3. Big Data and Human Resources
Have you felt these thoughts?
It is a math thing, I am not a
math major
We tried that and it did not
work
It is too complex for most
organizations
That is just not the way we
do things around here
February 2, 2015
4. Big Data and Human Resources
CORRELATION
VS. CAUSES
WHEN VS. WHY
February 2, 2015
5. February 2, 2015
Which is more
important?
Being able to know
when an event is
going to happen or
why it happened?
6. Big Data and Human Resources
Things one can do at a
large scale
Things that cannot be done
at a smaller scale
To extract new insights
February 2, 2015
7. Big Data and Human Resources
CORRELATION
February 2, 2015
8. Big Data and Human Resources
Big Data Tools
Predictive Analysis
Descriptive Analysis
Data Mining
Competency Analysis
Surveys
Business Analytics
Strategic Analytics
February 2, 2015
9. Big Data and Human Resources
CAUSES
February 2, 2015
10. Big Data and Human Resources
Your responsibility as a HR professional
Find the right person for the right job in the right place at
the right time
To ensure that the human capital methods, policies and
procedures are
Strategic in nature
Aligned with the corporate mantra, vision and mission
Be innovative
February 2, 2015
11. Big Data – Here is What We Do Know
“Six Sigma : The Breakthrough Management
Strategy Revolutionizing the World’s Top
Corporations” by Mikel and Schroeder
We Don’t Know What We Don’t Know
We Can’t Act on What We Don’t Know
We Won’t Know Until We Search
We Won’t Search for What We Don’t Question
We Don’t Question What We Don’t Measure
February 2, 2015
12. Big Data – Here is What We Do Know
“There are data points which make sense for us
as HR professionals
Time to hire
Cost of hire
Cost of failed hire
Absence Rate
Turn over rate
We Don’t Question What We Don’t Measure
February 2, 2015
13. Big Data and Human Resources
February 2, 2015
Why do I need these
data points?
14. Big Data and Human Resources
February 2, 2015
If you have the data you
have
defined the problem and
you have measured the
problem resulting in data
points
15. Big Data and Human Resources
Innovation doesn’t have to be about creating the light bulb or
telegraph. Innovation can be very important small changes to
something that is already working. That is the stuff that is
overlooked and it can take things to the next level.
David Steinberg CEO XL Marketing May 2013
February 2, 2015
16. The TLS Continuum
February 2, 2015Associates, Inc,
16
•Six Sigma
• Lean • Theory of
Constraints
• Ensures that all your
processes are
repeatable
• Creation of a standard
of work
•Removes waste from
the process
•Identifies the non-
value added
activities that are
creating the obstacle
• Removes these
steps from the
process.
•Identifies the
source(s) of
roadblocks in your
processes
17. Big Data and Human Resources
"We have learned to live in a world of mistakes and
defective products as if they were necessary to life. It is
time to adopt a new philosophy in America."
Dr. Edward Deming
February 2, 2015
18. TLS Continuum – Customer Centric
Go and See
Focus on the process
Do it now
Gain knowledge
February 2, 2015
19. TLS Continuum – Alignment
Change managers to
leaders
Transformational
leaders
Educate and Train
Breakdown silos
Avoid quotas
Coach
February 2, 2015
20. TLS Continuum – Continuous Improvement
Long term planning to
optimize services
Always a better way
Poka Yoke
Drive out fear
February 2, 2015
TLS Continuum
Remove Waste
Standard Work
21. February 2, 2015
How does this {process, procedure,
action, initiative, project, policy}
help the organization achieve its
business objective?|
If you can’t answer this in a clear way that is
measureable and where there is evidence that your
answer is true, stop doing it.
Ask your self?
23. Achieving HR Excellence
February 2, 2015Associates, Inc,
23
Customer Centric
Perspective
Quality
Improvement
Organizational
Alignment
Commitment to
meeting or exceeding
the customer needs
based on Voice of the
Customer
Better
Cheaper
Faster
Everything we do
must be centered
around moving
the business
enterprise
forward
strategically
24. Benefits to Your Organization
Reduction of defects
Lower costs
Higher customer satisfaction
Shorter cycle time
Predictable processes
Culture change
Focus on quality, the customer and doing it right
Pride in being the best
Standardization for problem solving
Highly trained workforce
Common language
February 2, 2015
26. February 2, 2015
THANK YOU
• It has been my pleasure to
speak to your organization
today
• Go forward and be
• focused, flexible and fast within
your organizations
• Embrace the changes that will
grow your organization
27. More Information?
Daniel Bloom
SPHR, Six Sigma Black Belt
Chief Executive Officer
Daniel Bloom &Associates, Inc.
PO Box 1233
Largo, FL 33779
(727) 581-6216
dan@dbaiconsulting.com
http://www.dbaiconsulting.com
Editor's Notes
Almost every issue of the HR professional journals contain some article pertaining to ‘Big Data” It evokes a wide range of emotions. There is a lot we know there is a lot we don’t know.
. When you hear someone throwing the term big data around are these your thoughts?
The image in front of you is a mixed up collection of the sources of big data that affect our organizations. Viktor Mayer-Schonberger and Kenneth Cukier define for us what Big Data is in their book Big Data: A Revolution that will change how we live, work and think. They tell us that big data refers to things one can do with more data instead of less data that creates new insights and value
Further it gives us a new glimpse at the world around us.
The idea is that we can identify events and describe why they occur when they do. Turn to your marketing department.
Predictive Analysis is a set of tools that supposedly allows the organization to predict the future. Take for example the retail store which through the tools on the previous slide gains an insight into what demographic is most likely to buy a certain product. In HR you could use the tools to understand why managers make failed hires over time.
However I would contend that within the HR arena Big Data is beyond the requirements to resolve our HR issues
As the human capital manager of your organization you have a very important and critical role in the future of the organization.
One of the barriers to discovering the problems are clearly defined by Dr. Mikel Harry in the book listed on the screen. Consider these issues prevalent in almost every organization. Do they affect your workplace?
Each of these create what we might call little data. So what do you do with this data?
In many organizations we have gone from what happened to what is happening to what is likely to happen. We further want to find the reasoning behind the events as they unfold.
The other question is do you need the immense data points
Big data has its place within the organization, The goal is to use the right tool for the right job. At this precise moment in time Big Data is probably not the right tool for you to develop the metrics and analytics to do what is expected of you in HR
Therefore you have two of the five stages completed.. To complete the process you need to take your data analyze its affects, improve how you operate and make sure it become the new normal
The important point is described by David Steinberg. It is not necessarily large changes in processes that yield successful change
Let me suggest a different perspective which is embedded in the six sigma methodology which refer to as the TLS Continuum.
We need to change our philosophy in order to be sustainable
There are 3 pillars to the implementation of the change in culture within your organization, beginning with the voice of the customer.
The second pillar is the corporate culture
Final pillar is the continued process improvement– the reason why our journey never ends
Have you asked yourself this question before beginning a process?
Let me suggest a different perspective which is embedded in the six sigma methodology which refer to as the TLS Continuum.
Think about this quote from the author TS Eliot for a moment. We may collect this vast array of data points but where is the wisdom to know how to resolve our issues. In addition is there ever too much data to the point that we have so much data that the reason for the data collection is lost in the process