segments). Both these examples allow HR and Business Leaders to make evidence-based decisions that drive down costs and also guide the reallocation of significant amounts of annual labor spend to generate a better return on our talent investments. (see here for 4 predictive attrition articles on our blog)
  • Relationship between mood and sales: A business-specific example is how we have analyzed the relationship between Associate daily mood responses (over 30M responses over the past year) and key sales performance indicators at our 2,000 Sears and Kmart stores. We’ve learned a lot about the aggregate mood in our stores and across our national footprint…frequency of specific mood responses, fairly consistent movement patterns of positive moods and negative moods, specific days of the week and events that trigger mood spikes, and mood clusters of our stores over time. The biggest insights so far have been the small but significant relationships that exist between mood mix and incremental sales metrics. Everyone knows how much mood matters on a personal level. But we’re excited to find statistical evidence that mood matters for business outcomes too.

What do you see as next steps using HR analytics?

At the end of the day, it’s all about getting better business outcomes. When the single largest expense line in most organizations is Labor, and more and more signals are surfacing on what really drives workforce productivity, I think it’s only a matter of time until HR Analytics becomes an extreme value creator and innovation engine for the enterprise. To do this, as an immediate next step, we need to continue to keep an enterprise-wide perspective and blend “people” data with data from other business processes and functions like Sales, Marketing, Customer Satisfaction, Risk, Operations, Supply Chain, IT, and others.

Many of these functions have already embraced decision science and advanced analytics to allocate resources, prioritize investments, and predict opportunities to create measurable value for the organization. Longer term, as the discipline of HR Analytics matures, I think we’ll begin to see capabilities like machine learning, natural language processing, and cognitive computing become part of the HR Analytics roadmap – and HR specialist skillset – at more organizations.

What would you change if you had to start again?

I know this will sound canned… but, I really wish I had gotten into this field earlier! Granted, in many ways HR Analytics is still in its infancy. But, the field is evolving so quickly. Not a day goes by that you don’t read about a new breakthrough in data science, BI capabilities, sensors, robotics, quantification of self, neuropsychology, wellness, engagement, leadership. It’s an exciting time to be in HR Analytics, because principles from so many of these previously walled-off domains are beginning to combine and shape the future of our craft.

What advice would you have for HR professionals who are planning to start with HR analytics?

HR Analytics is a blend of disciplines that historically haven’t been grouped together. The Analytics & Reporting team at Sears has depth in Economics, Statistics, Psychology, Computer Science, and Management Consulting. So my advice to those who are interested in pursuing HR Analytics would be to:

  1. seek out unconventional (for HR) skills and backgrounds steeped in data (i.e., quants)
  2. learn the technical skills/tools involved in manipulating and drawing inference from data
  3. keep an enterprise-wide perspective and augment your existing HR function knowledge
  4. adopt a change-agent mindset and start asking more “what if” and “why” questions
  5. start small, keep it simple, and build momentum by always linking to business results

Thanks a lot, Ian, for this great interview! 

Related interviews:

Interested in using predictive HR analytics as a key component in your HR strategy? Get in touch with CEO and co-founder Luk Smeyers for more information ([email protected]) or via Google+. Or follow iNostix on Twitter and/or Facebook for exciting international articles on HR analytics.

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