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How Your Data Can Save the World (Seriously!)

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How Your Data Can Save the World (Seriously!)

When you tell some one about something you're passionate about and they brush it off, it can be frustrating. But maybe data can make them more understanding.

· Big Data Zone
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Ever tried to talk to someone about a cause you’re passionate about only to have them shrug their shoulders and quote some stat about how small a percentage of your donation really makes it to the people at the end of the process?

If you work for an NGO or a non-profit or you manage philanthropic/Corporate Social Responsibility (CSR) initiatives for your company, I’m guessing this argument makes you want to tear your hair out.

After all, those of us that live in the real world know that it’s impossible to enact change without substantial costs — that no matter how much you want to channel every penny into the field, you also have to pay salaries, overheads, marketing and so on, exactly as if you were running a commercial operation. And that inevitably cuts into your budget.

What’s more, you went into this field to make a difference, not to make a fortune. The third sector is a behemoth driving force for change, tackling sweeping global issues from disease control, economic inequality, refugee crises and the devastating impact of climate change through access to education, employment opportunities and the arts. Areas that, typically, the private sector doesn’t touch because there’s no money to be made. Without your dedication and tenacity, the world would be a far worse place.

But here’s the thing: Deep down, do you also worry that maybe — just maybe — the naysayers do kind of have a point? Are you absolutely certain you’re being as efficient as you possibly can? Are you minimizing costs and eliminating waste wherever possible? Are you planning ahead to make sure your resources are always allocated in the smartest way possible, avoiding things like production bottlenecks and last minute transportation costs at one end, and over-supply and storage costs at the other?

In other words, since you have many of the same financial responsibilities as a business, are you also behaving like one? Are you as ruthless about stretching the value of your funding as corporates are about maximizing their profits?

…If not, you’re doing yourself, and your stakeholders, a disservice. Think how much further your efforts and your donors’ dollars would go, and how much more you could offer those that rely on your help if you were able to strip the inefficiencies out of your operations.

Think how much you could reduce stress and frustration, raise productivity and morale (and prove your critics wrong!) if you had a clear, effective system in place to cut the chaos and keep things running like a well-oiled machine.

That’s all very well…

But How? I Hear You Cry!

The simple answer is: by leveraging invaluable data to get a better picture of how your organization functions and better predict its needs in the future.

Of course, in real life, the solution is never quite that straightforward. Here’s how data engineer Mallory Solder summed up her data challenge at The World Food Program in this awesome TED talk:

“You have 30 possible foods, and you have to pick five of them. That’s already over 140,000 different combinations. Then for each food that you pick, you need to decide how much you’ll buy, where you’re going to get it from, where you’re going to store it, how long it’s going to take to get there. You need to look at all of the different transportation routes as well. And that’s already over 900 million options. If you considered each option for a single second, that would take you over 28 years to get through. 900 million options.

So we created a tool that allows decision makers to weed through all 900 million options in just a matter of days. It turned out to be incredibly successful. In an operation in Iraq, we saved 17 percent of the costs, and this meant that you had the ability to feed an additional 80,000 people. It’s all thanks to the use of data and modeling complex systems.”

Consider those figures for a moment: 17% reduction in costs. 80,000 more people fed. Decision-making that could take years, reduced to days.

It’s not just the World Food Program that’s catching on to the value of Big Data analytics and rapidly generated insights to improve the way they work, either.

For example, Crisis Text Line uses machine learning to help prioritize messages that get the most urgent human attention, helping to cut response times to high-risk texters from 120 seconds to just 39. Unicef is now using data science for large-scale projects ranging from tracking the movement of child refugees in Somalia (in order to better plan and allocate resources), through to understanding the patterns in Brazil’s alarming child murder rate that may help to identify and protect children at the highest risk.

Meanwhile, many other NGOs are using data analysis to improve their fundraising strategies, improving performance of their marketing and new sign-up teams, and cutting down the cost of onboarding each new donor.

These are data-driven approaches that create instant, real, life-saving results. That can ease your workload while allowing you to be vastly more effective.

But I’m Not a Data Scientist!

Me either. And here’s a little secret: you don’t have to be. As powerful, self-service business intelligence becomes increasingly available to organizations of all sizes and budgets, it’s becoming ever more possible to link up your data sources, run queries and draw out invaluable insights in near to real time, without the need for IT assistance.

But I Don’t Have the Right Data!

Ah-ha! Here’s where it gets interesting. More and more companies are shifting from straightforward donations to opening up their vast data assets to help NGOs achieve their goals. Called Data Philanthropy, it might just be the single most important shift in collaborations between the private and third sector — with the most profound impact on global development.

Take, for example, Facebook’s collaboration with The Red Cross and other leading organizations to create “disaster maps” using aggregated location-based Big Data. Here is a prime example of a billionaire corporation gifting its incredibly valuable data to the charities that need it, creating far greater value than a direct financial donation.

Then there are data science groups like Scotland’s Data Lab and Chicago’s Genomic Data Commons, the former of which encompasses the country’s leading data brains and the latter of which brings together one of the world’s largest resources of cancer-related data, making these skills and resources available to the causes that need them.

When it comes to getting hold of the data you need, appealing to the companies that have it for data philanthropy rather than (or as well as) monetary support could prove to be a mutually beneficial partnership – and an easier sell than requesting a check.

But How Does Data Analysis Work in Practice?

Take one of our own clients, Amadip-Esment.

For over 50 years, this Spanish NGO has provided people with disabilities with housing, workshops, leisure activities, training, and employment, collecting vast pools of data from sources including sensitive medical information, in-house operational software, a financial ERP, and their partners’ systems. To inform managerial decisions, the team had been manually inputting all of this into Excel spreadsheets and using pivot tables to draw out insights, which was incredibly slow and ineffective.

By switching to Sisense, they were then able to centralize and harmonize all this data without IT expertise, customize dashboards and run ad hoc queries, so that managers could quickly identify what was working, where efficiencies could be made, and streamline their planning for the coming months.

Future-Proofing Your Efforts

Financial efficiency doesn’t always come naturally to those working to solve the world’s biggest problems. After all, if you’re figuring out how to conduct emergency surgery in a war zone, shaving 10% off the amount you spent on bandages probably isn’t your major concern!

That’s understandable – but it isn’t sustainable. These are turbulent times for third sector funding. Keeping down costs, effective resource planning, anticipating cash flow hiccups and predicting times when demand for your support with soar are all essential ways to survive. By taking a smarter look at the data at your disposal using fast, intuitive BI systems, you’re better equipped to steer through budget pressures, identify ways to improve and convince donors that their money is in safe hands.

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Topics:
big data ,nonprofits ,machine learning ,data analytics

Published at DZone with permission of Shelby Blitz, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

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