Protecting Democratic Freedoms With Omidyar Network

In light of recent rhetoric and policy in the U.S. targeting immigrants, refugees, people of color and other vulnerable groups, we’re doing a call for proposals with Omidyar Network to bolster the efforts of organizations protecting these communities.

From helping organizations use data to better understand the impact of their programs, cut costs, better target resources or anticipate needs from their community, we can help with a variety of needs leveraging cutting edge technology and approaches.

If your organization is working to champion democratic freedoms and civil liberties in the U.S., we’d love to hear from you.

Learn more and apply by April 30th >

We’ll match selected organizations with a team of data scientists to work together on a long-term project starting in June.

Reach out to with any questions.

Source: DataKind – Protecting Democratic Freedoms With Omidyar Network

#GivingTuesday DataDive Capacity

Thank you for your interest in joining us at the #GivingTuesday DataDive March 3-5 in partnership with 92Y and the Bill and Melinda Gates Foundation! Together, we’ll be using data to unravel tough questions and prototype new solutions to support social change through increased philanthropic giving. Because we may have a full house this weekend, please continue to check this blog for the latest updates on event capacity!

We’ll update the text below and the image above to let you know if we’re full or if we still have room for more DataDivers to attend.





Doors open 6:00pm!


What’s this #GivingTuesday DataDive all about?

#GivingTuesday is a movement to celebrate giving of all kinds. Founded by 92Y in 2012 and celebrated on the Tuesday after Thanksgiving, #GivingTuesday inspires people around the world to take collaborative action to improve their local communities and contribute in countless ways to the causes they believe in. On #GivingTuesday 2016, individuals, corporations and civic coalitions raised over $170 million to benefit a tremendously broad range of causes, and gave much more in volunteer hours, nonmonetary donations, and acts of kindness.

While #GivingTuesday’s reach has grown significantly over the past five years, philanthropic giving in the U.S. still has not risen above 2% GDP. If we could increase it by even 1%, the impact would be massive – almost $4 billion of additional funding for causes addressing tough social issues from poverty to healthcare to education and more. To understand what might motivate more people to give, volunteers will dive into data from #GivingTuesday 2016 to generate insights for a report that will be shared publicly. Philanthropic giving is what fuels social change – lend your skills to help unleash even more of this critical resource.

Collaborate and engage with some of the brightest minds in data science, social change and technology as you work in teams to analyze, visualize, and mashup fascinating data sets to create real world change. We believe data has the power to change the world, but only when we all work together. Join us for a data adventure like you’ve never seen and get ready to make friends, build skills and help unleash the power of data to serve humanity!

Source: DataKind – #GivingTuesday DataDive Capacity

DataDiving to Support Youth with the Annie E. Casey Foundation

In early December, we packed our bags to host a DataDive with DataKind DC in partnership with the Annie E. Casey Foundation, an organization devoted to developing a brighter future for millions of children at risk of poor educational, economic, social and health outcomes. What made this DataDive special is that all the teams worked on challenges focused on protecting and improving the lives of at risk children and young adults, and in some cases they even used the same datasets. It was also unique in that teams were able to get input from youth experts and students from Code in the Schools, a nonprofit dedicated to teaching programming to students in Baltimore.

A huge thanks to the approximately 100 volunteers that came together ready to roll up their sleeves and dive in to the data, as well as our inspiring project champions that are doing such critical work to help support children at risk. We are also grateful to Allegheny County and the Philadelphia Youth Network for sharing their data and expertise throughout the whole process.


Helping Children in Foster Care in Allegheny County, Pennsylvania

This visual shows the impact of a child’s age on having a successful exit from the foster care system in Allegheny County, Pennsylvania. The visual was created by high school students from Code in the Schools that had never worked with data science before. With coaching from our DataKind DC Chapter Leaders, they learned onsite how to produce visualizations like this.


Children have more successful outcomes when they are in stable, loving families, but too often children in foster care move from home to home or are placed in group homes.  According to a report by the Annie E. Casey Foundation, children in group homes were more likely to test below or far below in basic English and mathematics, more likely to drop out of school and less likely to graduate from high school than children placed with families. Given these considerations, volunteers worked to optimize a child’s potential for a successful initial placement.

