1. Big Data Inside the Museum
Catherine Murphy - Natural History Museum
Casey Scott-Songin – The National Gallery
@cscott_songin

2. Big Data Inside the Museum
What is the benefit of ‘big data’
How can I best put my own data to work?
How can I audit the data sources I already have?
What should I do with insights from my data?
How can I effect strategic change based on insights?

3. What is big data?
Big Data can be understood in many different ways; most typically it is described as being large in volume, velocity and variety
(Laney, D, 2001)

4. Priority is a function of context
How can we take advantage of different information sources?
Priority is a function of context
(Covey, S)

5. Contextualising your data
Contextualising data
Linkable data
Internal data
Population demographics
Long term, wide scale surveys e.g. IPS, Taking Part
Modelled profiles on the population e.g. mosaic
Freely available information e.g. weather data, edubase
Survey
Ticketing information

6. School address in Edubase Geographical information
Combining data: direct links
School
bookings
School address in Edubase
Geographical information

7. Taking part survey, International passenger survey
Combing data: contextual information
Survey
Postcode mapping
Taking part survey, International passenger survey

8. Challenges
The linking of data will only be as successful as the individual data sources, and no data source is perfect – so how do we assess what we have?
Value
Quality
Risk
Ease of use

9. Value : how useful is this data source currently
Value : how useful is this data source currently? Could it be more useful ?
Things to consider:
Auditing data sources

10. Quality: what is the coverage of the data? Is it accurate and reliable?
Things to consider:
Auditing data sources

11. Risk: is the data covered by GDPR rules? Is it stored securely?
Things to consider:
Auditing data sources

12. Ease of use: how accessible is the format the data is in
Ease of use: how accessible is the format the data is in? Can it be easily manipulated?
Things to consider:
Auditing data sources

13. Opportunities
Big data supports deep data- and when used correctly can inform useful feedback loop where data leads to insight when you ask the best questions
Good data and bad data – doesn’t exist – it is how you describe, use and frame the finding - some methods of research will be less useful for different tasks

14. Data sources
ONS local statistics:
Educational database:
Taking Part:
International passenger survey:
Visit Britain:
Audience Finder:

15. The future of data at
the National Gallery

16. Moving to an enquiry based model of data analysis
Understanding what the data is telling us
vs.
Using data to answer questions and solve problems

17. Using big data to understand context

18. Putting visitors at the heart of what we do
Marketing
Exhibitions
Commercial
Learning
Development
Curatorial
Visitor Engagement
Putting visitors at the heart of what we do

19. Combining data sources
Quantitative data can provide you with an understanding of what is happening, while qualitative data can provide the why

20. Creating organisational change through evidence based decision-making

21. Insights Findings Data Recommendations
Easy fixes that can be implemented, directional advice, strategy recommendations, how might we? statements
Implications of the research - what the themes and patterns impact and why they are important to the organisation
Themes and patterns that emerge from the data, aggregated across multiple data sets
Qualitative, Quantitative
and Big Data

22. Who is using data and how
Who is looking at data
Who uses data to make decisions
Who is using data well

23. what are you going to change?
Who is using data versus who is using data well
If X goes down by 20%,
what are you going to change?

24. Finding opportunities to make evidence based decisions

25. Finding opportunities to make evidence based decisions
Starting small and showing impact

26. Finding opportunities to make evidence based decisions
Starting small and showing impact
Using data to mitigate risk

27. Finding opportunities to make evidence based decisions
Starting small and showing impact
Using data to mitigate risk
Using data to design

28. Finding opportunities to make evidence based decisions
Starting small and showing impact
Using data to mitigate risk
Using data to design
Presenting research to the organisation

29. Presenting research to the organisation
How does this research/knowledge impact my day to day?
What is one thing I can change based on these insights?

30. Action Statements [Our service/product] was designed to achieve
[these goals]
We have observed that
[user insight]
which is causing
[this impact]
to the business.
How might we improve
[service/product]
so that our users
[what we want them to do].
We will know we have succeeded based on
[this measurement criteria]
How might we:

31. Research-led Brainstorming
Ideas based on insights and recommendations
Brainstorming around “how might we…?” statements
Do NOT worry about budgets or feasibility at this point

32. Difficult to Implement
Prioritising Ideas
Normal Ideas
Original Ideas
Easy to Implement
Difficult to Implement

33. Prioritising Ideas NOW WOW! HOW? Normal Ideas Original Ideas
Easy to Implement
Innovative
Breakthrough ideas that can be implemented
Low risk
High acceptance
HOW?
Difficult to Implement
The How-Wow-Now Matrix is adapted from work done by The Center for Development of Creative Thinking (COCD). Information about the COCD Matrix was published in the book, “Creativity Today” authored by Ramon Vullings, Igor Byttebier 
Ideas for the future
Dreams or challenges
Not worth the effort

34. Put into practice Understanding action statements
Thinking about data sources
Brainstorming
Prioritisation

35. Action Statements Institution X was built to provide
A centre of learning around a global collection.
We have observed that
The number of non-English speaking visitors has gone up
which is causing
More questions and requests for language specific information about the collection
From Institution X.
How might we
Better suit the needs of our non-English speaking visitors
so that our visitors
Can learn more about our collection.
We will know we have succeeded based on
An increase in usage of non-English materials and an increase in visitor satisfaction from non-English speaking visitors.

36. What data sources do you think would be useful for this?
Put into practice
What data sources do you think would be useful for this?

37. How might we…
better suit the needs of our non-English speaking visitors so that our visitors can learn more about our collection?

38. What ideas would you suggest to this organisation?
Put into practice
What ideas would you suggest to this organisation?

39. How might this process help you in your future work?
Put into practice
How might this process help you in your future work?

40. Thank you! Catherine Murphy - Natural History Museum
Casey Scott-Songin – The National Gallery
@cscott_songin