Dealing with Development Data
Enterprise data for large organizations and companies in the Western world reminds me of cattle wrangling. An orchestrated dance between man and beast, with teams of experienced handlers with help of a trusted Border Collie, getting an unruly mass of high-value commodities from one place to another without losing any volume, protecting the herd from vultures or poachers… just like dealing with consumer data!
Dealing with data in the international development space is more akin to more rustic herding mentalities- that of the lonely shepherd on the hillside. Often equipped with only a staff, his herd is a lot smaller and not nearly as powerful. But it is no less valuable- the lifeblood of his well being- and usually just as unruly as the stampeding cattle herd!
This mindset of being the small, under-equipped Shepard hamstrings the development sector from truly leveraging the data revolution that is happening all around us (even in the commercial sectors of the same emerging markets we work in!). ICT4D evangelists have pushed digital data collection and evidence-based-decision making for years, but the use rate by technology luddites and non-early adopters has been less than encouraging.
So what is the problem? Why can’t we catch up to the big data users?
An informal survey of 20 projects I advise has brought to light the underlying issues preventing development professionals from leveraging the rapidly expanding market of products/apps/tools for modern data management.
We don’t know what tools are out there.
We don’t know how to use them.
We can’t afford them.
Good news: All of these hurdles can be overcome.
Bad news: There are dangerous pitfalls on the other side that are easy to fall into.
We don’t know what tools exist.
This was a major challenge 5 years ago that was hard to move past, unless you were a well-networked tech junkie who loved to try out apps in their free time. Today, there are a plethora of established tools on the market that (sometimes aggressively) market to development professionals. Donors have bought into platforms for data management, like DevResults, or formed partnerships with big software providers, like USAID & Microsoft.
Pitfall: Buying into the wrong technology.
As technology service providers expand into the development marketplace, it is easy for organizations or projects to get swept up in the “shiny bauble” pitches that are notorious in tech, without due diligence to understand if a particular product or app will really meet their need. Always, ALWAYS shop around before committing to a new product. Social media can be a great platform for getting unbiased feedback on a specific tool — search Twitter using a hashtag for #YourPotentialProductSolution to see what other users are saying.
We don’t know how to use the tools.
Youtube has a lot more to offer than just cute animal videos and highlight clips from reality TV. Just about every ICT solution or data management product on the market has “How-to” videos online that can give you a crash course and make you an expert in no time. As Quincy Larson preaches to his students at freeCodeCamp : Read-Search-Ask. Read through any blogs or instructions provided by the tool developer. Google is your best friend to find answers, if your reading materials don’t offer a solution. In most cases, you aren’t the first person to have a question about a software solution or app — somewhere on the internet someone has asked your question and (hopefully) shared a solution. Still can’t find an answer? Use the #ICT4D hashtag on Twitter to find experts that may be able to point you to the right resource.
Pitfall: Having just enough knowledge to get in trouble.
It can be relatively easy to find an answer to one problem you may run into. But many implementers find themselves running into bigger challenges that their limited knowledge can’t resolve. This can cause major problems for project activities — especially when you are in the middle of an important data collection exercise or have a report due tomorrow! If your organization is serious about using technology for data management, it is critical to invest in training and capacity building. Like all specializations, data management is a deep field and requires time to master. But don’t dismay — groups like TechChange offer a plethora of courses on using technology in the development space. Plan ahead, build the skills you need, and this pitfall is easy to avoid.
We can’t afford the tools.
Economics are our friend, especially as commercially available data management solutions become available in developing markets. With a little planning, good data collection, storage, analysis, & visualization tools are no longer out of reach for even the smallest of projects. Free, Open-Source options are wide spread, but even for-fee tools have become affordable — with good planning, an entire data management ecosystem can be deployed for as little as a thousand dollars per year. Big names in data storage, like SalesForce, even offer discounted rates for humanitarian organizations. Scaling pricing models across the board have made it easier for those of us with smaller (but still valuable!) data sets to utilize the same “Big Data” technology products as major corporations.
Pitfall: Spending too much on technology you don’t need.
It is easy to be wowed by the features of a new tool without realizing that what you are paying for won’t work in the rural low-lands of Ethiopia or deep recesses of the Amazon. Even worse, we pay too much for a Cadillac when all we need is a Fiat. Sit with your project managers and come up with a list of must-have features & functions before shopping for a technology. And when you find your dream tool, make sure that you aren’t wasting money on things you won’t (or don’t have the capacity to) use.
Does your team need a hand to deal with your development data?
Reach out to us today for a quick brainstorming consultation.
