Deepan Nithi - Winning with a top down data culture

Winning with a top down data culture

Deepan Nithi

September 2017

What I’ll cover today

Footer I Page 2

• Background on Lotto NZ and why we need analytics

• Leading analytics teams and the importance of a top down data culture

• Self service analytics at Lotto

Lotto NZ - Purpose

Footer I Page 3

To provide safe gaming that allows New Zealanders to play and win

while contributing money back to New Zealand communities

Lotto NZ - background

Footer I Page 4

• Crown entity established

in 1987

• 100% of Lotto profits are

returned to the community

• Last year $204 million

went back to the

community

• Over 3,000 organisations

and projects receive

lotteries grants each year

Lotto NZ - background

Footer I Page 5

Lotto NZ - background

Footer I Page 6

• Largest retail network in NZ with

over 1,450 stores

• Currently 1 store per 3,200 people

• Over 80% customer penetration

83%

4%

13%

Our games

Footer I Page 7

Why analytics at Lotto?

Footer I Page 9

Why analytics at Lotto?

Footer I Page 10

Why analytics at Lotto?

Footer I Page 11

Footer I Page 12

Data culture at Lotto

Footer I Page 13

• Strong backing from the CEO and executive teams

• Investments made for a sound BI and reporting platform

• Access to some high calibre analytics partners

• Roadmap in place to future proof our analytics capability

• Data at the centre of decision making

The analytics team

Footer I Page 14

• Where should the team sit?

• What size ?

• Skill set?

• Do we all need data scientists?

• Outsource or internal?

Data culture at Lotto

Footer I Page 15

Data culture at Lotto

Footer I Page 16

Self service analytics at Lotto

Footer I Page 17

• Why self service?

Enable access to data insights as and when required

Reduce reliance on the analytics team

Improve understanding of our data

Faster decision making

• Risks

Potential misinterpretation of data or visualisations

Poor decisions made as a result

More reporting than analytics

Self service through Power BI

Footer I Page 18

Self service through Power BI

Footer I Page 19

Analytics on the road

Footer I Page 20

Where to next?

Footer I Page 21

Questions?

Footer I Page 22