When volunteer data scientists at the DataDive began to look at the data regarding movement between placements, it was important to incorporate several contextual factors. Sometimes children move for a “positive” reason, such as moving to live with a relative. When the reason is “negative,” such as when a foster parent decides they can’t handle a child’s behavior and requests the child be moved, it’s called a disruption. There are some moves in a grey area that are not clearly good or bad, such as when a child is moved from a traditional foster home to a therapeutic foster home due to a need for health-related treatment. No matter the reason, the moves can be traumatic for children and typically have a negative effect on a child’s behavior. Minimizing such moves and increasing the likelihood that a child will be placed with a family rather than in a group home, is critical in providing children with a stable environment and increasing their chances for a successful exit from foster care.

Two teams set out to see how data on foster care placements in Allegheny County, which includes Pittsburgh, could help prevent mismatched foster placements and minimize moves overall for children in foster care.


Improving Foster Care Placements

Many children who enter into foster care are placed into homes based on immediacy of availability instead of fit, leading to a potential mismatch between children and their home environment. When a mismatch takes place, children may end up being moved repeatedly, with some placed in homes far away from their family, schools, community, courts and other support systems critical to their success.

Led by Data Ambassadors Janet Montgomery and Abhishek Sharma, a volunteer team of data scientists, and a small cohort of high school students studying coding, worked to uncover trends and insights about placements within the Allegheny County foster care system as a first step towards creating a matching placement algorithm and application for children entering the foster care system to improve the quality of initial placements.

The team discovered a number of insights including the impact a child’s age has on successfully exiting the foster system, as shown above. In addition, they mapped where children were being removed from homes in Allegheny County compared to where facilities were located and looked at which types of foster facilities might be leading to more mismatches. This was an exploratory analysis and further investigation is needed, but the team’s work provides a strong foundation for the future development of a matching algorithm. They successfully identified what characteristics could be used for predictive analytics to flag which children entering the system may be at greater risk for removal and therefore in need of extra support to succeed. Having better placements up front would mean more stability for children and hopefully a smoother return home, with their kin or legal guardians.


Reducing Foster Care Placement Moves

Each of these graphs shows the movement of a different child as they are given multiple placements with different families. The volunteer team identified four basic patterns that children follow represented above.


While some data is captured when a child gets moved from one placement to another, the reason for the move is not always documented, which makes it difficult to know when a child might be in need of extra support. For instance, disruptive moves might signal a mismatched placement, while positive moves might signal that a correct placement has been attained. In some cases, where an ideal placement isn’t available, placing a child near critical support systems might be a suitable, if imperfect, alternative. If move types were better classified, caseworkers would have greater insight into how best to support children in foster care and potentially predict when a move is likely so they could intervene.

Data Ambassadors Ravi Solter and Sharang Kulkarni led a team to understand and potentially discover some overarching reasons that might explain disruptions. They also wanted to understand what might influence the likelihood a child will have a “positive exit” from foster care overall. The team dove in, analyzing and visualizing over 14,000 cases of children switching placements. They confirmed Allegheny County’s hunch that a child’s race and age indeed have a significant impact on whether or not they successfully exit foster care. Gender also has a significant impact, as they found that boys have a higher percentage of good placement exits than girls. Only about 50% of girls have good exits, versus almost 70% for boys (as shown with the graph below).



This graph shows the percentage of good and bad exit outcomes by gender.


This analysis is an important first step for caseworkers and child service agencies to better understand what factors make a disruption likelier so they can make better initial placements.


The Philadelphia Youth Network – Helping Young People Find Early Employment for a Strong Long-term Career

Studies have shown that youth who do not have early work experiences are more susceptible to unemployment in the future and are less likely to achieve higher levels of career attainment. The Philadelphia Youth Network (PYN) aggregates outcomes of youth enrolled in a variety of employment programs across different service providers. They wanted to understand what types of employment, wages, sectors, earnings, hours and other factors help young people achieve success and stability in their careers and what kinds of employment programs are best suited for different kinds of backgrounds.

