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  • Writer's pictureNathan Temeyer

Measuring Impact Through Innovation

Interested in how AI is revolutionizing small business support? Keen on diving deeper into AI’s role in global development? Check out our Bizzy online journey. Our series of webinars and articles will delve deeper into how AI is becoming a strong ally in combating poverty.

 

ONOW recently joined YBI's High-Flyer program that aims to support high-growth potential entrepreneurs throughout their journey - from connecting them to the right resources, to building useful skills, gaining access to capital, or simply improving our tracking on whether our interventions are actually useful. IPA also released their Best Bets for Emerging Opportunities for Impact at Scale, and ONOW is actively working to find ways to deliver and scale number 8: consulting services to support SMEs. We believe that recent innovations in AI and LLMs have opened a window of opportunity to deliver upon this objective in a personalized and impactful ways. Over the coming months, stay tuned as we share our approach and learnings in these important areas for high-flying MSMEs in SE Asia!


The Problem of Traditional Methods

Enterprise Support Organizations (ESOs) face a big challenge: tracking their impact is tough. They often rely on basic metrics like participant completion rates or positive feedback percentages. These measures might suggest progress, but they don’t guarantee lasting improvements, and no one checks up on them over time. They're indirect and short-term. Statisticians suggest Randomized Control Trials (RCTs), but these are often impractical in this context.


What's the solution? At ONOW, our mission is to enhance business profitability through a direct, ongoing, user-friendly tracking system. We aim to collect data that’s not only reliable but within a process that's valued enough by business owners that they willingly share it without coercion. As YBI research indicates, financial data predicts future success but is hard to get. It’s sensitive, and using traditional accounting tools and processes can be tedious. So, many MSMEs opt not to bother with financial tracking at all. They are indirectly performing a cost-benefit analysis and deciding to spend their limited time elsewhere.


Our new platform changes this. By using AI, data automation, and visualization, we make tracking finances less daunting and more beneficial for business owners, encouraging continuous data entry and engagement.


Reducing Cost: Chatting Your Finances

Current financial tracking systems are detailed, starting with an income statement and requiring precise inputs. This is overwhelming for many MSMEs.


ONOW is taking a different route. We start with the balance sheet, a more familiar point for business owners. By knowing their cash balance, we can use AI and LLMs to back into the financial activity that led to the cash we see. Our aim isn't to capture every transaction but to follow the 80/20 rule, getting the majority of the information with minimal effort.


This method, demonstrated through a simplified ChatGPT example, shows the ease and user-friendliness of our data collection process. However, it should be noted that this is overly simplistic, and we're making substantial background improvements to optimize UX and localize the service beyond GPT itself.


With tools like GPT, data collection becomes scalable, unstructured, and conversational, ideal for our target audience who may be unfamiliar with traditional spreadsheets. This approach allows us to cover a wide variety of business types without predefined surveys, using the flexibility of LLMs.


Our system is also designed to handle financial gray areas, prompting for details until 80% of cash changes are allocated. The rest goes into an "other" category for future refinement.

To see the whole conversation and sample prompts for GPT, visit the link here. Remember, this is a prototype, meant for demonstration and educational purposes.


Increasing Benefit: Immediate Value Gained

And this process isn't just simpler; it's designed to be immediately valuable. Our goal is to balance the cost-benefit equation for MSMEs so that it becomes worthwhile to track finances. The above section focused on reducing the intangible cost, but we're also seeking to improve the benefit side. One challenge with financial tracking is the delay between inputting data and seeing benefits. Our platform is being built to add immediate value, making the process more appealing.


With LLM advancements, we can extract, categorize, and automate a process of unstructured conversational data into structured, valuable business intelligence right away. The example below shows the output from the previous conversation:



These reports include pieces like spotting anomalies, generating insights of revenue and expense trends, cash flow patterns, and dynamic forecasts. As the user engages over time, the value grows. This contributes to a personal investment that further cements the financial tracking habit.



What's Next?

As we progress along this journey, we're always searching for new sources of value to make this process more attractive to the MSMEs we serve. We believe that finding a way to capture this information directly, and avoiding the proxy measurements of user counts is vital to truly measuring our impact on business owners.


Without recurring, longitudinal financial information, we're left in the dark with only our opinions and guesses on how to proceed.

If we have data, let’s look at data. If all we have are opinions, let’s go with mine. - Jim Barksdale

To really measure impact effectively, we need to go beyond old methods and track it more directly. Relying on opinions, anecdotes, or flashy reports isn't enough – they don't hold up under close examination, and often overstate the impacts we have. The industry needs a direct, data-focused way to measure impact better. Just using reports won't cut it; without real data, we're stuck with the same old proxy metrics.


Our approach? Create a product that businesses are excited to use. We're working on enhancing our AI-driven data collection, making the user experience smoother, and adding more external data for deeper insights. We're also looking at incorporating gamified elements to make the product more engaging, tuning the UX, and more. We're committed to an experimental, step-by-step process. So, keep an eye out for more developments and updates from us!

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