This document discusses how analyzing different types of data can provide insights to improve business performance. It explains that big data is characterized by variety, velocity, and volume. Examples are given of the large amounts of daily data from sources like social media, aircraft flights, the stock exchange, and sky surveys. The document advocates linking learning and business data using analytics to generate actionable insights. It also discusses how the xAPI standard could integrate more sources of informal learning data and provide more valuable data insights.

1. Making Sense of
Your Data
Andy Wooler, Academy Technology Manager
April 4th 2014

2.  To materially improve business performance:
‒ Customer satisfaction – UP
‒ Revenue – UP
‒ Costs – DOWN
By
 Linking business data to learning data.
 Using analytics to generate actionable insight.
Why are we doing this?

3.  Variety – not just social media but text files, email, machine log
files.
 Velocity – not just how quick, but also data bursts.
 Volume – the sheer amount of data.
Big data

4. 4-ENGINE
BOEING JET:
25,000 flights
1920TB daily
The data multiplier effect at work
TWITTER:
200M users
90M "tweets"
8TB daily
NEW YORK STOCK
EXCHANGE:
2.7 billion shares
1TB daily
BUSINESS DRIVEN HUMAN DRIVEN MACHINE DRIVEN
WHAT DOES 24 HOURS OF DATA LOOK LIKE?
,
LARGE
SYNOPTIC
SURVEY
TELESCOPE
(LSST):
Galaxy map
3200 MP
30,000 pics
3000TB daily

5. Where are you on the scale?
Source: http://www.forbes.com/sites/joshbersin/2013/10/07/big-data-in-human-resources-a-
world-of-haves-and-have-nots/

6.  In groups of 3 or 4 people,
discuss where you are on the
maturity model.
 Things to think about:
‒ Do you have a data warehouse in
L&D?
‒ Do you share one with HR or the
business in general?
‒ Is it just SCORM/AICC data?
‒ What tools do you use apart from
Saba’s reporting tools?
Roundtable discussion

7. LMS
Assessment
Tool
2013: ARIES: Analytics and Reporting Integrated
Enterprise System
HDS Academy data today

8. HDS Academy data today

9. HDS Academy data today

10. LMS
IT Project
Database
HDS
Community
The Loop
Help Desk CRM Systems
LRS
(Learning
Record Store)
2013: ARIES: Analytics and Reporting Integrated
Enterprise System
2018: Advanced Analytics tools
HDS Academy data future

11.  In groups of 3 or 4 people,
think about what other data
might be useful to you.
 Things to think about:
‒ Do your top performers all read the
same books, watch the same
videos?
‒ What business data might also be
useful? e.g. CRM systems.
‒ Is there useful data in your
community tools?
Roundtable discussion

12. LRS
(Learning
Record Store)
WBT
completion data
Skill/
competence
data
Activity data for
informal learning
TinCan xAPI
data from
anywhere!
External non-
SCORM
content
Data from LRS can also be accessed and surfaced elsewhere
using xAPI
Where does xAPI fit in?

13. xAPI: A Game Changer?
Source: http://tincanapi.com/overview/

14.  In groups of 3 or 4 people,
think about what data xAPI
could deliver for you.
 Things to think about:
‒ Data value - how to determine if it's
trash or treasure?
‒ Data variety including structured,
unstructured and possibly machine
data.
‒ Your ability to understand the
meaning of this data.
xAPI: What do we need to track?

15.  Fred complained in the internal community about his
inability to sell widgets and customers who he had managed
to sell to were complaining in the customer community that
they don’t know enough or understand the product. Saba tells
us the Fred never completed his widget certification and
help desk activity confirms Fred’s customers as having more
than average issues with widgets. The internal community
data also tells us that Fred never viewed the “how to sell
more” book relating to widgets. Data from CRM confirms
Fred sells less widget product than his peers. Data from Saba
also confirms Fred’s skills rating is considered low compared
to his peers in widget products.
Actionable insights

16.  We need to expand our thinking on data outside of L&D/HR.
 We need to get onboard with xAPI NOW!
 We need to get new skills, such as Analytics, into L&D.
 And use those analytics to generate actionable insight.
What next?

17. Big data or big insights?
“It’s not the size of your source but the size of the insight that
really matters.”
Michael Hay, vice president of product planning, Hitachi Data Systems
http://blogs.hds.com/hdsblog/2012/11/title-big-data-its-not-the-size-of-your-
source-but-the-size-of-the-insight-that-really-matters.html

18. Questions
and Discussion

19. Thank You
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