Led by Data Ambassadors Nick Becker and Helen Wang, the team set out to analyze PYN’s data to provide insight into which employment programs are successful overall, which are successful for some groups, and which factors are driving success. Jobs assigned to students in an employment program are typically designed to be 120 hours over the course of six weeks, with a student “passing” the program if they’ve worked a minimum 86 hours. The team found that the program was actually getting more successful over time.


This graph shows the percentage of students in employment programs that have worked over 86 hours in their job assignments has been increasing. The program is becoming more successful over time.


The team also explored how demographics of the students, the length of job placement, what month the job starts and more were affecting success rates. They suggested future analysis on the students who don’t repeat the program to understand if it’s because they were unsuccessful or because they are going to school or found long-term employment. With better information about their employment programs, the Philadelphia Youth Network will be able to offer more targeted programs to help even more children achieve positive outcomes in their adult lives.


Annie E. Casey Foundation – Connecting Public Data Systems to Better Understand System-Involved Youth 

Youth who become part of the child welfare system are more likely to run away or become homeless; youth who age out of foster care face high risks of homelessness, and mental health issues are higher in homeless youth. While these issues are interconnected, youth service programs and agencies often do not share data with each other, making it difficult to view all aspects of a young person’s risks for homelessness and other negative outcomes. Inspired by Allegheny County’s integrated data system, Annie E. Casey Foundation wondered how might other municipalities adopt a similar integrated data system to show a more comprehensive picture of youth and help agencies better support youth involved in multiple systems.

Led by Data Ambassadors Greg Matthews and Aimee Barciauskas, the volunteer team aimed to explore the benefits of using an integrated data system for Allegheny County’s Office of Child, Youth, and Families by describing the populations of children and youth who have received services from their Behavioral Health and Homelessness programs.

The team produced population profiles of young people that have used each service or both services and described the groups of individuals who reappear between and within the same services.


This diagram shows the overlap of services used by young people – “bhs” or Behavioral Health Services, “shelt” or Homeless Services and “cyf” or Child Welfare Services.



These two graphs show the demographics of youth clients who used all services vs. Child Welfare services only.


The team also created an interactive tool to describe the youth clients and mapped their pathways through the systems over time.

These are two screenshots from the interactive tool. The top presents demographic information on the youth clients. The bottom shows how youth clients move through the systems over time.


The team recommended that the Annie E. Casey Foundation leverage data visualization tools for deeper exploration and more consistently categorize behavioral health services to allow for more robust analysis in the future. The Foundation is hoping to ultimately persuade other jurisdictions to link their disparate data sources on youth in an integrated data system like Allegheny County’s, allowing better monitoring of the risks that young people face and potentially improving targeted services to prevent disconnection.


Thank You!

Big thanks to all the volunteers that joined us for an inspiring weekend using data to support America’s youth – especially those that drove down from New York to be there! We are also grateful to Allegheny County and the Philadelphia Youth Network for sharing their data and expertise throughout the whole process. And a special shout out to the youth experts and Code in the Schools’ students that shared their wisdom and donated their time to give the teams’ context and help inform their analysis. And, of course, a sincere thanks to the Annie E. Casey Foundation for their generous support to make the weekend possible and the expertise they offered from their many years dedicated to building a brighter future for young people. Collaborations like this that bring experts together across sectors, age and geography are exactly what make new solutions possible so we are grateful to everyone that joined us to make the weekend a success!


Source: DataKind – DataDiving to Support Youth with the Annie E. Casey Foundation

DataKind Named One of Fast Company’s Top 10 Most Innovative Nonprofits

Big news – DataKind has been named one of Fast Company’s Top 10 Most Innovative Nonprofits for 2017 and we have you to thank.

