k.i.s.s my big data

K.I.S.S MY BIG DATACREATE A DATA-DRIVEN ORGANISATION

Pascal Moyon, Chief Digital Officer

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LASTMINUTE.COM AT A GLANCE

Household brand supported by 16 years of (irreverent) marketing investment


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• Invest in Big Data technology

• … improve your company

performance immediately

• … and grow happily ever after

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ONCE UPON A TIME …


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AMAZING SUCCESS STORIES WHICH INSPIRE ALL BUSINESSES

• Facebook,Google, Amazon, Trip Advisor: from limbo

to world companies in 10 years

• Role models for creating success how of data

• Focus on relevance and leveraging users/customers

input through continuous improvement

• Native data-driven culture


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HOW TO CREATE A DATA-DRIVEN ORGANISATION

• Bring transparency into

the business

• Identify, prioritise and

support the company

business needs

• Influence to improve

processes and indue

cultural changes

Analytics

Roadmap

Team

Communication

Data consistency

Tools

?


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ROADMAP

• Influence and consistency: top down!

– Start from management strategic indicators

– Understand the key strategic questions,

challenges and opportunities

• Accurate

– Unify company reports and create a common

set of definitions

– Identify the relevant source of data and

complement then if need be

• Actionable and quantifiable

– Focus on key drivers that the company can

actually influence

– Translate opportunity into monetary value

• Pragmatic

– Proximity with the business to ensure that the

insights can be easily consumed and

translated into action

– Educate: only provide the necessary data

Visits Conversion ABV Margin % Total

Product A -525,375 36,696 -614,926 -426,117 -1,529,722

Product B -1,687,958 994,686 34,206 -407,637 -1,066,703

Product C 416,548 -745,119 -134,449 -513,522 -976,542

Product D -155,545 208,143 24,703 -68,547 8,754

Product E 226,998 -29,667 -1,369 -191,050 4,912

Product F 316,003 -14,676 38,545 -66,948 272,924

Product G -183,104 171,408 4,747 -91,955 -98,905

Product H -1,271,169 21,932 88,041 -185,513 -1,346,709

Product I 600,467 -451,397 -4,471 -192,541 -47,942

Product J -67,827 -88,823 -37,218 -22,815 -216,683

Product M -118,160 -2,068 4,864 -12,824 -128,188

-2,955,083 531,700 -668,128 -2,306,060 -5,397,572

Align the business

on key issues


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• Identify key levers and opportunities

• Select relevant KPIs and data sources

• build self-improving processes based on robust data (quantitative and qualitative)

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IDENTIFY KEY PILLARS

• Speed and stability

• Conversion funnel

• Pinch points, heatmaps

• Choosing the right mix

• Executing effectively (ROI)

• Performance (conversion)

• Competition and competitiveness

• Quality

• Profitability

• Experience

• Engagement and feedback

• Segmentation

• Personalisation

Customer Product

UsabilityAcquisition


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• Common sense and hygiene still get a lot of mileage …!

– How much of Netflix’s success arise from its recommendation engine vs the size of

its inventory?

– The same for Amazon: customer focus, delivery promise and inventory size vs

clever recommendations?

• Complex algorithms need to be explained to get the business buy-in … and

they only work is they are understood, used and maintained

– Communication is key for acceptance, especially if engagement is required with

suppliers or customers

– Always weigh the benefit of increased performance versus the implementation and

maintenance risks

– Data scientists are in demand, with risks on turn-over and hand-over

• Conclusion:

– Walk before you can run

– Always prefer speed of implementation and test before perfection

– Start by a version 1 of an optimisation with the most likely segments, and make it better

=> will help a lot to bring the whole organisation up the learning curve

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BEING PRAGMATIC


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• One team!

– Significant risk otherwise to have different definitions, unnecessary

competition and confusion (let alone silos …)

• Complementary skills sets and styles

– Business: pragmatic and intuitive

– Reporting/Data: rigorous and process driven

– Data scientist: knowledge and technical

• Integration with the business

– Consider having business performance manager working alongside key

stakeholders (products and/or functions)

– And reporting and data science as shared services

– The team leader has to report as high in the hierarchy as possible: CEO

(ideally, CFO, CTO or CMO otherwise, with specific challenges)

• Invest on a robust team way above the tools

– Open-source tools such as Python and R are incredibly powerful

– Cloud computing is inexpensive

– Very few business needs require extensive computation capacity: create

a pilot first to test the concept and only industrialise after

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KEY ADVICE TO CREATE FOR A TEAM


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• The analytics paradox: more and more

data

• Less and less time bandwidth in the

organisation

• Finding ways to convey potentially

millions of data points into compelling

insights

– Speak the business language

– Present the relevant KPIs

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EFFECTIVE COMMUNICATION

Visits Conversion ABV Margin % Total YOY Margin, %

Product A 15,355 -40,095 -172,549 98,770 -98,519 -7%

Product B 257,481 12,048 -75,169 97,939 292,299 23%

Product C 814,432 28,695 -114,090 125,390 854,427 58%

Product D 5,796 120,761 -7,775 10,723 129,504 192%

Product E -98,297 339,071 -78,498 61,982 224,258 25%

Product F 84,988 -20,467 175 5,613 70,309 126%

Product G 5,102 23,971 -8,939 11,761 31,895 20%

Product H 32,893 9,568 -28,379 15,632 29,714 13%

Product I 107,411 130,001 -48,930 33,449 221,932 65%

Product J -64,050 -34,526 -5,616 4,940 -99,252 -64%

Product M -21,132 -9,166 -2,140 3,582 -28,856 -42%

1,900,599 -137,733 -621,285 483,833 1,625,415 26%


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• Link the C-suite and the digital execution to enable and improve the engagement

with the customers and grow the customer base effectively

• Create a consistent set of effective processes underpinned by a strong team

operating an architecture of cost-effective digital tools

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WHAT IS THE ROLE OF THE CDO?

k.i.s.s my big data

Data & Analytics