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An Introduction

1
HUMAN CAPITAL

71%

CUSTOMER RELATIONSHIPS

66%

PRODUCTS/SERVICES INNOVATION

52%

BRAND(S)

43%

BUSINESS MODEL INNOVATI...
3
4
The CEO asks for the financial impact of HR activities and HR-related
decisions. HR wants to become more of a business par...
Phase 1:
Opinions
Opinions
predominate.
Decisions
based on gut
feeling and
experience

Phase 2:
Raw data
There is
(structu...
Cut costs, not
capacities

Maximilize
productivity,
customer
satisfaction and
financial results

Inspire

Reach

Maintain
...
Revenue

Reputation/
image

Retainment

Staff
satisfaction/
Involvement

Customer
satisfaction

Work
environment
Staff beh...
Predictions
Causes

What happens?
Correlations

Why does it happen?
What could happen?
What if…?

Indicators

Matureness o...
A data-driven approach to make better decisions on
the human side of an organization
A continuous process of converting st...
Insights
Analysis
Data:
Collecting data from
internal and external
sources, and market
research

11

Statistic and
predict...
Some examples…

12
1. Analysis of internal data showed that great managers are
essential for top performance and retention. Combination
with ...
14

Are you currently measuring
this?
Percentage of employees still working at the company
after 12 months

Nearly engaged

Not engaged

What’s the situation in...
Performance is influenced by:

Staff turnover is influenced by :

1. Appreciation, trust and recognition

1. Personal deve...
• "Our call center employs almost one hundred people. Despite the
attention to recruitment en training we noticed a great ...
Classic analysis

HR analytics

Absence%

What is the impact of absence on
customer satisfaction, quality,
productivity an...
One business unit outperforms
the other on employee
satisfaction.

We expect a problem in
recruiting the right talent in t...
Cost reduction. How can we best restructure the organization so we have lower
costs, but without loss of skills and still ...
From (RAW) DATA TO METRICS AND ANALYTICS

21
Problem/
Question

Understand
the business
question
Create the
hypothesis
and concept
analysis tree

22

Data

Analysis

I...
Cut costs, not
capacities

Maximilize
productivity,
customer
satisfaction and
financial results

Inspire

Reach

Maintain
...
Assessment
Performance/development/
training

IQ/Competencies/
skills
Absence
(holiday/
sickness)

Work-life
balance
Emplo...
Focus: start with a business question, not with the data!
What data is needed to answer the question? First data clarified...
Clarify data, connect and/or create
Solution: cooperation between suppliers, IT, HR and data analyst. Start
with simple du...
Predictive
Explanatory
Descriptive
average, median,
frequency, standard
deviation, trends

27

cross-tabs, buttons,
analys...
It’s not enough to be right, you have to
be proven right!

Pay attention to the last step: reporting your
findings!

28
29
Get to it!

30
AnalitiQs gives organisations the
knowledge and insight needed to make
better decisions and take action. Pitfalls
are avoi...
32
33
"A good hockey player plays
where the puck is. A great
hockey player plays where
the puck is going to be.“
Wayne Gretzky

...
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Workforce analytics, an introduction

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Workforce analytics, also called HR analytics or people analytics is getting much attention lately. And rightly so! Research has shown that companies using data to drive their decisions and actions are more succesfull than others. With (predictive) analytics an accurate view of the future requires predictions based on data rather than personal hunches or speculation.

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Transcript of "Workforce analytics, an introduction"

