January 19, 2022

Paternity Leave — Why Does It Matter?

Day 1 of my paternity leave. We didn’t know where to place her, so we made a pop-up bed in our living room, and the dining table became her first bed.

Gojo recently developed its leave policy by which everyone is entitled to 14 weeks maternity and paternity, 100% paid by the company up to a certain amount. According to our study, it is the most generous of this kind. I became the second person inside the organization to use it, and I was away from the office from late September until late October (I wish I could make it longer!). I am not alone — during the pandemic period, Gojo members are seeing a baby boom, and some more will take it soon. 

Let me write about why we developed this policy and the things I hadn't realized before taking the leave. 

A good parental leave policy is essential for pursuing gender parity in society. The gender pay gap is insignificant when both men and women don't have kids. The gap conspicuously widens after they become parents. In many countries, only women take maternity leave and look after the newborn babies, and their role tends to remain fixed even after the end of the maternity leave. Thus the gender gap widens. To prevent this from happening, both men and women should take ma/paternity leave. 

Not only that. A strong leave policy makes the organization more sustainable. Che Guevara used to say something like, "no one is irreplaceable." Organizations should be able to run just as well even when key people are absent, including the founder CEO. 

However, after taking my paternity leave, I learned a few more things. 

First, I learned that it is an extreme joy to spend time with a newborn baby. Her face changes literally every day (I took a photo every single day, so I am sure). I learn something new about her every day, and vice versa. I felt that every input I gave to her impacted her development. It is a fantastic experience that all parents ought to enjoy. 

Second, it makes a happy family. Especially under covid, even husbands are not allowed to spend the first several days with the neonatal baby. These days generate a significant “parental IQ” gap between women and men. If men don't take paternity leave, it is almost impossible to catch up. The result would be that wives always look after all kids-related matters, and husbands cannot be involved (some are deliberately not involved). The grudge gets larger every month. In the worst-case scenario, husbands become isolated from their family members. Some Japanese men told me things like, "after I became a father, my wife started focusing on kids only, and I felt like I became an ATM." In Japan, many old-age divorces are due to kids-related matters. It is a sad thing — they loved each other to the point of getting married, and the result of the marriage becomes the cause of divorce. 

If you take paternity leave and actively join kids-raising, you will not experience this problem. At the very least, my relationship with my wife got even better after having a baby. 

Third, after skipping the company's Executive Committee for 5 consecutive times, I confirmed that even without me, the organization would get going. I read the meeting minutes and watched the meeting videos, realizing that all the key problems are raised and analyzed well, and all the required solutions are executed. 

The experience made me think about what is my raison d'etre. As the founder CEO, I am here to bring about non-linear change to the organization, delivering something the other colleagues cannot do. Following my period of leave, my work time allocation changed considerably, and I see some positive results already. 

We are always looking for talent. If you are interested, please visit our website! https://gojo.co/join-us


Taejun is the co-founder and CEO of Gojo. He is passionate about equality of opportunity. Prior to founding Gojo, Taejun worked in investment banking and founded Living in Peace, an NGO.

December 3, 2021

Shifting Your Career to Serve a Social Mission

In this post Haruna, a member of Gojo's Corporate Planning Team, shares her career journey until she joined Gojo, and what she learned in the process. Enjoy!


Some members of Gojo's Tokyo office during a party. Haruna is the left-most person in the front row.

What does “work” mean to you? It means a lot to me — as someone once said, more than half of your time awake is time spent at work, so it should bring joy. I fully agree with this statement. In my view, it should not just bring joy, but also be meaningful. Today I will share my journey on how I built up my career, what my struggles and lessons learned were, and how I eventually decided to shift my career to pursue my original hope of serving the developing countries. I hope it will be interesting to those who are thinking about shifting their career, especially in a more “social” direction.

When I graduated from university, I questioned myself, “what do I want to spend my time on?” I wanted to make sure I spent time on something I thought was important, and to me, at that time, working to improve the life of poor people in developing countries felt much more impactful than spending time to bring marginal value to already somewhat-fulfilled people in Japan. So I started looking for a government job to support developing countries. However, I could not get an offer and, when I got my first offer from a consulting company, I stopped searching. At that time, I wanted to focus on my university orchestra activities and wasn’t thinking very seriously about my career and future, so I ended up starting my career as a strategy consultant.

