Benjamin Cave – Trainer

@cave_ben3 May 2023

The Self(less) Publisher

Enable participants to understand the the importance of open data strategy

Course aim

Explain the key pitfalls of organisations without a data strategyList the key characteristics of an effective open data strategyUnderstand the four keys open data strategy on the organisationSolve a simple open data strategy challenge by applying game theory principles

Outcomes

Data strategy as roads

We build roads to connect places we value

We build data to get to decisions we value

https://www.flickr.com/photos/ronsaunders47/7459822850

Which is sometimes all you need…Without strategy, roads all look like this…

https://www.flickr.com/photos/highwaysagency/6194409693

But most times we need strategy

to ensure our roads make sense together…

When data strategy is optimised

friction is reduced

http://www.theodi.org/data-spectrum

What is data strategy?

5 minutes in groups

“A single, unified, organisation-wide plan for the use of corporate data”

Credit: Capstone

“A roadmap and plan to identify what to do with a company’s data and to support

accessing, sharing and managing the content,”

Credit: SAP

“A statement of the value the organisation sees in their data and a set of actions to

capture that value,”

Credit: Benjamin Cave, ODI

Why is data strategy important?

Call-out answers

Bad data costs the U.S. alone $3.1 trillion annually

Credit: IBM

Workers in knowledge & data roles spend 50% of their time correcting and testing

data

Credit: Thomas Redman

Costs roughly 10 times as much to work from incorrect data as from perfect data

Credit: Rule of 10, Thomas Redman

Without data strategy the organisation can fall into one of these five traps…

Trap 1: Siloed

“We don’t know who holds what”

Siloes companies don’t know where data is stored and, in some cases, how it is used. Different parts of the

business use their own data for their own goals with very little sharing

Trap 2: Resistant

“That’s not the way I work”

Resistant companies have staff who refuse, deliberately or otherwise, to tow the line when it

comes to data management & use. Different people pursue their own goals regardless of the strategy.

Trap 3: Piecemeal

“This time lets do it this way”

Piecemeal companies lack a central data strategy. They have many data strategies for different projects or data types and each new area is set up without reference to

the others.

Trap 4: Legacy

“The system means we have to do it this way”

Legacy companies have strategies designed around the constraints of their systems or workforce skills. Even

where the goals of the business are different, strategy is led by resources rather than objectives.

Trap 5: Focussed

“That data isn't relevant to us”

The focus company only cares about data that serves a single or limited set of objectives. They will discard or

neglect any data not directly relevant to their focus area(s).

So strategy is important… How does it get made?

literacydevelopment oversightintegration

The keys to putting [open] into data strategy

development

1. Set the vision for data

2. State the value clearly

3. Create simple actions

1. Set the vision for data

Visions don’t have to be complex… just clear

Exercise

With a partner, write a 1-sentence vision for how your company will ideally use data

5 minutes in pairs

2. State the value clearly

Group DiscussionData strategy is about a clear statement of the value you expect data to bring to the business

Generate a list of types of value data can bring to your business

15 minutes in groups

3. Create simple actions

Exercise

What are the main elements of a data strategy ?

5 minutes in groups

Map

Describe

Maintain

Share

Govern

Find out who holds what and where it is

Ensure all data is well described and can be searched

Schedule the correct support to ensure consistent access

Create access arrangements that maximise value & respect privacy

Integrate data into reporting structures & management priorities

Data literacy

1. Levels EveryoneWhat is data and why

it matters to the organisation

SpecialistsHow to analyse, store and work with data

effectively

ManagersHow to manage work with data and achieve

strategic goals

VisionariesHow to deliver impact

and innovation

2. Domains ArrangementVisualise how skills can be built up to

develop deep understanding &

confident application

DomainsBreak down levels into

priority skillsets

3. Topics

Using the framework

1. Classify level of pre-existing data literacy2. Determine target level based on role

3. Select relevant domains based on function4. Pick topics based on interests

For best results, topics should be adjacent.

Exercise

Use the framework to classify the best skills for our four personas20 minutes in groups

Brian - administrative assistant

Brian doesn't work with data. He doesn’t understand why the

organisation has a data strategy. Brian also has a career interest in

business management

Nita – customer insights manager

Nita looks after the customer insight team. Her staff analyse large

volumes of data. Nita wants to increase productivity and monitor

results.

Elise- market analystElise produces market models for

company strategy. Her job involves frequent data interaction. Elise is

interested in improving her sources of data and range of analytic

techniques

Terrance – head of partnerships

Terrance heads up strategic partnerships. His role involves

regular discussion of data sharing arrangements. Terrance is also

interested in the business potential of open data

Personas for diagnosis

integration

Integrating strategy1. Take a phased approach based on quick wins

2. Start with low resistance areas3. Ensure buy-in at team level4. Prioritise comfort over scale

5. Capture evidence for iterative improvements

Exercise

Use the spectrum to map 5 datasets from your own organisation [1 for each category]15 minutes in groups

oversight

Why create incentives?Open data benefits the organisation but some people will lose out

Those who resist perceive the current state as ‘pareto optimal’; any benefit to one person bringing at least equal harm to others.

Incentives allow rational actors to pursue their interests while contributing to the goals of your open data strategy

Incentives to implementA key driver of positive strategy adoption is strong, well-aligned

incentives

Different functions within the organisation respond to different incentives

Finding the right incentives to overcome differences, harness competition and encourage collaboration is a priority for strategy

architects

Exercise

Play the contribution game

20 minutes

The contribution game

RulesEvery player starts with 100 pounds

Each round the player decides how much to contribute to a ‘public pot’ between 0 and 100 pounds

The public pot pays everyone double the average contribution of all players

Every player ends the round with their share of the public pot plus anything they did not contribute

Example3 players

Player 1 gives 60 pounds, player 2 gives 40 pounds and player 3 gives 20 pounds

The average contribution to the public pot is therefore 40 pounds

Each player receives 2*40 pounds from the public pot to add to their leftover money

So player 1 has 120 pounds, player 2 has 140 pounds and player 3 has 160 pounds

Round 1 – No incentive

Budget: 100 pounds

Reward: 2 * average contribution

http://goo.gl/forms/Nm5B2aAwd7xJzb753

Round 2 – Individual punishment

Budget: 100 pounds

Return: 2 * average contribution

Punishment: Lowest balance eliminated

http://goo.gl/forms/vANFi1GKsXUNgfHy2

Round 3 – Collective reward

Budget: 100 pounds

Return: 2 * average contribution

Reward: If the average end balance > 150 pounds, everyone gets a sweet

http://goo.gl/forms/RHtk4xX56B0Oi3203

Round 4 – Race to the middle

Budget: £100

Reward: 2 * average contribution

Present: Closest contribution(s) to average get 10 sweets

Round 5 – Observation principle

Budget: 100 pounds

Reward: 2 * average contribution

Visibility: All contributions made public

http://goo.gl/forms/6Iu2Eu6vIntkTdBG3

Strategic Incentives

Incentive Metric Pros ConsOverall Quantity Numeric Target Collective action,

scale of resultFree-rider

problem, less useful data

Selected Quantity List of Targets Useful data, equal

contributions

Time-intensive, unit resistance

Competitive Reward

Number from Unit

Competitive drive, broad engagement

Less useful data, penalise success

Competitive Sanction

Number from Unit

Overcome apathy, broad participation

Race to the middle, Hostile environment

Impact Reward Qualitative Maximise results, focus resources

Free-rider problem,

inconsistent

Benjamin Cave – Trainer

@cave_ben3 May 2023

Thank-you