Part of the magazine’s annual ranking of the World’s 50 Most Innovative Companies, this list honors leading enterprises and rising newcomers that exemplify the best in nimble business and impactful innovation. We were humbled to be recognized in the nonprofit category, alongside truly inspiring organizations like our friend and past project partner GiveDirectly, fellow New York-based The Fund for Public Housing and The Movement for Black Lives just to name a few.

While our stylish orange hoodies almost certainly swayed the judges, we know the real reason we were selected is because of all of you.

Even more than data, our work is about people. As we tell our incredible volunteers and project partners at our community events or before they kick off a project – YOU are DataKind. Our work depends on our global community of over 14,000 socially conscious data scientists, social innovators, subject matter experts, funders and data for good enthusiasts of all stripes.

Thank you for donating your time and talent to apply data science, AI and machine learning in the service of humanity. This honor goes to all of you, dear DataKinders – congratulations!




Source: DataKind – DataKind Named One of Fast Company’s Top 10 Most Innovative Nonprofits

A maturity model for data evolution

In the last three years we’ve seen a notable improvement in how UK charities and social enterprises harness data.  We know that it can be a powerful tool for driving social change. However, we also recognize that adopting data on an organizational level is often a slow, laborious and sometimes painful process; one that typically entails a shift in thinking among leadership, acquiring new skills and talent, breaking down data silos and raising awareness about what data can do across an organization.

To help charities better understand and alleviate the challenges of incorporating data into their efforts, DataKind UK wanted to build a data maturity framework. In partnership with Data Orchard, a small UK-based research consultancy, we undertook the Data Evolution project to map out the journey towards data maturity. It was supported by Nesta, Teradata, Esmée Fairbairn Foundation and Access – The Foundation for Social Investment.

As part of the project we ran two workshops, surveyed 200 social sector organizations, carried out in-depth assessments with 47 people from 12 social sector organizations and developed a framework documenting the five stages we identified these organizations go through as they adopt new data practices and become more data savvy.

You can learn more about the project here and also explore the maturity framework itself here. If you’re interested in reading more about our data maturity initiative as well as similar work being developed for local government, here’s a great post we co-wrote with Nesta you should check out.


Image credit: Kelly, via Flickr (CC license)

Source: DataKind – A maturity model for data evolution

Data4Good Job Alert Roundup

If you’re looking for a job that lets you use your data and technology skills for social good, check out the selection of opportunities below we’ve heard about through the grapevine or stumbled upon online. Know of a great opportunity we missed? Tweet at us or email us at and we’ll share it.

DataKind is Hiring!

  • Our Executive Associate (New York) will be the right-hand person to our Director of Operations.

Other Great Organizations Are Hiring Too…


Source: DataKind – Data4Good Job Alert Roundup

Ingredients of a Thriving Chapter

By the DataKind Bangalore team

Happy New Year from DataKind Bangalore! As we head into 2017 and our third year as a chapter, we’ve been reflecting on the successes of 2016 and how much our community of over 1200 volunteers and project partners has accomplished together. But what makes a successful DataKind Chapter? For us, there are a few key ingredients. Check out highlights below and get excited for the year ahead!

1 – Volunteers That Embody Our Values

Volunteers are at the center of DataKind’s work. DataKind Bangalore is entirely volunteer-led, supported by a team of committed and talented people that exemplify DataKind’s values. Because they are always going above and beyond, we created the monthly DataKind Bangalore Awards to recognize their specific contributions. Get inspired by our November and December winners!

Chetana Amancharla
A Senior Technology Architect at Infosys, Chetana works on application development, software process engineering and program management. Chetana has been an incredible addition to the DataCorps team for Centre for Budget and Governance Accountability. She has been building and refining various data visualizations for the tool, polishing our user interface with her great eye for design and detail. And she does all of this on top of her career and Saturday classes, all while taking care of her 8-year-old son. Her knowledge, expertise and commitment is truly an inspiration for the whole community.

Sahil Maheshwari
Diversity and Expertise
An Engineer and MBA, a few minutes conversing with Sahil is enough for anyone to realize that he is an expert data scientist. With his wide ranging knowledge in statistics and probability, he has been instrumental in the eGovs DataCorps project. A fast learner, he’s also generous in sharing his knowledge and gave a workshop on statistics for the Chapter. His motivation to try out new things inspires all of us to do the same. We’re grateful to have someone with such a rich skillset and rich love of learning with us.