The experience was terrible. Very long working hours, no proper training, a bad relationship with the manager all piled up to become a lot of stress. I started getting both mental and physical issues, and had to take leave of absence. I went back to work after 3 months, but was asked to leave the company at the end of my third year.  

I quickly searched for a new job. Luckily, because of my “strategy consultant” background, I got a lot of offers. I chose to go to a company called Rakuten, a Japan-based e-commerce company, which was trying to go global at that time — including developing countries in Asia and Africa. I thought that maybe this job could connect one day to my original wish of serving the developing countries.

This job change turned out to be a success. I worked closely with the CEO and had a chance to see the company from his view, which was a whole new experience for me — it definitely pushed me up to a different level. I started to enjoy work for the first time in my life, and started to feel that I was making a difference. I increased my presence within the company and was soon promoted to become one of the youngest business heads. I had a lot of struggles there too, but really enjoyed growing the business supported by a great team. Moreover, I loved the people at Rakuten. Everywhere, there was the culture of moving fast, getting things done.

However, even though my career at Rakuten was successful, I started to question myself again, the same question I asked myself when I had first started my career: “what did I really want to spend my time on?” I hadn’t forgotten my initial aspiration of contributing to the people in developing countries. I tried to chase this dream within Rakuten by raising my hand to meet startups in India, visiting Africa to find business opportunities etc. I also started looking outside to find things to do outside work to fulfill my wish — I joined a network of professionals supporting social startups, and I started to volunteer for an NGO supporting children in Africa. I even started a similar kind of program within Rakuten, an accelerator to support social startups by Rakuten employees.

I could have continued like this, but once I experienced the deep sense of achievement and fulfillment by putting my energy into something to which I was really committed, it was hard for me to fully focus on my assigned job at Rakuten. I decided to shift my career to pursue my original mission — to support developing countries and reduce poverty. It was a tough decision. I had to leave behind 10 years worth of social credit I had built, a good salary, a stable job which I knew how to run, a managerial position — basically a successful career.  People said I should continue at Rakuten, especially as I had just given birth to my second child, and I was already going through a lot of changes in life. I could understand this argument, but one day I asked myself: if I died today, would I have any regrets or not? The answer was clear: I would regret not having spent my work time on something I thought was meaningful.

So here I am at Gojo & Company, a startup with a mission to extend financial inclusion to everyone, so that people can determine their own future. The mission resonates with my personal values, and so far my 6 months at Gojo have been great. Of course, there are pros and cons, and there never is a “perfect job”. My salary went down significantly, and I need to work more. Lots of new things to learn, a new culture to get used to, new people to get to know — all of this requires hard work. Having said that, the best thing here is that there are like-minded people around me who take social impact seriously. There are so many things which I can tackle that seem interesting and important — the kind of things I really pushed for at Rakuten but never got management attention can easily become an important project here at Gojo.  Although it might be too early to tell, I think I managed to make a successful transition.

Aligning your personal mission with the company’s mission may not matter so much if you think about your day to day work. Having a good relationship with your colleagues, working on a fun yet challenging job, and having good work-life balance matters more in the short run. But if you stop and look back on what you have achieved, and see that it is exactly the impact you wanted to make on the world, there is a deep sense of satisfaction. So, I want to encourage those who are hesitating — “it is never too late to pursue your mission!”


Haruna Tanaka works for the Corporate Planning Department at Gojo & Company.  She works on various projects at Gojo, including corporate governance, social performance management, stakeholder impact management, client impact measurement and R&D.

November 16, 2021

Governance, Decision Making, Leadership and Microfinance

As I was getting involved in microfinance in the late 90s, it was mainly operated by 2 types of players: Non-Profit Organisations (such as NGOs and International NGOs) and Cooperatives. Most countries had not yet set up regulations to allow commercial microfinance banks to operate.

I remember the significant opposition against commercial microfinance by many players in the microfinance sector. Many donor representatives but also a large number of practitioners did not feel comfortable with the commercial model. The cooperative movement was perceived by many as the “ideal” model, allowing the end beneficiaries to be part of the governance of the microfinance banks to decide on their services. Cooperative systems were perceived as superior models.

Beyond the governance, it is also clear that private ownership in microfinance was not accepted for another reason. The idea that private interest could generate profits from “poor people” was unacceptable to most.

As I co-founded PlaNet Finance in 1998 with the support of Jacques Attali and Muhammed Yunus (Chairman of the Advisory Board) and started providing independent rating & evaluations in the sector, as well as other services (consulting and funding), we started evaluating and financing many MFIs. 

