Description and rationale
Use good-quality evidence and insights for early identification of needs and to implement targeted interventions.
In short, be data-informed in our approach to digital inclusion. Rather than relying on assumptions or reacting to issues late, this principle means we will use data to identify who is digitally excluded, why, where they are, and let that evidence guide our actions. For example, data might show which areas have the lowest broadband coverage or which demographic groups use our online services the least. With this information, we can proactively target support, for example by setting up a digital training session in a community that data shows low internet usage. Being evidence-informed also means we will measure the outcomes of our initiatives. For example if we distribute tablet devices to a certain group, we will collect data on usage or skills improvements to see if it worked and adjust our future approach accordingly.
This principle supports the Council’s value of being evidence-based and transparent. It also helps build the business case for digital inclusion, by showing the positive impact or identification of unmet needs, so that we can secure continued support and resources.
In summary, data is our compass. It helps us allocate resources wisely and it keeps us accountable. Importantly, a data-driven approach often reveals hidden gaps and makes sure we do not rely on who shouts loudest, but also find those who may be quietly under-served. Overall, this principle enables continual improvement and smarter decision-making in achieving inclusion goals.
Maturity levels
Level 1 – Initial
Decisions on digital inclusion are mostly ad-hoc and anecdotal. Efforts might be guided by isolated complaints or assumptions (e.g. “I think older people in Village X struggle with online forms”) without quantitative evidence. Little relevant data is collected or used beyond basic usage stats.
Level 2 – Developing
Some data is collected and used occasionally. For example, the Council might look at web analytics (traffic, drop-off rates) or national surveys (e.g. ONS data on internet use) to inform plans. However, data is not comprehensive or regularly analysed for inclusion. There may be one-off research projects or pilot surveys (e.g. a library surveying patrons’ digital skills), but no routine, Council-wide practice of using data to drive inclusion decisions.
Level 3 – Mature
A defined data strategy, referencing digital inclusion, is in place. The Council actively combines multiple data sources, e.g. service usage stats, the Digital Exclusion Risk Index (DERI) for local areas, resident and staff surveys, feedback from support lines, to map out where digital exclusion is highest and what factors contribute. Decisions and resource allocations are backed by this data: for instance, choosing a particular town for a new digital skills centre because the data showed low online uptake and poor broadband there. Outcomes of inclusion initiatives are measured with data (e.g. after a project, we check if online transactions or digital skill levels in that area increased).
Level 4 – Leading
Real-time and predictive analytics are used to continuously improve inclusion efforts. The Council can even anticipate needs, for example by using demographic trends or predictive modelling to anticipate which communities might face digital exclusion in the near future and be proactive about solutions. Data on digital inclusion is openly shared with partners and possibly the public, fostering transparency and wider problem-solving. At this level, nearly every inclusion strategy or project is shaped by data insights, and the Council adjusts its approach in an agile manner based on what the data shows works or doesn’t work.
Metrics
Digital Inclusion Dashboard KPIs
Establishment of a Digital Inclusion Data Dashboard tracking core metrics.
Target: Dashboard is live and reviewed quarterly. This may include metrics such as:
- Online and offline service use: Percentage of transactions completed online, split by service and demographics, to identify gaps in service availability.
- DERI Scores: Digital Exclusion Risk Index (DERI) for each locality with a baseline and target to reduce high-risk areas.
- Training and/or support provided: e.g. Number of residents who attended digital skills sessions or were assisted by Digital Inclusion Champions to measure our output.
- Broadband connectivity: Percentage of Somerset population with access to high-speed internet to track infrastructure progress.
Evidence-based projects
Percentage of digital inclusion initiatives that explicitly use data in their planning. For example, a project plan references survey results or usage stats that justified the intervention.
Target: 100%. This ensures all projects are rooted in evidence.
Monitoring frequency
Frequency of data analysis and reporting on inclusion. Regular reporting indicates we are continually using data, not as a one-off.
Target: Quarterly internal updates, and an annual public report.
Adjustment and learning
Number of strategy adjustments made based on data insights. For example “We changed our approach in X programme after data showed low impact.”
Target: At least one significant course-correction per year based on data. This metric is qualitative but emphasizes a learning culture. Also track if all major inclusion actions have defined success metrics from the start, and report on them.
Strategic alignment
Target Operating Model
Data and Insight theme: The TOM includes a theme of Data Insights and Evidence, which calls for “using data across the organisation intelligently to inform decision-making and improve service delivery”. This principle directly applies that to digital inclusion – ensuring we gather and use relevant data to guide our strategies. It also ties into the TOM‘s aim to “target early help to people and communities that need it most”. Data allows us to identify those people and communities in the context of digital access, and to target early help such as training before a service goes fully digital, or connectivity investment in a poorly served area.
