How to Startup?
Phase 2 - Non-Profits
The step involves building an MVP and a product roadmap which will ultimately lead you to a good product.
Now that you have identified your EPIC idea, you are ready to develop it. But it's important to take an iterative approach to building your idea so that you can incorporate what you learn from users, the system, and the market.
Typically startup founders start with a minimum viable product (MVP) - a lightweight version of a product that delivers core value to users. This MVP can then be used to get feedback from the users & assess their willingness to pay for it.
But for non-profit founders especially where the user does not pay for the intended product/service, the feedback signal on whether any impact/value was delivered is virtually non-existent. This makes building an MVP a lot more challenging for non-profits. Also, in those cases where the government or donors will pay for the service, it becomes very important for the non-profit to build salience around the problem.
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Product development process:
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Start building evidence based narrative around the problem
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Build an MVP / launch a pilot to test the most crucial assumptions in your impact model
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Test your product with first set of potential customers
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Goal is to learn from users and take feedback to improve the product
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Measure progress on your leading indicators
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Make a week-on-week plan (sprints) to improve your product
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Make iterations to the product based on user feedback.
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Evidence based narrative building :
Founders should begin building evidence-based salience around their problem area early in their journey. The scientifically collected data builds credibility amongst different stakeholders and makes it easier for founders to enlist supporters, funders and partners.
. Here are ways you can go about it:
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Is there unique data that you can use to quantify the problem? Do you have easy access to this primary data or can you collect it quickly? If not, can you look at the secondary data and derive insights from it?
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Write an evidence based report on it & make it available on your website.
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Distribute the report through media by either directly reaching out to journalists or engaging a cost effective PR agency.
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If you don’t want to invest in report, publish bite sized chunks on social media.
At Change Engine, we work with our founders to understand what kind of data they can collect or collate to highlight the issue they are working on. For instance, Ritwick of Prajatantra foundation wants to democratise political entry in India. He has started with collecting data around the role of privilege in elections and quantifying the extent of gatekeeping currently present in the process of candidate selection by political parties. Recently Prajatantra published a report on method of political entry . The report got covered in print as well as digital media such as Times of India, Indian Express & more This has helped build a narrative around the problem & get people interested in helping them solve the problem.
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Building the MVP for your high impact idea
For non-profit founders, it may take months or even years for the impact of your work to show up. Because of the longer term horizons, it is important to think through risks in getting to impact and identify leading indicators of success that can be tracked during implementation.
Impact model: An impact model outlines the series of activities that you will do to deliver the core value or impact to the user, which can be replicated consistently. One way to get to your impact model, is to list down all that must happen for the intended impact to happen. Make sure you write down who needs to do what in your value chain. And then list down all the activities you will have to do to drive the intended behavior.
Intended Behaviour | Activities |
|---|---|
NGOs agree that outcome based funding can increase their funding pool | Build narrative around outcome based funding |
NGOs agree to open up & integrate their data system | Build open APIs, integrations & visualisation engine |
Donor pays for outcome based funding | Publish case studies for outcome based funding |
Donors ask their grantees to share their impact data for funding | Support donors in educating their grantees & assist with integrations |
But as is often the case, usually your impact metric will take months if not years to show up. How can you then make sure that your intervention has a high chance of success?
This is where minimum viable testing comes into the picture. Each activity listed in your impact model, will have certain underlying assumptions about the market, about behaviour of users or other actors. Once you have identified them, you can build a minimum viable product to test the most important assumptions for your idea to have an impact and iteratively test out your full model.
Intended Behaviour | Activities | Assumptions |
|---|---|---|
NGOs agree that outcome based funding can increase their funding pool | Build narrative around outcome based
| - Are there enough non-profts which want to outcome based funding?
- Are there any tailwinds?
- What stage of non-profits benefit from outcome based
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NGOs agree to open up & integrate their data system | Build open APIs, integrations & visualisation engine | - What kind of data systems are non-profits currently using? Do they have APIs?
-Are non-profits willing to open their data and what granularity?
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Donor pays for outcome based funding | Publish case studies for outcome based funding | - What is the cost of implementing our system as a % of grant? Is it affordable?
- Would donors be willing to pay for more transparency?
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Donors ask their grantees to share their impact data for funding | Support donors in educating their grantees & assist with integrations | - How much customisation would be needed for each ngo?
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Leading indicators:
You will also need to identify clear leading indicators to measure your progress as your iterate on the product. For instance, for the above startup, some of the leading indicators could be:
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How many NGOs has signed up to integrate with the platform?
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How much time donors are spending on the platform?
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How much are donors/ngos willing to pay for the solution?
Relevant Readings :
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Minimum Viable Product (MVP)
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User Interviews
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Non-profit models:
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Other miscellaneous notes:
As a founder, you need to have a working hypothesis of how you would be best positioned to deliver your impact. We have seen two major methods;
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Tech as a core component of the solution:
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Personalisation at scale
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GTM / Distribution
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Digital public good
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Tech-as-an-enabler / Non-tech
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Owning & defining the problem / bringing it to salience - evidence based research
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Sandbox
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Building institutional capacity (government, markets, policy reform)
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Build feedback loops for the system
At a high level, a pathway to systemic impact involves:
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Discovering, defining & highlighting the problem and bringing it to salience
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Figuring out an idea that can make a significant impact and is cheap and simple enough to be delivered at scale
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Delivering the solution at scale through self scaling or by building institutional capacity (working with the government, policy reform) or helping crowd in markets
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Building feedback loops for the system. (Quite often this is the problem you want to highlight)
For a non-profit, typical risks would be:
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Impact risk: Does the intervention actually lead to the intended impact?
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Execution risk: Are we able to identify a doer-at-scale who can deliver the program at scale without compromising the quality.
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Funding risk: Have we identified who will pay for this at scale?
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Execution risk: These are the few questions you should ask yourself to help assess them:
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Execution risk:
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Is the solution simple enough that it can be implemented by you or other people without compromising the quality?
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Does the solution have a lot of moving parts and processes?
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Can tech help standardise the service at scale?
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Funding risk:
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What is the per unit cost of delivering the solution to the end user?
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How much do people/government currently pay for a similar service?
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Would anyone of these have enough budgets to pay for the service -user or government ?
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Are there enough incentives so that markets can ultimately crowd in?
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Can tech help bring down the costs through reducing user acquisition cost / ops efficiency / program delivery?​​
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