As we were doing so, in the early 2000s, we witnessed many cooperatives failing. In West Africa but also in Latin America and other parts of the world, large cooperatives were bankrupt or nearly bankrupt, only being saved by governments and development agencies providing them every year with the funds they needed to survive. At this time, I got involved with PlaNet Finance & PlaNet Rating in many programmes with cooperatives, either to try to support / save some of those cooperative microfinance banks by providing them with technical assistance (such as in Mexico for instance) or to rate and evaluate them and allow governments or donors to design programmes to support them (such as in West Africa)

A shopkeeper in a transaction with a client in Madagascar / Arnaud Ventura

For years (mainly in the late 80s and 90s), a number of international cooperative movements such as Desjardins International, Crédit Mutuel International, WOCCU, were promoting the models that had worked in their home countries internationally by supporting local microfinance cooperatives with expertise and funding..

However, during the 2000s decade, commercial microfinance emerged and started growing at an accelerated pace, to become during the 2010s the main player in the microfinance sector.

How come commercial microfinance was able in less than 10 years to thrive while cooperatives did not manage in the previous 30 years?

There are probably many reasons behind this factor but I would like to highlight 2 of the reasons which I believe are fundamentally behind the success1 of commercial and the failure of cooperatives models in microfinance:

  1. The efficiency of commercial microfinance. This efficiency is largely the result of efficient decision making which private companies with simple and aligned shareholding bases and clear decision makers excel at doing. Cooperative microfinance banks are often struggling with complex governance, many hundreds of owners (the clients) with different and sometimes conflicting agenda which makes decision making much more complicated and sometimes impossible. In specific situations, a strong leader is able to make this governance structure work and can, thanks to his/her natural authority and/or his legitimacy, accelerate decision making. This was for instance the case at Grameen Bank, a cooperative bank with a strong charismatic leader, the founder: Muhammed Yunus. However, unfortunately too few cooperative microfinance banks could benefit from such a charismatic leader.
  2. The strength of commercial capital: as was expected in the early 2000s, as soon as commercial investors realized that microfinance was a new asset class they could benefit from, with potentially good profitability, commercial capital started to flow significantly into the sector. And commercial capital was invested primarily into commercial microfinance rather than cooperatives, not only because of the reason above but also because of legal & regulatory limitations (much easier to invest in a private company than in a cooperative company). As a reminder, in 2020 more than 150 million people have access to microfinance with a total loan portfolio above 140 billion USD, while in the early 2000s, microfinance was reaching fewer than 20 million people for a portfolio below 20 billion USD. Commercial capital is largely responsible for this huge growth in the last 20 years.

I think this story around Efficiency, commercial and cooperative decision making can be applied beyond the cooperative sector (for instance the public sector or government-owned businesses, etc.). I would argue that the key to efficiency is alignment. An organization is efficient if the key stakeholders are fully aligned so that decisions can be made quickly and implemented efficiently. There are many ways to reach alignment in an organisation but the most efficient ways are probably those highlighted above:  

  1. One, or a limited number, of charismatic leaders followed by their teams, 
  2. A simple governance with very few owners aligned on the same goals.

As many microfinance banks are now facing serious challenges to face digital disruption and to meet clients’ expectations, quick decision making and alignment are going to be key success factors in upcoming digital transformation, so it is time for every organisation to learn from history and improve their governance & organisation to become more efficient in decision making.


Arnaud Ventura is a Managing Partner of Gojo & Company. As Managing Partner, Arnaud oversees strategy, business performance & development. He also leads the development of Gojo & Company in Africa.

Prior to joining Gojo, Arnaud founded and led two of the leading financial inclusion group worldwide. From 1998 to 2008 Arnaud cofounded and led with Mr Attali & Mr Yunus PlaNet Finance, one of the global and most successful European Financial Inclusion Group. From 2008 to 2019, Arnaud founded & led Baobab (formerly MicroCred), the leading Micro&SME digital bank in Africa & China.Additionally, Arnaud has been appointed Young Global Leader of the World Economic Forum in 2013 and he cofounded the French China Foundation the leading network of Young Leaders between French and China and Share Africa, a platform to support African youth.

October 4, 2021

A Little Theorem About Credit Scoring

In order to speed up loan approval processes, many banks and microfinance institutions use computer algorithms to calculate credit scores. I'm sure many of you are familiar with seeing a numerical credit score like '700'.

