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Benjamin Cave – Trainer
@cave_ben2 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_ben2 May 2023
Thank-you