1 of 12

Value

1

2 of 12

Value

2

Intangible

Tangible

EBITDA

Empowerment

Engagement

Compliance

Risk mitigation

Cost avoidance

NPS

Revenues

Business

Value

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Value

3

Intangible

Tangible

EBITDA

Empowerment

Engagement

Compliance

Risk mitigation

Cost avoidance

NPS

Revenues

Business

Value

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Activities of a Data & Analytics function

4

Intangible

Tangible

Data literacy

Data governance

Data platform

Data insights

Data automation

Data science

How should we allocate our efforts?

How do we know if we create value?

We can think of 6 key activities - or “services” - that the Data & Analytics function provide to a company and its people:

- On the left, data literacy, data governance, with quite indirect impact

- On the right, data science or automation, with most measurable impacts.

So, how do we decide where we should invest our efforts?

Should we focus on measurable impacts, and disregard intangible? Are investments in data governance less important than data insights, or data science?

Our collective challenge, as data professionals, is probably to define that right balance:

- to make sure that when the impact are tangible, we measure them,

- that when they are not, we find a way to assess or justify them.

- and that when it comes to business casing or justifying investment, we have a correct approach to balance the full scope of data services.

I’m not going to do start right away with more concepts on how do we measure value, and instead I will do a shortcut to what the end-state looks like for us at Bupa. <transition>

+2’

(7’)

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Value delivered

5

and covering “intangible” when target is met

Virtual P&L as driving principle

With starting point on “tangible”

195 activities prioritised
124 started

17 (14%) had a positive EBITDA
Best three have an ROI of 31x and worth more than half the total value

Target:

2.00

At Bupa, we tried to organise our governance around the measurement of tangible value, while not de-prioritising the intangible value either, and the way to reconcile the two for us was to define with leadership an area of comfort

We’re measuring EBITDA, when we can, or converting less tangible value measurements into EBITDA, and we achieved a return of investment of 2.8.

The investment is the sum of our salaries, bonus, overhead, cloud subscription, any opex and capex that is allocated to the Data & Analytics function.

The gains, is the fraud waste and abuse, the enhancement on retention, pricing, underwriting, and other impacts.

I’d like to point out a few interesting insights on our journey:

- 86% of the projects are loss making

- when a project succeeds, it really succeeds: our top 3 use cases have an average ROI of x31

- we reached our target of 2x after 12 month, and we’ve been wobbling around 2.5, investing more and more into long-term enablers since then, as is illustrated in our share of efforts on the right.

This means we’re still focusing more than 50% of our efforts on intangible value

+3’

(10’)

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Frameworks

6

Strategic KPIs

Strategic pillars

Financials

Alignment to our strategy

Ease to implement

Costs

Simplicity & Time

Change Management

Pay-back

period

Expected returns

1

2

3

4

5

BEFORE STARTING A PROJECT

AFTER STARTING A PROJECT

Direct cost tracking

Business outcome

EBITDA Impact

Virtual

Profit &

Loss

Timesheet

Effort

Decision

Committee

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Operating model

7

Calculate use case scores

Ideate potential use cases

Prioritise

use case backlog

Deliver the backlog

Measure success and inform

UC01

STAND BY

TO DO

UC01

UC04

UC02

etc.

Sprints

Success

metrics &

retrospective

Feasibility

VIRTUAL P&L

Tracking efforts spent (Time & material) and achieved gains (tangible or intangible) for each use case per quarter

Value is the responsibility of business sponsor

CORE

HYBRID

UC05

1

2

3

4

5

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Skill mix

Highly confidential

8

Math

System

Coding

Business

Timothy

Robin

Henri

Julie

Anna

Iris

Patty

Alex

Johan

Jackie

Don

Dicky

Jeffrey

1

2

3

4

5

9 of 12

Transparency

9

1

2

3

4

5

10 of 12

Trust

10

Credibility

Reliability

Intimacy

Self-orientation

x

1

2

3

4

5

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Trust

11

Credibility

Reliability

Intimacy

Self-orientation

x

1

2

3

4

5

1

2

3

4

Trust is:

Credibility -> through being technical enough to address the core challenge (data science) -> this with driver #3 we discussed earlier (Team training, career framework and skill set mix)
Reliability -> through always delivering on what you say -> being accountable of the team’s time, OPEX, timeline, and providing transparency -> this comes with driver #4 we discussed (Transparancy)
Intimacy -> by staying close to the business, to what matters to them, to the empathy that is needed to serve -> this comes with driver #2 (operating model with Hybrid approach)
And self-orientation -> by forgetting your own agenda, and putting the customer and business agenda first before your own -> this comes with driver #1 (prioritisation frameworks, virtual P&L)

If the business, Finance and leadership trust you, then finally you can unlock value and be a true transformative agent of the company

That’s it for us today! Hope this gives you some inspiration for your own journey, and thank you for listening!

2’

(16’30)

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12

Thank you for listening!