On Saturday morning and Sunday afternoon I attended the DataKind DataDive in London.
Tracey from Lancashire Women started with powerful footage from a couple of service users who the charity had helped when they had become isolated and depressed. Lancashire Women work with people to unpick adverse childhood experiences. With their data set they wanted help to understand what was working and how to deliver services that are the most beneficial.
Anthony Nolan save the lives of people with blood cancer by providing stem calls to people in need. Their process involves potential donors signing up to a database, and then when a match is found with someone in need there is a follow up for further checking. Forty percent of initial sign-ups do not continue to making a donation.
Laura Bunt and Jo Bevan talked about AddAction, who help people with addiction and mental-health related issues. More people are dying from addiction-related issues. Jo articulated one of the objectives as “If we know something works really well, how do we influence people to do things the same way?”.
Ruth told us about FareShare, who work with people and charities to distribute food that would otherwise go in the bin. Some families have hiked two miles across town so they can get a hot meal.
While we all have bills to pay, I believe those of us with tech-related day jobs can and should apply our skills to help others.
The DataKind Process
This was my first Data Dive, and I was there to understand how the DataKind process works, as well as how my experience could match with what they need. Technically, it seems to be Python and related data science libraries, using different kinds of plots to explore the data, linear and logistic regression and geo-mapping. DataKind work with the charities for six weeks prior to the Data Dive to clean up the data and establish what questions are feasible based on the available data.
Asking The Right Questions
I recently finished reading Seth Godin’s new book, This is Marketing (which is a different kind of marketing, based on trust and empathy), and it struck me while listening to the stories of those in need how important it is that we’re clear on what is the change we seek to make (for those we seek to serve). Any product or service we create, whether for-profit or not-for-profit, needs to be based on really understanding the needs of the user at a deep level.
For the DataDive, the charities had a number of questions prepared to focus the analysis of the Data Scientist, and the teams working through these until the evening on Saturday, continuing on Sunday morning.
Day Two Presentations
Due to the sensitive nature of the data, all attendees signed a Non-Disclosure Agreement so I’m unable to report on the data or the findings.
However, all of the charities had actionable insights from the weekend’s work, and some seemed surprised at how much could be achieved by a team of dedicated data scientists in that time.
Find out more about how you can volunteer for DataKind.