improving business outcomes through rapid data visualisation
DESCRIPTION
Visualising data provides clarity, increases engagement and delivers unexpected insights. A rapid and adaptive approach to building visualisations can help you realise value with a minimal investment. David and Ray shared thoughts and client stories from work in Perth and Melbourne at an evening briefing in Perth, Western Australia, on 29 October 2013. David is a lead management consultant with a mathematical visualisation bent (find him on LinkedIn or see his blog). Ray is a lead developer consultant who enjoys thinking up and building products (twitter @grassdog).TRANSCRIPT
Improving business outcomes through rapid data visualisation
29th October 2013
David Colls & Ray Grasso
Informed decision-making & unexpected insights… right away.
Mapping cholera deaths London,1854 Spatial visualisation
by John Snow, 1854
Communications at GE Image from GE
Decision cockpits at P&G Image from HBR
courtesy of P&G
More organisations using visualisation
HealthHack Oct 2013
Why visualise data?
1
2
3 Easy to understand
New insight
Shared view
Holistic view
Independent Market Operator (IMO)
Facilitate competition between power generators and retailers Encourage private sector investment in power generation and retailing. Support the development of sustainable energy sources
IMO Goals
The Problem
We want to be
more transparen
t
… people to understand what we do and why it’s valuable
The Approach
Decide on an initial direction
Get our hands on the data
Follow the data
Rapidly build and refine
Shift from the data problem to the communication problem
Get it to the audience
Evolution of a visualisation
Example
Let’s look at it live…
Outcomes
… I am a developer and would be interested in accessing your data...
...can I just say how awesome the IMOWA data visualisation page is! … take that NEM …
Takeaways
Minimise speculation Use real data Be open to unexpected opportunities
Follow the data
It’s okay to start out vague Test with users to see if your story is being communicated effectively
Rapidly refine the story
6 Weeks Open source technologies Explore where the data leads and release early and often.
IMO Summary
Improving a Call Centre
What does a big Call Centre look like?
200,000 10,000
500 24
7
calls each day agents products hours days
The Problem
It’s so big, we don’t have a clear picture what it looks like now, let alone how to improve it
We also saw…
Surprises in demand and supply Data issues answering queued calls Same-queue transfers
Plus: timing discrepancies, very long calls,
mischaracterised agent skills, etc, etc, …
The Approach
Get the data
Evolve a fuzzy visualisation
Ask: Why?
Deliberate fuzziness leaves room for ambiguity and interpretation
Pursue quantitative investigation
Takeaways
A fuzzy visualisation helps you discover questions
Visualisation gives insight on operations and on data quality
You can rapidly evolve a very complex visualisation
Call Centre Summary
Undertaken as part of a major programme 2 weeks to build Used “Processing” software Accelerated learning reduced programme duration & operational improvements were realised sooner
NOPSEMA National Offshore Petroleum Safety and Environmental Management Authority
http://www.flickr.com/photos/19779889@N00/ (Arby Reed)
2 Weeks Simple visuals on existing systems can provide benefits.
NOPSEMA Summary
Benefits
Provide a holistic view of complex systems Glean unexpected business insights Craft engaging communications
Where to from here?
Start small and stay lightweight Use real data throughout Refine and adapt
Questions?
Thank you