  1. 1. An Introduction 1
  2. 2. HUMAN CAPITAL 71% CUSTOMER RELATIONSHIPS 66% PRODUCTS/SERVICES INNOVATION 52% BRAND(S) 43% BUSINESS MODEL INNOVATION 33% TECHNOLOGY 30% PARTNERSHIP NETWORKS 28% DATA ACCESS/DATA-DRIVEN INSIGHTS 25% R&D/INTELLECTUAL PROPERTY 22% PRICE/REVENU INNOVATION 19% ASSETS (PHYSICAL INFRASTRUCTURE) 15% CORPORATE SOCIAL RESPONSIBILITY ACCESS TO RAW MATERIALS 2 13% 8% Source: IBM CEO survey 2012
  3. 3. 3
  4. 4. 4
  5. 5. The CEO asks for the financial impact of HR activities and HR-related decisions. HR wants to become more of a business partner Recession leads to reviewing costs as well as the largest balance/expense: people! On the other hand: scarcity of deployable and suitable workforce asks for more and different insight. There is a lot of data available! 5
  6. 6. Phase 1: Opinions Opinions predominate. Decisions based on gut feeling and experience Phase 2: Raw data There is (structured) data, but very raw and hard to process Describe 6 HR Intelligence Phase 3: Phase 4: Metrics Analytics Ratios and control numbers are measured. But metrics make people numb and /or raise questions explain Insights: with the help of analysis, relationships are defined, trends and special populations are identified predict Phase 5: Datadriven Insights are consistently used to make decisions, start actions and change processes
  7. 7. Cut costs, not capacities Maximilize productivity, customer satisfaction and financial results Inspire Reach Maintain Build a flexible organisation Business-economic aspect 7 Recrute Develop HR aspect
  8. 8. Revenue Reputation/ image Retainment Staff satisfaction/ Involvement Customer satisfaction Work environment Staff behaviour Policy, Culture, Leadership and Management Products, Means, Processes and Communication 8 Customers Loyalty
  9. 9. Predictions Causes What happens? Correlations Why does it happen? What could happen? What if…? Indicators Matureness of HR analytics 9 Source: Boudreau/Ramstad, Beyond HR, 2007
  10. 10. A data-driven approach to make better decisions on the human side of an organization A continuous process of converting staff-, customer-, market- and business information to actions Requires a mix of knowledge, skills and technology, tools and techniques, varying from relatively simple reporting of HR ratios and KPI’s to, complex, predictive analytics Supports faster and better decision making “Turning Data into Profit” 10
  11. 11. Insights Analysis Data: Collecting data from internal and external sources, and market research 11 Statistic and predictive analysis: describe, explain, predict Converging and processing analysis results to true insight and actions
  12. 12. Some examples… 12
  13. 13. 1. Analysis of internal data showed that great managers are essential for top performance and retention. Combination with research further identified the eight characteristics of great leaders. HR analytics is considered to provide a competitive advantage 2. Google developed a mathematical algorithm to proactively and successfully predict which employees are most likely to become a retention problem. This approach allows management to act before it’s too late and it further allows retention solutions to be personalized. 3. Within the PiLab Google conducts applied experiments to determine the most effective approaches for managing people and maintaining a productive environment. The lab e.g. improved employee health by reducing the calorie intake of its employees at their eating facilities by relying on scientific data and experiments (by simply reducing the size of the plates). Is your company ready for this? 13
  14. 14. 14 Are you currently measuring this?
  15. 15. Percentage of employees still working at the company after 12 months Nearly engaged Not engaged What’s the situation in your company? 15
  16. 16. Performance is influenced by: Staff turnover is influenced by : 1. Appreciation, trust and recognition 1. Personal development 2. Daily activities 2. Daily activities 3. Manager 3. Appreciation, trust and recognition 4. Etc. 4. Etc. What does your company focus on? 16
  17. 17. • "Our call center employs almost one hundred people. Despite the attention to recruitment en training we noticed a great turnover in personnel, which costs an unnecessary amount of time and money. Nowadays we don’t only use personality tests and background questions to direct our interviews, but to predict if candidates will be able to keep doing the job to satisfaction and if they are “keepers”. This way we can limit the number of interviews we have to conduct and decrease the turnover in personnel (and with this recruitment costs). Thanks to HR analytics." Recruitment 10%-30% less recruitment costs, that is desirable to you? 17
  18. 18. Classic analysis HR analytics Absence% What is the impact of absence on customer satisfaction, quality, productivity and revenue? What causes absence? What impact do managers have on absence? What impact do workload, engagement and/or the customer have on absence? Absence per department Absence costs Reasons for absence Frequency and duration 18 What do you know about absence in your organisation?