Credit scoring collects various pieces of information about a loan applicant and maps them to a single number. Based on the applicant’s loan repayment history, their use of other financial services, and other factors, the algorithm calculates a score such as '670 for this applicant', '740 for that applicant', and so on. And if the score is lower than the predefined threshold, the loan will not be approved.

Here, I would like to introduce a little theorem that makes up a part of Gojo's credit scoring approach.

Whether or not you can repay a loan without issues depends to a large extent on the size of the loan. For example, if I take a loan of $1 million, and spend it all at once without thinking, I will probably have a problem repaying it later. However, if I take a loan of $1, and use it to pay for some expenses, I will probably not have a problem repaying it later. In other words, credit scoring, which measures my ability to repay the loan, should be a function of the loan size.

Now, let's extend this view just a little bit more. The larger the loan size, the higher the credit score that should be required for the borrower, and therefore the higher the hurdle. The smaller the loan size, the lower the credit score that should be required for the borrower, and the lower the hurdle.

If that is the case, then for any given borrower, there should be a loan size that represents a manageable hurdle. For any kind of borrower, if we keep reducing the loan size, we will eventually find an amount that matches the maximum credit score they can achieve.

Maxima’s MBela team with an MBela agent at her house after a community gathering. / Koh Terai

The above paragraphs outline a little theorem about credit scoring, which is my favorite. Of course, we can take a further step to consider how we might apply it in practice.

Why don't we just look for the (maximum) loan size we believe a borrower can handle, and use that as their credit score? Rather than producing a score like '670' or '740', it would be easier for everyone to understand that $500 is the maximum possible amount they would be allowed to borrow. If the amount is clear, borrowers can plan their investment.

 We are actually applying this approach in a loan product currently being offered by Maxima, our partner in Cambodia. Their small digital loans project (also known as MBela) uses an automated assessment process to provide a credit score in the form of the maximum amount each person can borrow. The resulting credit score is easy for both the agent and borrower to understand.

Gojo wants to provide services that are innovative in their simplicity.


Yoshinari Noguchi is a researcher at Gojo and Company. He works in Gojo’s R&D team, and is currently looking into new ways to understand and support money management for low-income people, as well as analysis of data from the Hrishipara diaries and Gojo’s own financial diary projects.

September 3, 2021

Introducing the Fit Factor: A new impact measure

In this blog post we introduce The Fit Factor: Matching Loans and Savings to Cash Flows, a new paper from Gojo’s R&D team.

Typically, when we set out to measure the impact of a loan on someone’s life, we tend to look at what happens after they take the loan— for instance, whether their income increases, whether they are able to spend more on education, or whether they acquire more assets. However, there are a couple of limitations to this approach:

  • Outcomes data taken following a loan tends to be a snapshot of a certain point in time, and is usually collected at a time pre-determined by the service provider, rather than at a time that makes sense for the borrower in terms of when they expect to see results from the loan
  • Changes in income and increased spending on education can be influenced by many different factors in a person’s life, not just their access to finance. For instance, we see in financial diary research that unexpected events happen more often than we might think, such as accidents, sudden medical needs, new opportunities, and other events which may disrupt the original plans a borrower had for their loan

While outcomes data is useful, it cannot give us the full picture of the utility provided by a loan or other financial service. What if, in addition to outcomes data, we considered the impact of a financial service from a cash flow perspective? In other words, what if we could see how loans or savings fit with clients’ real cash flows and affect their day-to-day money management?

Using data from Stuart Rutherford’s Hrishipara Daily Diaries project, we would like to introduce a new impact measure which looks at how financial services either reduce or add to the volatility of a person’s cash flows. Our working assumption is that services which increase cash flow volatility generally make money harder to manage, and vice versa. We call this measure of impact on volatility the Fit Factor.

Read our paper setting out the concept, its applications as an impact measure, and its limitations here.


Yoshinari Noguchi is a researcher at Gojo and Company. He works in Gojo’s R&D team, and is currently looking into new ways to understand and support money management for low-income people, as well as analysis of data from the Hrishipara diaries and Gojo’s own financial diary projects.

Cheriel Neo leads impact measurement at Gojo and is also a member of Gojo’s R&D team. She is setting up and running Gojo’s financial diary projects in Cambodia and Sri Lanka, and is interested in using data to better understand Gojo’s current and target clients.

