By Ajit Dayal – Founder, Quantum Advisors and HelpYourNGO

My conscious journey as a novice ‘philanthropist’ began in 1992 when I started donating money based on a simple formula: my company allowed me to travel in business but I travelled in economy, I worked out the fare difference and agreed with the company to donate the money saved from my lower travel bills to charity. Over the past three decades of being in the periphery of the charity world I have witnessed an evolution: the passionate innocence of a desire to give has turned into a lexicon of complex analysis — complete with diagrams and charts — to evaluate whether the soul of the recipient of an act of goodness by a donor had been altered in depth, breadth and resiliency.

Data and data analysis is important, I get that. My ‘day job’ as a fund manager investing in the stock markets is to analyse the annual reports of companies and — using base data and assumptions — evaluate which stocks are a good investment. In fact, 20 years ago, we took the template that we used for analysing publicly listed securities and built HelpYourNGO — a powerful database and search tool for evaluating, comparing and donating to India-based NGOs.

Data is good. The difficulty arises when data is used to try and make judgements on the effectiveness of monies granted to one charity versus another charity — and when this measurement is used to determine a result. For example, the HelpYourNGO database may list a charity which helps children in Mumbai and another one which helps children in Patna. How do you evaluate whether GBP 100 given to the Mumbai charity was more (or less) effective than the option of giving GBP 100 to a charity in Patna? It’s like comparing the cost of operating a business in London v/s Lancashire. The salaries of staff are not comparable in the two geographies. The rental costs are not comparable. The cost of providing food, clothing or shelter to the children in the two cities is not comparable. A metric that looks at “lowest cost to feed a child” would skew money towards Patna, or Lancashire. And what metric would one use to measure the smile of a child in Mumbai who was given a hot meal (as against a daily option of looking for thrown away food in a garbage bin) v/s the smile of a child in Patna who was given a hot meal (as opposed to picking some wild fruits or berries from a tree)? Can you measure the “delta” in each smile and work out the impact of the GBP 100?

The art of giving used to have a touchy, feely, cottage industry aura about it, where there was a geographical or emotional connect between the giver and the recipient. Measuring the impact was not a point of discussion — knowing that there were a few more smiling faces in the community seemed like a good enough reason to help. Is the cottage industry of philanthropy now an industrial farm which has distanced the producer from the consumer? Like the transporters of farm produce and cold storage supply chains, a plethora of intermediaries, consultants and handlers — each with a good intention of seeking efficiency — may deliver a more impactful end result to a nameless beneficiary who can rarely taste the freshness and goodness of the donor’s intent.

It is the avowed objective of many to model NGOs on the likes of large corporations and build Olympic Champions. The logic is: size is scale, scale is efficiency and efficiency will translate into a happy donor and grateful recipient. These enterprises are staffed with ‘managers’ who devour data and conjure reports based on the philosophy of William Kelvin that “What is not defined cannot be measured. What is not measured, cannot be improved. What is not improved, is always degraded”.

The yearn to industrialise the art of giving has resulted in an army of robotic, number-crunching soldiers who may not have the humane touch-point of the cottage industry’s crucial last-mile connect with a beneficiary. For every statistic of a numbered beneficiary in a spreadsheet there used to be a hand that held out hope and comfort. Scale makes human touch more difficult — scale seeks a cold, robotic approach to measurement of quantity with a struggle to evaluate quality.

In HelpYourNGO we aimed to find a balance between data, measurement and the preference for a cottage-industry approach to helping. We standardised data across NGOs operating in various focus areas and geographies. We measure what we can measure and pass no comment or judgement on the generated number. For example, donors can see the percentage of their GBP 100 donation that made it to the eventual beneficiary and compare this with the similar ratios for other NGOs in the database. They may wish to junk that data or use it to make a decision. We keep the desire to connect the donor to the beneficiary not only by reporting on the progress of the NGO they may eventually fund but also by giving the donor the option to donate to an NGO in or near the postal code or city where they live or grew up: familiarity breeds empathy and connect.

In Glasgow, COP26 focused on the challenge that economic growth for the sake of growth is a dangerous path to follow as it can lead to an unstable planet. Similarly — as members of Philanthropic Impact — we need to find the balance of powerful data gathering and data analysis (which helps us trace what has happened to monies or grants given in the past) and learn how to use that to decide on whether to release the next grant or not — or donate somewhere else for “efficiency”. That delicate balance between the need for data to evaluate where money flows without trying to measure all that is not measurable is the challenge before us.

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