Strategic Objectives
Evidence-based policy and equal opportunity: Being data-informed supports the Council’s commitment to evidence-based decision making (one of our core principles in the Corporate Plan). For example, the Corporate Plan’s “Fairer Somerset” priority acknowledges that some people cannot access digital services and commits to retain other options. A data-driven approach would measure how many people fall in that category and whether that number shrinks over time with our interventions. It contributes to “Flourishing Somerset” by informing where digital infrastructure or training is needed for economic participation (aligning with the Corporate Plan’s promise to improve connectivity in areas that need it most). For “Healthy and Caring Somerset”, data might highlight areas or groups that are not accessing online health services, prompting targeted support and supporting positive health outcomes. Overall, this principle ensures that our actions toward each strategic goal are guided by knowledge of where the real-world gaps are, making achievement of those goals more likely.
Wider Corporate Plan
Transparency and accountability: The Corporate Plan emphasizes being open and accountable. By using data and sharing results, we live up to that – we will have the ability to show residents and members how we are doing on digital inclusion (e.g. via an open digital inclusion index or updates with stats). It builds trust that the Council is not leaving inclusion to chance.
Additionally, the Corporate Plan’s theme of “empowering communities and working with partners” can be enhanced by data. We can share localised data with community groups or Local Community Networks to empower them to help. This principle also intersects with the Council’s digital transformation efforts – as we digitize services, being data-informed ensures we do not inadvertently widen gaps and that we track the impact on all residents.
Actions to ensure maturity
- Define and track key KPIs: Create a Digital Inclusion Dashboard. Likely metrics include those above: online service usage by area/group, number of people supported, connectivity stats, etc. Assign owners for each metric (e.g. Customer Services for channel usage data, Digital Transformation team for broadband data, Libraries for training numbers) and report on them quarterly. This institutionalises data monitoring.
- Leverage business intelligence (BI): Work closely with the corporate BI or analytics team to gather and analyse data. For example, have BI produce heat maps of digital exclusion risk across Somerset using indices and our own data. BI can also correlate datasets (e.g. areas with high face-to-face service usage vs low online usage) to pinpoint “cold spots”. If needed, invest in tools or licenses such as analytical software or data sources that help measure digital inclusion.
- Close data gaps: Identify where we lack data and take steps to fill those gaps. If we do not know employees’ digital skill levels, consider a staff digital skills survey. If we lack info on residents’ digital access, incorporate a few optional questions into existing citizen touchpoints (for instance, ask about internet access in housing application forms or during adult social care assessments). Make sure to do this in a privacy-compliant, sensitive way. Over time, build a richer picture of who might need digital help.
- Use data to target projects: Before launching any major inclusion initiative, require a brief data analysis to justify it. For example, if we plan a series of digital training workshops, decide locations by analysing data (perhaps library staff input, socio-economic data, and DERI scores show certain communities would benefit most). Document this in project plans to encourage the habit. After the project, collect outcome data (attendance, any change in online usage by participants, etc.) to evaluate success.
- Regular Reporting and Reviews: Add digital inclusion metrics to existing performance frameworks. For example, include them in quarterly corporate performance reports or the Transformation programme dashboard. Host an annual Digital Inclusion review where data for the year is presented to Members (e.g. how many residents gained connectivity or skills, how service usage patterns have changed). Use these reviews to celebrate progress and identify priorities for the next year based on evidence.
- Data Sharing and Partnerships: Share relevant data insights with partners and communities. For instance, publish a summary of digital inclusion stats on our website (while maintaining individual privacy) to raise awareness. Internally, share with Local Community Networks details like “in your area, X% of people are not online; we are focusing on this by doing Y”. Externally, collaborate with agencies like the NHS, DWP, or community groups to exchange data – they might have complementary data (e.g. GP online registrations, library usage) that, when combined, give a fuller picture. A collaborative, data-driven approach with partners ensures efforts are aligned and resources pooled.
- Iterative Learning: Establish a practice that every major program includes an analysis phase at the end using data to answer “Did it work, and what next?”. If, for example, an initiative didn’t reach as many people as hoped, analyse why (did the data target the wrong group? was the channel inappropriate?). Feed these lessons into the next cycle of planning. In essence, use data not just to start projects but to refine and improve them continuously (the Plan-Do-Check-Act cycle fuelled by data). This could be overseen by the working group or BI team as a formal feedback loop.