Improving business outcomes through rapid data visualisation

Post on 04-Dec-2014

1,065 views 0 download

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