BIG DATA and HR. Incompatible?

Transcription

1 BIG DATA and HR Incompatible? Karl Hentschel, Independent Consultant and Trainer Member BICSI, Member PMI, Member IEEE 2016 MCCS Inc CTO HR&ICT 2016, Kingston, Jamaica November, 2016

2 Welcome 2 After several years of hesitation, BIG DATA Analytics is starting to be deployed in many Organizations Primarily in areas deemed mission-critical: Marketing, Sales, Customer Service But what about HR? Current trendline for this discussion: HR is using structured data in its business streams How can this possibly be enhanced by using BIG DATA Analytics?

3 Current State 3 Understanding customer behaviors, tracking marketing and promotional channels, financial forecasting these are all business critical tasks heavily dependent on the collection and thoughtful analysis of data And yet by comparison, HR lags behind In fact, 8 out of 10 practitioners reported in 2015 that they and their leaders continue to use gut-feel to make talent decisions 1 1 Filipkowski, J. (2015). Insightful HR: Integrating Quality Data for Better Talent Decisions. Oracle & HCI.

4 What is BIG DATA? 4 BIG DATA is unstructured information from many sources Data is collected at every point in Life, especially from Social Media, IoT, streaming video platforms, etc. Vastly outnumbers amount of structured data on which we rely on up to now Source: Hitachi Big Data

5 Example of Unstructured Data 5 Source: IBM Big Data Analytics: Disruptive Technologies for Changing the Game

6 Opportunity in BIG DATA 6 Organizational information is typically historical, incomplete and limited to hard facts For a forward-looking perspective (using statistical and predictive modeling) it needs to be enriched with external information Source: EY - Insights on governance, risk and compliance

7 Consensus: BIG DATA is definitely coming to HR 7 Source: Bersin by Deloitte, 2014

8 What would HR like to Know? 8 Do YOU know. What characteristics drive high performing sales people? What work assignments will lead to strong leadership? What attributes of a job candidate will lead to perfect fit? Why retention is low in certain locations and jobs? What is the real result of poor on the job safety? Why some of your top people leave for competitors What compensation and rewards will drive most value? Answers are somewhere in the unstructured data pool!!

9 Case: Large Insurance Company 9 A $33 billion insurance company has developed a behavioral assessment based on a set of beliefs held by their top executives: Top sales people need college degrees from top rated schools, They should have good grades, and They should have experience selling high value products But BIG DATA Analytics proved otherwise Source: Bersin by Deloitte, 2014

10 Case: Large Insurance Company 10 BIG DATA - Results of Data Analysis Input from various sources Using focussed analytics Results - see next slide Source: Bersin by Deloitte, 2014

11 Case: Large Insurance Company 11 Data Analytics showed Six Things mattered: Very Highly Correlated with Success No typos, errors, grammatical mistakes on resume Did not quit school before obtaining some degree Had some experience selling real-estate or autos, or similar Demonstrated success in prior jobs Ability to succeed with vague instruction Experience in planning time and managing lots of tasks Source: Bersin by Deloitte, 2014

12 Case: Large Insurance Company 12 What did NOT matter: Where they went to school What grades they had The quality of their references Source: Bersin by Deloitte, 2014 The Belief System Was Wrong Within six months of implementing a new screening process revenues went up by $4 2 million December 2016

13 Should HR consider BIG DATA Analytics? 13 Most common viewpoint: Harvard Business Review: 71% of CEOs surveyed believe that human capital is the TOP contributing factor to sustainable economic value Increasing pressure for a higher ROI on Human Capital Anywhere from 60-80% of organizatinal budget related to human capital related costs, yet do more with less prevails In a sales driven organization, calculation is relatively easy; gets slightly messy when analyzing non-profit or government agency Game for Big Data and HR has started (TalentSpace(blog) 2015): Not only is Big Data critical on the front end with recruiting, but also during the employee lifecycle Important to use multiple data sets together to determine peak performance and critical competencies Recommend analyzing employee performance data, engagement data, productivity data and movement data (promotions, laterals, etc.) to uncover valuable insights about what keeps an employee engaged and productive

14 So, where to start? 14 In most organizations HR has already considerable amount of data concerning talent, leadership, and skills capabilities The issue is to deliver new breakthrough solutions for your organization Also, many organizations do not have the organizational structure, skills, leadership, and knowledge to use this information yet

15 BIG DATA is BIG 15 As shown earlier, data is coming in unabated: defined in terms of 4 Vs Volume Variety Velocity Veracity Issue is to clearly define analytical objective Source: IBM Big Data Analytics

16 Modelling 16 Given the vast data pool, analytical objectives need to be precise and focused Focus should primarily be on business solutions NOT on HR solutions Requires intuitive analytical skills

17 Four Keys to Success Reliable: 2. Actionable: 3. Scalable: 4. Understandable: Data must be true and validated over time Seasonal changes, organization changes, must be handled Reports must be detailed enough to let managers take action Drill, filter, group data so it is relevant and meaningful Goal is a business-driven dashboard (red/yellow/green) The process of collecting and analyzing data must scale Your outputs must be useful for people at all levels People must be able to visualize and understand what you find Line managers, executives, and employees must use the data

18 Roadmap for Telcos 18 Source: Deloitte: Opportunities in Telecom Sector: Arising from Big Data, 2015

19 CRM and ERP Systems 19 What about CRM and other Human Resource Management Systems? Excellent for data gathering Segregating into appropriate information groupings Placing into appropriate data pools

20 CRM and ERP Systems 20 But, what about analytics? All have analytical modules However, all are cookie-cutter Do not consider that each organization faces unique challenges

21 CRM and ERP Systems 21 Bottom line HR software systems are aging Average HRMS system in large companies today is more than 5 years old and more than half are over 7 years old Enterprise software is considered to become nearly obsolete in seven years New User Interfaces are a top driver for replacement The biggest challenge HR software buyers face is the fear that people won t use the systems Research shows that the #1 driver of change is the need for a more compelling, consumer-like experience Potential use of Big Data Analytics is driving that change

22 Thank you 22 I hope you have some questions during the Panel discussion Karl Hentschel, Independent Consultant and Trainer karlh@modern-concepts.com

23 Source Material 23 IBM Smarter Workforce Institute: Are traditional HR practices keeping your organization average?, 2015 Forbes: 7 Reasons HR Technology Is So Hot Today, 2015 McKinsey & Company: People analytics reveals three things HR may be getting wrong, 2016 Bersin by Deloitte: Big Data in HR, 2014 Forbes Series: Big Data in Human Resources, 2013/14: A World of Haves And Have-Nots, and Talent Analytics (People Analytics) Comes of Age HCI: Analytics for Talent Management, 2016 Tableau: Big Data: Top 9 Trends for karlh@modern-concepts.com