August 27, 2021

Designing technologies for financial inclusion

In today's digital world, physical cash is rapidly becoming a relic of traditional financial systems that have disadvantaged the unbanked. By combining mobile digital financial tools (such as mobile remittances and loan disbursal) with other money management tools (such as financial education), we believe unbanked people can access financial services and break out of the poverty cycle. At Gojo, we wish to include financially excluded people and enable them to achieve financial goals and self-sufficiency.

I joined Gojo as a Software Engineer in August 2020 to enable this mission and solve our mobile engineering challenges, of which there are many. I’m going to talk about two of these today.

Challenge #1:

How do you create a Digital Field Application system that works even if the cell tower is down?

Most of the time, we take internet access for granted. That’s not the case for our customers in many countries, where the internet can be patchy and a precious resource. In order to ensure that our DFA didn’t stop working when the internet did, we had to architect our technology to be offline-first.

First, we loaded our app onto an Android tablet with 32GB of storage. We were able to store all the relevant data like names, photos, and loans locally on each device. The user, typically someone like a loan agent, doesn’t even need to know whether the tablet is online or offline, because the app behaves the same either way.

In the event of the internet dropping off, as soon as the tablet is reconnected to the internet, the data automatically syncs with our servers. That enables us to maintain data quality despite patchy internet.

Field officer taking photos of new M-Lady client using Gojo's DFA / Koh Terai

Challenge #2:

How do you enable field agents to update their Customer Forms on the fly to capture desired and customisable client data?

A critical piece of our Digital Field Application is to collect client information on tablets. This information is then used to make a decision on whether a client is eligible for a loan or not. These forms can vary widely depending on the data capture requirements of the partner. Keeping the fact in mind that the KYC forms could change on a regular basis, it did not make sense for us to go for a conventional route, i.e., to hardcode forms on the tablet itself.

We solved this problem by implementing the SDUI (Server Driven User Interface) architecture for our form screens. It works in conjunction with the offline architecture I mentioned above to render the latest version of the form to the client when the internet connectivity is present, or the latest cached version in the offline scenario. 

It provided us the following benefits: 

  1. Partners no longer need to depend on mobile developers to update the app to show specific changes in forms or to change the order of the UI. An agent can now use a web portal to make any changes he/she wants in the forms and it would be reflected in the app instantly.
  2. It’s easier for loan agents to introduce new form fields, like images and map views from their office computers and have it reflect on the mobile app.
  3. It enables the engineering team to create more reusable form components and scale across partners, because we do not have to hardcode the forms for each of our partners.

As we continue to scale our Digital Field Application across Gojo partner companies, these solutions will evolve, but we're confident that our approach of immersive design and innovative development is the best way to yield technology that is as resilient and adaptive as the people in the places where it is meant to be used.


Jeet Dholakia works as part of Gojo's technology team as a software engineer, focusing particularly on mobile engineering. He is passionate about solving complex engineering problems and good mobile design, and is currently working on Gojo's Digital Field Application and Customer Mobile Application.

July 6, 2021

RESET podcast: Taejun on founding Gojo

Our CEO Taejun was recently interviewed by Dr Vic Woo of Stanford University on the new sustainability-focused RESET podcast. In this episode, he shares the story of how he founded Gojo and the thinking behind our investment strategy.

July 2, 2021

3 key factors in financial modeling for microfinance

Group loan clients in Cambodia being served by a Maxima loan officer / Taejun Shin

I recently completed the financial modelling process for Gojo, and thought that the process might be of interest to other investors in financial inclusion, or anyone interested in the economics of microfinance.

The financial modelling of MFIs is not complicated. Financial Revenue is the key item amongst the other P&L items to understand the structure and assess the scalability of microfinance businesses. It is calculated as interest rate multiplied by Loan Portfolio. In this blog, I would like to focus on the Loan Portfolio because the other factor, the interest rate, is capped by regulators in some countries, and is not always a parameter which MFIs can freely change.

The loan portfolio can be broken down as follows. The 3 items colored in red are the key indicators on which I would like to elaborate further.

  1. Productivity (# of disbursed loans / LO): One of the most important factors is Productivity, which here means the number of loans disbursed per loan officer. This indicator shows how many loans a loan officer can handle at a time, or how many new loans a loan officer can disburse in a certain period.