  19. 19. One business unit outperforms the other on employee satisfaction. We expect a problem in recruiting the right talent in the future. • What is/makes the right talent? And what should a talent look like in five years? • What do the talents of the future want? And how can I reach them? • What is the impact of talent on our results? 35% of our personnel continues to grow within the organisation. 19 • What is the relationship between managerial / leadership style / behavior and scoring higher on employee engagement? • What other aspects influence the satisfaction score? • Why does this 35% continue to grow, while others don’t? And what is the financial impact of the 35% that develop? • How successful are the 35% that are internally promoted compared to personnel being attracted externally? Do you know the strength and direction of these relationships?
  20. 20. Cost reduction. How can we best restructure the organization so we have lower costs, but without loss of skills and still manage to keep the staff engaged? Continuity. How do I insure growth and continuity within the organization? So I will still have the right people three years from now. What will my structure and employability look like in three years according to my current staff turnover and absence? Customer satisfaction. How do we increase customer satisfaction by means of (a change in) our staff? How does employee satisfaction influence customer satisfaction in our organization? 20 What is your main business question?
  21. 21. From (RAW) DATA TO METRICS AND ANALYTICS 21
  22. 22. Problem/ Question Understand the business question Create the hypothesis and concept analysis tree 22 Data Analysis Insights Look for data sources, define and/or create Collect data Cleansing and enhancement Run analysis Review analysis tree Combine and translate analysis results to real insights and actions Presenting Reporting (Action) Effective reporting and visualization of results
  23. 23. Cut costs, not capacities Maximilize productivity, customer satisfaction and financial results Inspire Reach Maintain Build a flexible organisation Business-economic aspect 23 Recrute Develop HR aspect
  24. 24. Assessment Performance/development/ training IQ/Competencies/ skills Absence (holiday/ sickness) Work-life balance Employee/ contractor/ temp Position/ grade/ role/ contract Personality / drives Company Leadership / culture Means, cooperation and communicati on Reputation Strategy/ products/ services Colleagues team / other Remuneration/ recognition 24 Candidate Finance (salary/ cost/ revenue) Manager Satisfaction / engagement Commute Vacancies Customer satisfaction
  25. 25. Focus: start with a business question, not with the data! What data is needed to answer the question? First data clarified? Get to it with analytics! Then add data step by step. Consider privacy! How/which data can be integrated maintaining privacy? Choose: data from system or research? Manage data warehouses internally of externally? Start simple, with a proof of concept! Advantages: get to know the data, first analysis/report completed quickly, create acceptance. Improve processes & data based on analysis. Don’t try to automate everything (immediately)! Manual steps are okay! Is all the data present in systems? Or in Excel files, etc.? Does building an interface stack up to monthly downloading data? 25
  26. 26. Clarify data, connect and/or create Solution: cooperation between suppliers, IT, HR and data analyst. Start with simple dump for 'exploration', then improve further (make formats, exports and/or ‘direct’ clarification) Data cleansing Solution: collaboration between HR, ‘the floor' and data analyst. Offer partial lists for clean up. Discuss processes and improve. Alternating (reporting / analysis) desires Solution: stepwise approach, Start with standard, delivery every two weeks and, adjust if needed. Shared budget responsibility. 26
  27. 27. Predictive Explanatory Descriptive average, median, frequency, standard deviation, trends 27 cross-tabs, buttons, analysis of variance, percentiles, pareto analysis Cluster analysis, correlation, regression, discriminant, factor, CHAID, neural network, associative techniques, etc.
  28. 28. It’s not enough to be right, you have to be proven right! Pay attention to the last step: reporting your findings! 28
  29. 29. 29
  30. 30. Get to it! 30
  31. 31. AnalitiQs gives organisations the knowledge and insight needed to make better decisions and take action. Pitfalls are avoided by our experience and expertise, which is fuelled by examples provided by other companies. Our approach is branded by passion and results. A combination of strategic thinking and hands-on implementation is our preferred way of working. We are naturals in collecting, organising, structuring and analysing data. One of our other focal points is the transfer of knowledge and improving the professionalism of staff and line managers, so that the customer will be self sufficient in the future! 31 • HR-Intelligence Audit, including an action plan to implement or improve HR analytics. • AnalitiQs’ HR Reporting as a Service: clear, comprehensible information rapidly available in reports and dashboards. And all of this in a secure fashion for an attractive monthly fee. • Full or partial handling of reporting (including warehouse data) and analytic projects. • Full or partial handling of (market) research projects. • Training and coaching in HR analytics: to expand internal capacity. • Full or partial handling of staff research.
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  34. 34. "A good hockey player plays where the puck is. A great hockey player plays where the puck is going to be.“ Wayne Gretzky 34 Any question? info@analitiqs.com Tel: +31 75 20 22 603

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