Copy of DataKind UK data maturity assessment

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1	Notes for data maturity call
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3	1. Introduce your selves and purpose for the call: The reason we have these calls is to understand how the social change organisation (SCO) uses data within their organisation and what would be the best ways in which DataKind UK can support the SCO to increase their data maturity. Our mission is to improve the overall data science capacity of the organisations we work with, and we will use the information gathered in todays call to assess the impact of our work with you.
4	2. Ask the questions below- each reviewer can take it in turns to ask questions or one person can lead. Write brief notes
5	3. Assess the overall category according to the data maturity framework: https://static1.squarespace.com/static/5d514d1775e9c90001345670/t/5d9f402df0b6312eb6c55f69/1570717742668/Data+Orchard+Data+Maturity+Framework+NFP+Sector+2019.pdf
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8				DATA MATURITY CALL								IMPACT CALL- 3 months post DataDive. Six months post DataCorps
9	Data Maturity Category	Questions	Responses	Yes/No (Enter 0/1)	Notes Reviewer 1: Name	Question score (optional)	Score reviewer 1	Notes Reviewer 2: Name	Yes/No (Enter 0/1)	Question score (optional)	Score reviewer 2	Notes Reviewer 1	Score reviewer 1	Notes Reviewer 2	Score reviewer 2
10	1. Uses	Introduction: We're interested to hear how your organisation broadly uses data- for what purposes and how you protect the data you use.					0				0
11		Can you describe how your organisation uses data across the following functions: see responses	Recording activity/work with clients			0				0
12			Measuring service quality and performance
13			Measuring the difference you make e.g. outcomes, impact evaluation
14			Evidencing the needs/problems you seek to address
15			Understanding the types of clients/environment you serve (e.g. profiles, characteristics)
16		Can you describe how you are compliant with the DataProtection Act 2018/ GDPR and whether you ensure that people you collect data from are aware of the purposes you will use their data?	GDPR compliant			0				0
17			Have the necessary legal requirements (e.g. consent, legitimate interest) to share data for analysis
18			Do you conduct data protection impact assessments to assess the consequences- both positive and negative of making use of data?
19	2. Data	Next, we would like to hear about the data you collect, and discuss what it covers, it's quality and consistency.					0				0
20		Thinking about the quality of data in your organisation as a whole, to what extent do you agree or disagree with the following statements?	We collect and record data in an efficient manner			0				0
21			Our data is complete, consistent, accurate and, where necessary, kept up-to-date
22			We collect the right data i.e. relevant, meaningful and necessary
23			We quality assure the data we collect
24			We maintain a record of data assets and who's responsible for them
25		Do you make use of data in the following ways?	Share data internally from different teams, departments or services			0				0
26			Commission independent research or evaluation
27			Use publicly available external research (e.g. government, academic)
28			Use publicly available open data sets (e.g. raw data)
29			Use shared measures and benchmarks with other organisations
30	3. Analysis	Moving on to analysis, we'd like to understand what type of analyses you currently do					0				0
31		What type of analytical techniques do you use across the organisation?	Basic counts and/or charts			0				0
32			Descriptive analytics (about what happened e.g. summarising the overview averages, variation, range, past trends)
33			Diagnostic analytics (about why it happened e.g. drilling down to explore causes, patterns, anomalies, discovering differences, correlations)
34			Predictive analytics (about what will happen in future e.g. forecasting, modelling trends, behaviour patterns, machine learning)
35			Prescriptive analytics (about how you can do it in the best way e.g. optimisation, recommending decisions for effective intervention, experimental design, simulation, artificial intelligence)
36		How automated and integrated is the data analysis process?	Data is discussed informally between teams			0				0
37			People verbally report on data as part of strategic discussions
38			Data is manually collated in reports using data from different sources
39			Data analysis and reporting is automated for some individual systems
40			Data from different sources is brought together and analysed in an automated way e.g. we have a dashboard/business intelligence system/data warehouse, pulling data from different tools and systems
