University of Illinois students take a Lean Start approach

Datify lets you “Take control of your data”

What do we do?

We hypothesize that a problem exists in that small businesses are losing substantial sums of money to unproductive employee behavior. After speaking with several small business owners, we realized that experience and intuition are often the only tools used by small businesses to assess employee productivity.

There is no such thing as “too much information” in today’s day and age. We complement experience and intuition with data-driven validation for methods to increase employee productivity. Showing small businesses a direct relationship with their current level of productivity in terms of the money they lose every month will aid their decision-making process.

We are testing this assumption with a novel device that collects network data to understand the relationship between businesses and their employees. Based on our research, combining the data from this device with statistical studies on productivity will allow us to determine a solid figure as to the money the employer is losing to unproductive behavior. Through analyzing changes in network usage over time, we will determine whether this assumption stands true.

For example, we see that the average employee is visiting Facebook for 5 minutes after every 30 minutes. We know that this is unproductive, not because the employee is using Facebook, but because she/he visited every 30 minutes. If the employee did so for 10–20 minutes after every 90 minutes instead, research studies show that this would boost productivity.

So say Jim is the employee in the above-mentioned case, we can estimate fairly accurately that the company loses $60–80 every day because of Jim’s unproductive behavior. The business would save significant money if the employer asked employees to take 10–20 minutes break after every 90 minutes rather than take 5–10 minute breaks after every 30 minutes. This will increase productivity as well as employee satisfaction because they get to take longer breaks without breaking their train of thought as often and without guilt.

What does the employer have to do to get access to data? He sure must have to be super-tech savvy!?

This is where we come in. The employer needs to have absolutely no technical experience. All she/he has to do is connect our device (which is as big as a ring box) to his WiFi router, and check our website once every week/month. This tells her/him a solid figure on the amount of money the company is losing to unproductive behaviors and the steps to be taken to reduce this. We also map the progress of the company in saving money over the months using a graph. Just plug the device, and check our website, that’s literally all you have to do!

Why do we do, what we do?

Since 1995, over 65% of the American population work in small businesses. There are over 27 million small businesses in America. Small business is the life of this country and economy. Making them efficient will boost the economy by a significant amount. A better economy means better social services and a better standard of living for the American people.

How did we get here? Our process and how we found our niche in the existing value chain?

We first started as a group of highly ambitious engineers from UIUC with a mission to understand the world of the Internet and opportunities to provide better Internet connection to third world countries. However, our research got us deep into the nitty-grittys of networking and then we hit on the Internet of Things! We watched a TED Talk, according to which an average nurse in the US takes 21 minutes a day to finder her/his equipment every day. If this number was reduced from 21 minutes to 20 minutes, merely by 1 minute, the healthcare industry would save around $60 billion every year!

With this in mind, we realized that the market for Data collection and analysis was virtually unlimited!

While many other student-based startups were focused on re-inventing the next Tinder or Facebook, we had a grander vision! To make every consumer efficient and have them more control over their data through personal data licensing. This caught the attention of two remarkable professors Dr. Scott Carney (from the Electrical and Computer Engineering department) and Professor Brian Lilly (from the Technology Entrepreneurship Center).

Realizing that the idea was a novel one, but too ahead of its time, as people are not yet comfortable with the idea of data licensing, and after talking to some remarkable people at 1871 like Mitch Posada, we realized that our niche in the existing value chain lay in the B2B market as of now.

Testing our hypothesis

To test the viability of the DataBox, Ashu tested the device at his house for his roommate. She works at a pawn shop, cleans a bank and sells products online. The DataBox showed her web usage while selling products online and we determined that she would make more money from selling products online than working in the bank (and she loves selling online much more than the bank too!).

We spoke to 31 companies to find our niche. There are many companies starting to realize the potential of IoT, and in order to build beautiful and creative products we need some people talking about us, so we can start testing our device fast. We also gained interest from Harbor Street Ventures, iVenture Accelerator, and TechDay New York.

Here is a link to our F6S to see more about our progress.

Written by Asutosh (Ashu) and Eric

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