    This indicator can be further broken down by branch or product. The productivity is highly correlated with branch vintage, i.e. the productivity tends to be lower at a newly opened branch but it improves as time goes by as officers get trained and become more experienced. Also, this indicator can be further improved through streamlining operations / processes through technology, such as the use of a Digital Field Application, automated underwriting, cashless payments etc. 

    One example of this at Gojo is a Digital Field Application called Bridge, developed by our tech team, whose MVP succeeded in significantly reducing the registration and loan approval time from 3 days to just 40 minutes! With the device, the loan officers are able to spend more time on client sourcing instead of becoming engaged in unproductive paperwork.
  1. Loan size: MFIs are willing to offer larger loans to customers who have repaid previous loans, as they can see more of the customer’s credit history than before. But for the MFI to be selected as the customer’s lender of choice, they need to keep a good relationship with customers through close and constant communication, otherwise the customers would end up changing their lenders. The MFI offers larger loans when the MFI is confident enough that the customers will repay the loans.

    Therefore, to offer larger loans, it is critical for the MFI to have a deep and up-to-date understanding of customers, including but not limited to, their business, financial situation and personal events. Considering this, although I mentioned the role of technology above, the microfinance industry will not immediately transition to fully tech-equipped services, unlike many other industries, but "tech & touch" will be the key concept for MFIs at least for several years going forward. Given that many MFI customers still do not own smartphones/smart wallets, data about their business situation, financial needs and other life events cannot be collected through these kinds of devices but needs to continue being collected through human touch to some extent. Modelling loan size therefore means we have to take into account the MFI's current and future capacity to collect data on customers and assess their creditworthiness.
  1. Branch expansion (# of branches): Room for branch expansion largely varies by country. For instance, in some countries such as Bangladesh, financial services have already spread widely to the bottom of the pyramid, but other countries still contain large numbers of underbanked or unbanked people. In more competitive markets, the MFI needs to have some unique selling point or advantages compared to existing players, whereas in less competitive markets they would be able to enter more easily.

    The decision on whether to open a branch depends on potential demand for credit, risks, economics, the competitive environment, and many other factors. An additional factor to take into account is the strategy of a MFI, as some MFIs focus more on urban areas while others target rural areas. There are financial institutions which do not have physical branches, rather operating through agent networks. For such institutions, we would possibly use the number of agents instead of the number of branches.

Although obviously there are many more factors to be considered when developing a financial model, such as operating expenses, fundraising and so on, I believe these three items above are the most critical and impactful items to microfinance businesses. At Gojo, we have seven partners as of now and while each partner has a different business model, the key financial success factors for most of them are the three I have outlined above.


Ryo Satake is an accountant and works in Gojo's finance and strategy and analytics teams. He recently led the process of financial modelling for Gojo's overall business and has helped to formalise the budgeting and financial reporting processes for Gojo's partner companies.

June 4, 2021

Data as (s)oil in microfinance

Farmer in the field in Anad, India. Photo by Nandhu Kumar on Unsplash

Data is the new oil?

In the past decade, the phrase “data is the new oil” has become hugely popular, with hundreds of articles and talks using this metaphor. And there is good reason for this: many see data as the “fuel” which is giving energy to the 21st century economy. 

Data on its own has no, or little value - similar to crude oil, it needs refining to become a useful and valuable resource. Only after we process our data, put it into the right context, and use it for decision making, do we get the real benefits (in the same way that oil is much more useful when turned into petrol, asphalt or plastic). To do so, we need infrastructure for collecting, storing and processing the data - which is another similarity with the oil industry.

But is this metaphor really fitting?

First, oil is a finite resource, consumed over time, and rarely reusable. This is very different from the nature of data- data  is (almost) unlimited, reusable and multiplies whenever we cross it with other data (we create information, rather than using up data). This gives us unlimited opportunities without having to worry about running out of “fuel”. 

Second, with oil you need to start big - the infrastructure is very complex and it requires a huge investment. Again, data is very different - you can start from simple data analytic functions, gradually developing your capabilities and outreach. It is also possible to test solutions and pivot if the chosen path does not fit your business. 

Third, you can store crude oil and it will still keep its value, whereas data very often loses its value over time. For example, records of some events age very quickly, and can only bring benefits if used immediately.

Finally, in case of leaks, oil can be cleaned up (although the damage to the environment is done and not always fully reversible), while in case of data it is impossible - leaked/stolen data can damage businesses and people’s lives for many, many years.

