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Rochelle’s Web Cast Takeaways
Essentials to Advancing Analytics Capability
These are my Key Takeaways from a
members-only web cast that took place on
29 November 2016
Essentials to Advancing Analytics Capability
Facilitator:
Paul FedorDirector, HR & Service Centre Metrics & Analytics,
Northrop Grumman Enterprise Shared Services
Watch the full web cast and download the slides here!
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BackgroundLaunching or progressing data analytics capabilities is in the forefront for many shared services organisations as teams continuously evolve their knowledge-based skills and the value they deliver to their customers.
Advancing on the analytics spectrum from measurements and historical reporting to predictive analysis requires a sound strategy, the right tools and leadership involvement.
Background
The following are a few highlights from Paul’s insights and our group exchange.
1“All data, dashboards,
metrics are useless unless the knowledge and insights
derived from them are translated into action.”
– Suchitra Mishra
2Most important element when
building capability is focusing on the WHY
and the IMPACT.
3Essential for stakeholders
and customers of analytics to clearly understand
the differences between reports (historical), metrics/performance indicators (past/current state) and
advanced analytics (future/predictive).
4Important to
provide information to
give data context
was a key benefit for managers and stakeholders.
Play Ball!*The Seattle Mariners baseball team beat the San Francisco Giants last night 10-0. Who do you think will win the next game?
Does your answer change if you have more data? • The Mariners had key players injured
in last night’s game.• The Giants will start the league’s
best pitcher in the next game – a pitcher who hasn’t lost a game all year.
Now, who do you think will win the next game?
*Example taken from presentation slide no. 8 of the web cast
5Leadership needs to understand both the
model / methodology and the data in order to see value
in analytics and trust your numbers.
6Begin with the end in
mind and focus on using analytics to solve a business problem.
7Avoid simply providing data
to answer questionsversus
understanding the objective of the topic and perspective
being presented.
8Predictive analytics and leading
indicators start with a hypothesis.
Build questions and correlate data to prove/disprove the hypothesis.
Example: Flight risk factors in an attrition model to predict who might leave your
organisation
9When developing your strategy and assessing current maturity level, identify what will make
your organisation more competitive.
i.e. Retail industry has high turnover; provide analytics to support factors that contribute to attrition in order to outline
a plan to lower by 10%.
10Desired skills in analytics talent – people who know the data and systems,
team members skilled at analytics and understanding patterns, and someone with
consultancy experience capable of interfacing with very senior leaders in the
organisation.
Recognise it’s unlikely to find all the skills in the same person…or even 2 or 3
team members.
11Data quality and integrity
– when you have gaps or inconsistencies in your data, gauge the confidence level stakeholders have in
the systems/data sources.
Utilise the most important data elements and explain what’s
missing.
12Incentivise or measure
data entry accuracy and compliance to governance
to raise data quality.
WANT TO LEARN MORE?
Check out the presentation slides and recorded version of the web cast for further details.
ONE LAST THING…
You’ll need your Shared Intelligence login details to watch the web cast.
Can’t find them? No problem. Email [email protected]
and we’ll be glad to assist you.
