Big Data. How it is Transforming Learning and Talent Development
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1 Big Data How it is Transforming Learning and Talent Development
2 Agenda 1. Big Data Background 2. Big Data in Talent and Learning Analytics 3. Examples and Getting Started
3 Big Data Defined Big Data.. The ability of society to harness information in novel ways to produce useful insights or goods or services of significant value. Source: Mayer-Schonberger, Viktor and Cukier, Kenneth. Big Data. HMH. 2013
4 How is Society Using Big Data? Google searches for flu-like words predicted spread of H1N1 flu virus faster than the CDC The Oakland A s used data to build a team that won 1 st place in the American League West and had a 20 game win streak in 2002 Target Corporation spending patterns knew a girl was pregnant before the girls father knew it Source: Mayer-Schonberger, Viktor and Cukier, Kenneth. Big Data. HMH. 2013
5 What Constitutes Big Data? Element Meaning Example Volume Large amounts of data Wal-Mart collects more data in a day than can fill 20 million filing cabinets. Velocity Variety Value Veracity Speed of collection and processing Range of data types and sources Better decisions with data Reliable and accurate data Location data on mobile phones predicted cars in shopping mall lots to determine holiday sales Smart phone users that contain , text, satellite locations, music, internet sites, etc. Police in Memphis use data to determine where to patrol, reducing crimes by 25% Reasonable data can be reliable. Who Wants to be a Millionaire audience right 91% of time, expert right 65% of time. Source: KnowledgeAdvisors. How Metrics that Matter is a Big Data Solution Source: McAfee, Andrew and Brynjolfsson, Erik. Big Data: The Management Revolution. Harvard Business Review, Oct 2012 Source: Surowiecki, James. The Wisdom of Crowds. Random House,. 2004
6 Big Data is / is not Big Data IS Correlation Prediction More data Estimates Messy data Objectivity Re-use What? Profile Opt Out Big Data is NOT Causation Precision Less data Exactness Clean data Emotion Delete Why? Privacy Opt In
7 Big Data 3 Ingredients 1. Data. Must have data or access to it. 2. Skills. Tools or expertise to mine insights. 3. Mindset. See the potential and unlock value.
8 Big Data 3 Consumers Data Scientists perform the analysis - Preferred Format: raw data, flat files Business Managers daily decisions - Preferred Format: formatted reports Senior Executives strategic decisions - Preferred Format: Dashboards
9 Guru s View on Data In God we trust. All others must bring data. -W. Edwards Deming You can t manage what you don t measure. -Peter Drucker Data-driven decisions are better decisions. It s as simple as that. -Harvard Business Review
10 Big Data in Talent Analytics Element Meaning Example Volume Large amounts of data A government entity analyzes hundreds of thousands of learning evaluations to identify low impact content and revise it. It had 5 years of higher output with no new funds. Velocity Variety Speed of collection and processing Range of data types and sources A strategic 3 day program of a technology company collects feedback on smart phones and data is instantly available to program managers for analysis and change. A federal agency gathered capability data to identify workforce gaps. Financial acumen was rated lowest. L&D created a program on it and recruiting added it to their job profiles. Value Better decisions with data A sales organization collected performance improvement data and saw a 33% variance in performance between regions to displace poor performing management principles. Veracity Reliable and accurate data A statistical analysis calculated an 11.43% performance gain for a marketing team vs. a predictive evaluation calculating an 11.5% performance gain.
11 Key Metrics for Talent Set Goals Monitor & Report Efficiency Effectiveness Outcomes Volume Content Financial Utilization Delivery Operational Investment Learners Workforce Improve Analyze
12 Correlating Data Over Time
13 Onboarding Analytics Example Profile: Large Insurance Company Over 25% Turnover within 1 st 90 Days Key Metrics: Onboarding Effectiveness Quality of Hire New Hire Satisfaction Solution: Automated 30, 60, 90-day new hire touchpoints Targeted reporting to managers & program owners Identified flight risks for early intervention Results: 93% of flight risks retained 73% reduction in measurement costs
14 Learning Analytics Example Profile: Large Business Services Company Multi-Million $ Annual L&D Investment Key Metrics: Program Effectiveness L&D Operation Efficiency Linkage to Business Outcomes Solution: Automated post-class & on-the-job evaluations Monthly imports of business metrics Operational & executive reporting Results: Strengthened partnership with business High ranking on Training Top 125
15 Leadership Analytics Example Profile: Large Technology Company 1000s of new leaders to develop Key Metrics: Bench Strength Leadership Effectiveness Business Outcomes Solution: Semi-Annual 360s of Emerging & New Leaders Leadership Program Evaluation Leadership-to- Business Outcomes Correlation Results: Significant Leadership Effectiveness increase Business Outcomes linked to leadership development
16 Capabilities Analytics Example Profile: Large Biotech Company Improve sales competencies Key Metrics: Certifications Quota Attainment Sales Employee Retention Solution: Annual sales competency assessments: 180s & 360s Global, 15+ languages Correlated competency gains to business outcomes Results: Increased performance for 70% of sales force Increased retention by 8%
17 Engagement Analytics Example Profile: U.S. Government Department High turnover, little insight into drivers Key Metrics: Employee Engagement Employee Retention High Performer Retention Solution: Automated Exit Interview surveys Filtered & ranked by 15 employee demographics Monthly management reporting Results: Identified and addressed key drivers Increased retention by 5.6%
18 Smile Sheet into Smart Sheet Not only evaluate The training but also the process such as onboarding or leadership development or sales effectiveness.
19 Predictive Analytics via Smart Sheet Transaction processing outsourcer Call center problems Training investment significant resources Smart sheets 64% not applied, other priorities Used data to approve manager support coaching After manager support scores rose 20% and customer satisfaction scores increased 5% almost immediately
20 The Cost of Inaction Benchmark Scrap Learning Performance Gain Due to Training Typical Company 50% 9% MTM Client Average 33% 13% MTM Top 25% 18% 28% MTM Top 5% 10% 39%
21 Contact Us John R. Mattox, II, Ph.D
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