Suchismita Naik
An engineer-turned-designer, Suchismita has been leading design work for our CBGA’s DataCorps project. She exemplifies a great passion and commitment to the work and is always ready to try out those last-minute design suggestions (No matter how cumbersome they seem!) Apart from being the creative brain of the project, she brings great enthusiasm and vigor to the team, making her a fun and energizing teammate to work with.

Murugesan Ramakrishnan
A consultant at Fractal Analytics, Murugesan is absolutely fantastic to work with. With an immense will to learn and almost limitless energy, he keeps the eGovernments DataCorps team moving full speed ahead. He’ll git at 2am or on weekdays, blowing us away by how much he accomplishes in addition to his demanding job.


2 – High Impact Project Partners

Partner organizations are our vehicle for impact so we depend on their subject matter expertise to inform our volunteers work. We’ve had the honor of working with many incredible organizations this past year, but we’re especially excited to launch two long-term DataCorps projects in 2016 that will be wrapping up soon:

Centre for Budget and Governance Accountability (CBGA)
is a civil society organization that promotes transparent, accountable, and participatory governance, and a people-centered perspective in the preparation and implementation of budgets. CBGA has been building Open Budgets India, a data portal to make India’s budgets open, usable and easy to comprehend. The DataKind Bangalore team is co-creating a Story Generator Tool that helps users browse visualizations across various state-level fiscal indicators and schemes. The project is still in progress and the beta version of the tool is expected to launch in February.
Check out the source code and documentation >

eGovernments Foundation transforms urban governance with the use of scalable and replicable technology solutions. Using four years of data from the Chennai municipal corporation’s public grievance portal, we hope to build a problem forecasting and alerting system to predict trends and generate alerts at ward levels for better urban governance.
Check out the source code and documentation >


3 – A Community of Learning

Any good data scientist or social innovator embraces continuous learning, which is why we were excited to launch DataLearn –  a series of of talks, workshops and discussions that brought together some of the best names in the data science and social good community.

From creative hacks of Machine Learning – which viewed machine learning and artificial intelligence through the lens of creative subversion to Data Visualization and Storytelling with Data to the open data environment in India and ethics, we covered a variety of topics. We also hosted skill-building workshops, including statistical analysis with R, exploring data with pandas, text mining and Natural Language Processing and web scraping with R.

And true to our word about sharing learnings, we recorded many of these talks!

Check out our YouTube video series to learn more >

And The Last Ingredient? You!

In 2017, we are looking forward to exciting collaborations with more project partners, more values-driven volunteers and learning even more with our community, but we need you to make it a success! Stay tuned for more DataLearn sessions on Bayesian statistics and inference, time series modeling, developments in Deep Learning and more, as well as DataDives and collaborations with NGOs in interesting domains.

Join our Meetup to get involved! >

Follow us on Facebook and Twitter for updates and announcements!

Source: DataKind – Ingredients of a Thriving Chapter

A Big Welcome to DataKind’s Newest Board Member!

We’re thrilled to announce the addition of Elizabeth Grossman to DataKind’s esteemed Board of Directors, a team of top minds and dedicated champions in the Data for Good movement.

Director of Civic Projects in the Technology and Civic Engagement group at Microsoft Corporation, Elizabeth helps design and execute long-term, strategic partnerships for Microsoft that leverage technology to make a sustainable and scalable impact on local and global civic priorities. She has also worked on policy and societal impacts of emerging technologies and governmental science and research program design with universities and scientific societies as well as at the U.S. House of Representatives Committee on Science and the National Academy of Sciences. 

A longtime friend, collaborator and supporter of DataKind, Elizabeth worked with us on the very first DataKind Labs projects to advance the Vision Zero movement, to reduce traffic-related deaths and severe injuries to zero, in three U.S. cities – New York, Seattle and New Orleans.

