For all the talk of big data, how many nonprofits, foundations, and national associations truly have the capacity to use it in a way that could find innovative new ways to tackle some of the most critical issues of our time? This might be the case for larger foundations sitting on billion-dollar endowments. But even then, they are focused on larger ROI in developing countries or newer industries where they can move the needle.

As we continue to see rapid growth in this digital age, small to medium organisations continue to double down on the status quo with limited capacity software supporting a glut of program managers, mar-com staff, and grant officers with visualisation tools that simply highlight the problem through a more focused lens.

This is a missed opportunity given that tech exists now that can identify new patterns that could determine a totally different approach to solving the issues people have dedicated their careers to within these organizations.

The origins of explaining big data were not initially applied as a term as they are today, but more of an adjective on how to tackle a problem. This drift in interpretation has ultimately affected the social sector’s approach, with folks selectively using data sets to reaffirm their own symbolic reasoning and process in solving a particular problem.

Philanthropy is changing. The vehicles through which funds are being invested are changing. Philanthropy is transitioning from funding as a charitable transaction to one with a social justice lens at its core. To adapt to this paradigm shift, the sector is going to need new voices, experiences, education, training, and expertise when it comes to executing these dynamic new takes on how we support programs and projects looking to deliver real impact for those they serve. And it’s not just the type of staff that will need to change. It’s also the jobs that support the work.

The accumulation, sorting, analysis and reporting is one area that will help drive this change. A mindshift from outputs to outcomes and an understanding of your work beyond the narrative you have crafted. But there is a trap out there just waiting for those looking for the quick fix…

You can invest in data technologies and collect all the data you can possibly imagine, but it’s worthless if it’s not analyzed or communicated to decision-makers so that action can be taken from the insights. Some organizations attempt to communicate data findings across departments of an organization, but something typically gets lost in translation as it makes it way from the data scientists to the executive decision-makers. This issue is so prevalent that only 18% of companies believe they can gather and use data insights effectively, according to a McKinsey survey. Due to this reality, some organizations have opted to add a data translator to help bridge the gap.

The above excerpt was very much business focused but have many lessons for the charitable sector and that’s in the translation of data to help inform better and more impactful decision making. 

Looking again at business applications for an insight into market shifts, did you know that Kmart Australia recently hired a team of 10 ‘data translators’ that sit embedded within its top three operational areas to improve traction and take-up of analytics?

CIO Brad Blyth showcased the retailer’s efforts to build its data analytics maturity internally by sharing that Kmart is in a constant “three-phase development cycle” for its analytics capabilities – “trying to understand the problems and establish solutions; scaling that up; and then really trying to drive the value out of whatever we’ve built there.”

The following excerpts from Blyth at a recent AI Summit definitely shared some insights that could be relevant for the social sector moving forward.

“Like all good tech organisations, the minute we got our access to some funding, we went off and started building things, and we had a very much ‘build it and they’ll come’ mentality that we tried to push through,” Blyth said.

But the business was often indifferent to what was being presented to them.  

“In the early days, we really didn’t get a lot of traction,” Blyth said.

“We started thinking about what we are missing here, and really there was a communication problem.

“The people who had access and could build the solutions didn’t really understand the problems, and the people that had the problems didnt really understand what was possible.”

The solution was to hire and embed “data translators” into key parts of Kmart – people whose job it was to understand the problems and articulate them in a way that made them understandable as data problems.

“We’ve seeded data translators in our top three operational areas – online, stores and merchandise,” Blyth said.

“They understand that area of the organisation. They’re close to the P&L and close to the problem spaces, and they have the necessary skills to articulate it in a way where we can start solutioning and coming up with a hypothesis of how we could potentially problem-solve for this.”

Blyth said there are now 10 data translators. He said their impact was immediate.

“The minute we put them in, something amazing happened. There was an unlock,” he said.

“We had a 400 percent growth in three months in our backlog – this is all the ideas that we collected, potential things that we could chase and generate value with. 

“For each single one of those we noticed a dramatic increase in the amount of benefit that we thought we could go after. This really helped drive that establishment piece.”

So what are data translators and how might they be helpful to the for purpose sector in addressing some of the defining social issues of our time?

The clearest definition I found as to what exactly is a data translator and what are the key skills required to be one came from an article written by Louise Maynard-Atem and Ben Ludford who shared that:

A data translator is someone who can bridge the gap in expertise between technical teams, made up of data scientists, data engineers and software developers, and business stakeholders.

From a nonprofit perspective those groups will be less technical and more programatic, but will help inform leadership to make better decisions.

And that’s what we are in need of. Someone to make sense of the data objectively, stating what it shows, what it means, and what it means for the organisation. There are some organisations I know that do try and interpret the data but the stats are cherry picked to reaffirm current strategy and on many occasions layered with nothing more than assumptions with a heavy dose of bias.

These roles don’t have to be that explicit in the non-profit realm either. A program manager that has the following qualities could be charged with translating data from it’s IT/Tech functions through to the relevant decision makers.

  • A desire to ask questions and get a deeper understanding of issues (mission and data/outputs and outcomes)
  • The confidence and authority to challenge perceptions and biases of individuals at every level of the organization
  • A solid understanding of sector wide requirements and vernacular
  • Analytics knowledge or desire to acquire it to be effective communicating with data scientists
  • A passion to give others on the team an advantage of understanding the work and outcomes by using accessible language

An amazing primer for what data translators are and what they might do for your organisation can be found here – Forget Data Scientists And Hire A Data Translator Instead? By Bernard Marr for Forbes.

Data translators in the future are people I see based within the programmatic areas of for purpose organisations. They will also form a critical partnership with fundraisers who you all might have heard me call knowledge brokers. They share similar skills and traits but have vastly different outcomes. 

Knowledge brokering is a role that acts as a connector and interpreter of new and emerging concepts, acting as a bridge for people seeking answers to questions on one side and those who have the answers on the other. The defining traits include translating technical info or hard numbers into something more accessible and understandable and providing links to knowledge, market insights, and research evidence while helping to convert that into practical tools, actions, and narratives. This role is becoming increasingly important because knowledge is a pre- cious commodity these days, especially with the rapid advances in technology and the way we do, understand, and interact with things.

Whether we’re discussing data translators or knowledge brokers, the sector would benefit from some professional self-definition of these kinds of actors moving forward. 

Data, when defined, has the ability to help guide our decision making in tackling some of the biggest issues of our time. And over the next few years, it will become more readily digestible and available for future-focused groups that truly want to solve these existential problems. Philanthropy has a big role to play in bringing data into the mainstream, whether that be through direct funding, advocating for or supporting public philanthropic partnerships that use it to inform and de-risk large-scale investment, or simply by being a trusted vehicle for its reporting (think community foundations, economic development corporations, and industry groups).

So, let’s not be afraid of investing in things that may challenge our thinking and our approach, and let’s reinvent the missions of our organisations so that they can be more successful and profitable for decades to come.

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