(S)oil

While listening to The Data Strategy Show1 podcast, I encountered for the first time the idea of “data as a new soil”. In the episode they mention the soil metaphor in passing, in contrast to oil. I found the soil metaphor to be much more accurate and decided to extend this thinking further.

First of all - you need to work patiently with data/soil to bring value. To grow crops, you need to know the quality of your soil well (explore your data), understand what crops you can expect to grow on this type of land (understand the business context), prepare the soil for agriculture (prepare data), sow seeds (run analytics), water crops and look after them (enrich your data, observe the results, improve analytics), protect from pests (ensure data security), harvest crops (make use of ready information), and… iterate or improve on the process.2

Moreover, the soil metaphor is useful to show that without previous experience it might be better to turn your enterprise into a data-driven one gradually. As with soil or land - if you are new to agriculture, you can start with a small plot, learn, experiment, pivot, and progress with time. Unlike with oil, you don’t need to build the whole operation from day one, but can start small and keep gradually improving.

You also need to be patient - careful preparation, good understanding of data and business context are key to obtaining the best outcome and should not be hurried. Data projects you start now might bring value after a few years - crops you planted today will not grow in a few days.

Of course, the examples above do not exhaust the similarities between data and soil, but they demonstrate the usefulness of the soil metaphor.

Woman working on a rice field in Chiang Mai, Thailand. Photo by Eduardo Prim on Unsplash

In the context of microfinance

In the microfinance context this metaphor is even more appropriate- and it is not only because the low income households we serve very often make a living from agriculture or animal husbandry. 

The microfinance sector has not usually been associated with being “data-driven”. Access to data has historically been limited, the need for data analysis has not been recognised, and the lack of proper infrastructure for data was very common. With growing usage of smartphones and tablets, however, the situation has slowly started to change, this change has rapidly accelerated under COVID-19 - more and more microfinance institutions are starting to implement better data collection methods, build (or outsource) data analytics, and use data more often in decision making or product development. But (almost) everyone proceeds in the same way as a farmer starting to cultivate a plot of land - start with a small project, learn, experiment, and then pivot or scale. And just as with growing crops: for some outcomes we will need to wait a little while.

Finally, one important point: data belongs to the people, to our clients. They give us access to their personal information and in exchange we improve our operation, pricing, and product fit. Together, we are cultivating the soil and sharing the fruits of our labor. Sometimes literally.3


Tomasz Ociepka works on data analytics at Gojo. He is currently working on setting up Gojo's data lake for the secure storage and easy analysis of data from Gojo's partner companies.

March 30, 2021

Familiar Objects Used in Unfamiliar Ways – Smartphones in Rural Cambodia

Last March, I conducted two weeks of ethnographic field research in rural Cambodia with the local staff at our partner company Maxima.

Aside from learning about the villagers and their behaviours around money, I also tried to understand their relationship with technology.

During my research, I observed one phenomenon that surprised me.

Many of the homes I visited had mysterious numbers written on their ceilings. They were written with permanent marker, or etched into the wood. I was baffled by what they were.

Mysterious numbers written and scratched into the ceiling of a home in Banteay Meas, Cambodia / Koh Terai

Can you guess what they are?

It turns out that they are phone numbers of contacts that are important to them — doctors, police, their family members, and relatives.

The baffling part is that these people all owned feature phones, and some of them even owned smartphones.

So naturally I asked them, “why don’t you put these numbers into your phone?

Their responses made me smile.

I don’t know how to register numbers into my phone, I only know how to receive calls”.

My phone is in English and besides, I can’t read

If I lose my phone, I would lose my data.”

“If the numbers stay in the phone, they sometimes get deleted. They never move if they are on the ceiling.

My phone is in English and besides, I can’t read

I felt enlightened after hearing their responses. It became clear to me how their relationships to their mobile devices are quite different from the relationship I have with my smartphone.

For me, this leads to other interesting questions we could ask like…
- What are their relationships with their mobile devices like?
- How would that influence their relationship to mobile apps?
- Does this behaviour tell us anything about the strengths of social ties in these communities?
- Are there clues we can derive from the way people use spatial memory to organize information?

“I got this phone 2 years ago. I don’t know how to use the phone. I only receive calls. I only remember if the last two numbers are 27 it’s my first daughter, if its 20, it’s my second daughter.”

How many people do you know that store phone numbers on their ceilings at home?


Koh designs products and services for Gojo. He spends time listening to clients and potential customers to deliver well-intentioned financial and digital products for low-income households.

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