Her knowledge and expertise in areas such as civic engagement, partnership design, smarter and more sustainable cities, research and technology policy, data sharing and government ecosystems will be indispensable in helping further DataKind’s work and mission, particularly on larger, civic and sector-wide projects like Vision Zero.

With the guidance of our devoted Board of Directors, now five-strong with Elizabeth, and the help of our talented and amazing volunteer community, DataKind finds itself approaching another phase of growth; with more staff, increased chapter engagement, and a thriving volunteer network – all paving the way for more projects and opportunities to harness the power of data science in the service of humanity.

Please take a minute to join us in congratulating Elizabeth and officially welcoming her to DataKind!

Source: DataKind – A Big Welcome to DataKind’s Newest Board Member!

A look back at DataKind UK's 2016

We’re sure many of you are looking forward to the festive season and waving goodbye (and good riddance) to 2016. Here at DataKind UK, we’d like to take a moment to reflect and appreciate all the good stuff that happened this year.

2016 was all about growth and impact. We doubled our number of staff by welcoming Lauren Smith as our Project & Events Coordinator and grew our brilliant team of Chapter Leaders with Kate Vang, Billy Wong and Gianfranco Cecconi joining Rishi Kumar. We got much smarter at selecting and scoping projects, as well as testing new event formats. We ran one-day DataDives for single projects. We experimented with DataJams – a day of data wrangling to better understand the data at hand. Behind the scenes, we’ve been working in partnership with Data Orchard to survey 200 UK charities and social enterprises, interviewing 12 of them to produce a data maturity framework that will be launched in 2017.


We’re pleased to have partnered on projects with the following organisations over the last year. We also provided light touch advice and support to a further 15 charities and social enterprises.


2016 Events Roundup

We’ve had a packed calendar of events from DataDives to DataJams. Find out more below!


DataDive: Cafedirect Producers’ Foundation



Meetup: When the rubber hits the road:

the highs and lows of small data


Workshop: Data Evolution London Workshop            

Workshop: Data Evolution Hereford Workshop


Meetup: When good algorithms go bad…

DataDive: Shared Assets & the Ecological Land Co-operative

blog post here


DataJam: National Council for Voluntary Organisations

Meetup: Data-for-good Summer Social



DataDive: Autumn DataDive




Meetup: data+visual

DataDive: Marks and Spencer

(Internal event for analysts and their charity partners)

blog post here


DataJam and DataDive: DataDiving into

Company Ownership with Global Witness

blog post here



Meetup: Who owns UK companies?   





Project Highlights


  • During a one day DataDive, the Cafedirect Producers’ Foundation (CPF) sought to better understand the smallholder famers they support. For example, the volunteer data scientists showed which factors correlate with higher incomes and how farmers adopt different agricultural practices and innovate. CPF continued working with one of our volunteers on a consultancy basis and they are now figuring out how to empower smallholder farmers to use their own data to inform their businesses.
  • Shared Assets are developing the prototype we produced at a DataDive with our friends over at Outlandish. They are building a platform to explore UK land data because good information on land is crucial to making good decisions about it. Many common good land users struggle to access the information they need e.g. who owns the land, what has it been used for, or where to find new project sites. The prototype pulls together dozens of open data sets enabling common good land users to identify and compare different sites on a range of characteristics, saving them time and money while helping them to make smarter, data-informed decisions.
  • Global Witness managed to get three separate organisations (Open Corporates, OCCRP and the Spend Network) to bring data to a DataDive in November. 50 data scientists descended on the newly released beneficial ownership data showing, for example, that thousands of UK companies are owned by other companies in tax havens and some of these tax-haven-owned companies are in receipt of government contracts.

Things we’re excited about in 2017


  • We’re busy prepping for a DataDive with the NSPCC next year in partnership with Credit Suisse (huge thank you to Ben Wilkinson at Credit Suisse for his personal donation to support this work).
  • Watch out Newport – we’re headed your way. We’ll be DataDiving with the Office of National Statistics next year.
  • There’s an exciting schedule of monthly Meetups starting on 24th January – save the date and sign up to our Meetup page to find out more.
  • We’ll be launching an organisational data maturity model for the social sector that we’ve developed with Data Orchard.
  • Plus we’ve got a couple of DataCorps projects up our sleeves. Volunteers will be needed – watch this space!