41		Can you describe the most advanced data project your organisation has conducted?
42	4. Leadership	Now on to leadership, and whether senior leaders in your organisation are driving your organisations use of data					0				0
43		How much does your organisation use data in the decision-making process?	The leadership is aware of the value of data			0				0
44			We have people with data analytics expertise within our leadership
45			Our leadership champions the use of data. They drive questions, are influenced by findings
46			Leaders invest enough in data related resources (people, skills, learning, tools)
47			We have an overarching business plan with defined measurable goals
48		How systematic is your organisation's use of data?	We use current data to monitor what's happening now			0				0
49			We use historical data to identify trends and patterns
50			We review historical data for quality assurance
51			We actively improve data collection based on reviews of previous reporting
52			We have a data strategy, endorsed by leadership
53	5. Culture	Next we would like to understand your organisation's data culture & general data practice					0				0
54		How engaged with data is the staff?	Data is seen as a team effort (not just one person's responsibility)			0				0
55			People from different teams/levels of seniority regularly discuss data and how to act on it
56			We're comfortable using data internally to ask difficult questions and challenge our practices
57			Data is easily available and accessible to staff when they need it
58			Staff share and discuss external data
59		Do you have a strong data security culture?	Our policies and practices are robust to ensure our data is safeguarded (e.g. rules on passwords, how data is stored)			0				0
60			We delete data about identifiable individuals that is no longer necessary
61			We specify and manage access to sensitive and personal data (e.g. related to job role)
62			We're confident about the security of the data we hold on paper, computers and other devices
63			We monitor and test potential risks to improve our data security and protection (e.g. theft, accidental loss, malicious attack)
64	6. Tools	These next questions are about the common IT used across the organisation					0				0
65		Does your organisation use the following tools to COLLECT data from your clients and stakeholders?	Paper forms or questionnaires			0				0
66			Staff data entry into database/CRM system (e.g. recording interactions on the phone/e-mail/in person)
67			Third-party online tools: surveys or mailing lists
68			Own website or mobile app (e.g. online registrations, bookings, orders, sales)
69			Social Media
70		To what extent does your organisation use the following tools to ANALYSE and REPORT on data you collect and store?	Manual/Visual Search or counts			0				0
71			Spreadsheets (Charts, Counts, Pivot Tables)
72			Database/CRM Analysis and Reports
73			Business Intelligence/Dashboard/Data Visualisation Tool
74			Statistics software (e.g. SAS, R, Stata, Python, SPSS, GIS Mapping)
75	7. Skills	This final section is about the data skills within your organisation					0				0
76		What data specialists does the organisation employ?	Data entry clerk - responsible for collecting and reporting data, perhaps largely using spreadsheets			0				0
77			Data manager - responsible for managing data collection and storage systems, perhaps a database administrator, perhaps with a more general role
78			Evaluation analyst - using statistical tools and models to learn from internal data (e.g. what works)
79			Research analyst - focused on the analysis external statics for policy advocacy
80			Data scientist - focused on advanced statistical modelling to automate decision-making
81		Does the broader staff have the skills they need to use data?	Staff are providing training on how to collect, manage, use and store data			0				0
82			Staff receive regular refresher training on data management
83			Most staff are data literate
84			We have the right skills and capabilities to maximise the use of our data
85			We coordinate our data expertise across teams/services including senior, specialist, technical and administrative roles
86		Next steps: We will discuss your data maturity score with your project application at our next scoping committee. We will then be in touch to let you know if we have approved your application or if there are any amendments needed.
87	SUM	Total score/ Overall thoughts- Please provide the reasons you assessed the SCO at that level of data maturity					0				0				0
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91	Key	See Data Orchard to read full profie https://static1.squarespace.com/static/5d514d1775e9c90001345670/t/5d9f402df0b6312eb6c55f69/1570717742668/Data+Orchard+Data+Maturity+Framework+NFP+Sector+2019.pdf
92	0-1	Unaware
93	1-2	Emerging
94	2-3	Learning
95	3-4	Developing
96	4-5	Mastering
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