Source: DataKind – A look back at DataKind UK’s 2016

DataDiving with Marks & Spencer

Running DataDives is part of DataKind’s DNA. However, over the years, we have experimented with different formats and formulas. At DataKind UK, we’ve been partnering with Marks & Spencer, a UK food and clothing retailer, to run internal DataDives with them for three years running.

Similar to other DataDives, the event involves bringing together groups of volunteer data scientists and selected charities to work on data-for-good projects. Unlike other DataDives though, the events are not open to the public. Rather, they are attended by M&S’s internal data analyst community and invitations are extended to some of their suppliers.

On Thursday, October 27th and Friday, October 28th this year, 40 Marks & Spencer data analysts came together to help three fantastic charities: Oasis Community Learning, Shelter, and the Welcome Centre. After much coffee and number crunching, the assembled brain power produced some spectacular results. 

Check out highlights of findings from each project below!

Oasis Community Learning

“…It is the best level of human resources analytics that Oasis Community Learning has ever had and it is great to see the educational impact being clearly mapped to the turnover of our staff.”    
John Barnaby, Chief Operating Officer, Oasis Community Learning

Oasis Community Learning is one of the top three Academy providers in the UK with 47 schools across primary, secondary and 6th form serving 22,000 students with 4,300 teachers. Oasis wanted to look at their human resources data to understand staff turnover and absence, and what this means for pupil performance.

The volunteer analysts found that staff turnover was higher in schools with students that have special educational needs and English as an additional language. They found that primary schools spend twice the amount per day to cover staff absence compared to secondary schools. The analysts also found that primary schools tend to underestimate these absence costs. While these are all provisional findings that require further analysis, the DataDive enabled Oasis to see these patterns in their HR data for the first time and Oasis has accelerated their plans to become more data-driven.


“…The DataDive has equipped us with a set of ideas and insights that has helped to clarify which direction to head in to develop a deeper understanding of our clients...”
Dean Robinson, Business Systems & Analysis Manager, Shelter   

Shelter helps millions of people every year struggling with bad housing or homelessness through advice, support and legal services. They wanted to dig into their outcomes data to understand what happened to their clients. What is the result of their help? What are the changes for the client? How do these changes compare for different people accessing different services around the country?

The M&S analysts dived in and, in no time at all, whipped up an interactive dashboard to enable Shelter staff to explore these very questions. The volunteers looked at the number of hours Shelter staff spend delivering services in different parts of the country. They also explored the rate at which cases were dealt with. For example, those over age 65 are more likely to have their cases resolved than those aged between 25 to 34. Shelter’s business systems team was thrilled, and they have even started learning R, a data analytics programming language!

The Welcome Centre

“A very well organised and structured event, the outcomes of which will make a genuine difference to our organisation’s business processes…”
Andrew Tomlinson, Trustee, The Welcome Centre

The Welcome Centre is a food bank in Huddersfield and South Kirklees that supports people experiencing crisis through practical help. They wanted to understand their clients better and identify those who would benefit from additional support, advice and referral to other services. In particular, the Welcome Centre wanted to know who is most likely to become a repeat user of the food bank, as those individuals tend to need extra support.

The all-star team of pro bono analysts got to work and were able to find factors that predicted how likely it was that someone would need extra support. Based on a person’s age, their number of dependents, and the reason for their referral to the foodbank, we can begin to predict the kind of support they will need. The Welcome Centre is looking to develop the model further so they can identify who needs support earlier, what future demand for the service might be, and to test hypotheses for which interventions work best with which clients. 

A huge thank you to Marks & Spencer’s Plan A team and to Pete Williams, Head of Enterprise Analytics at M&S, for driving another successful DataDive. We look forward to next year’s!

Source: DataKind – DataDiving with Marks & Spencer