How can I assess the value of my data assets?

Hello! I am a former automobile dealer, and I had an auto repair shop, body shop, and licensed vehicle inspection station in central Missouri. I am very familiar with this industry. I entered this market at the wrong time, grew quickly, and hit the Great Recession at the wrong time. My goal was similar to yours, to wholesale vehicles, but also to export classic cars to the middle East. Canada is a great source for people here, because the prices are in fact lower for US buyers. I am still somewhat involved in the automotive niche, and I even recently purchased a replacement engine on a Scion from Canada because it was about one third of the price that I would have paid anywhere close. One thing you mentioned that stuck out in my mind is focusing on SUVs and trucks. When you specialize, you create your biggest potential. If you can create a name for yourself for supplying a particular size of truck, say a 1/4 ton pickup with an extended cab, you might be able to connect with volume buyers who are looking for low cost alternatives to buying new. This could be municipalities with tight budgets, small transport companies, service industry companies, etc. Once you find a hot niche, word could spread fast, and if you've mastered the supply side, you will be able to move vehicles super fast. And if you have the capability of doing some mechanical upgrades on the vehicles before you sell them, you'll make a greater return on your investment. One example of a hot niche is Jeep Cherokees in Colorado. Cherokees sell for 20% to 30% higher in Colorado than what they go for in the Midwest. I know of a person who did nothing but purchase Cherokees and fix them up for selling in Colorado. He had a very solid business. The advantage to focusing down on a very tight selection of vehicle models is knowing what to expect. You'll know what parts are likely to be worn out at a particular mileage, where these vehicles tend to rust first, what mechanical issues are common, or electrical problems that you can run into. When you are wholesaling and buying anything and everything, you'll heighten your chances of getting burned. I've been there myself, and learned some hard lessons. At the end of my run in the business, I wish I could have hit the rewind button and only scoped out a narrow variety of vehicles that I had the most knowledge on. I plan on re-entering the business soon. I've got a particular car in mind, the 1995 Ford Mustang. I rebuilt one of these, and I know all of the gory details for this car. Right now, they are a dime a dozen, and you can find them everywhere. My plan is to restore them and sell them, because this body style and the Fox body are the next ones which will become "nostalgic". Drill down and find out which pickup truck is your best prospect. Factor in common problems, cost of repair, and demand out on the market. Then stick with that model within a certain range of years, and make a name for yourself in that niche. You are guaranteed to have better success if you take that approach!

Qualifications on the answer: Created the first website to be ever commercially licensed by a ministry of education for in-school use (Brainium 1996). Was a VC associate at a 500,000,000 firm called Knowledge Universe focused on all things education-related that intersected with technology. Short Answer: Yes and no. Longer Answer: Learning analytics is one of those "lightening in a bottle" kind of industries. Everyone knows it's going to happen, whomever makes it happen at scale first, will have a huge advantage, and even more niche plays in this space will still create massive value for shareholders and significant transformation of education as we know it. That's the good news. The problem is that funding startups in the education space that are dependent on "permission" being granted by existing institutions and their employees is very much hit or miss. It's getting easier to raise a $500-800k seed round for a good idea with a good team, but the problem is that getting the next bigger round is very challenging in that the models of most of these seed-funded companies are not growing fast enough to prove to institutional investors that a growth model of the idea being very big in a relatively short time-period is credible. So if you're intent on pursuing this, I'd be sure to focus entirely on how you can get growth and adoption with requiring little to no institutional buy-in which sounds almost impossible on the surface of the area you're exploring but I believe isn't actually impossible. I'm very passionate about this space and want something like what you're describing to succeed so would be happy to do a quick call to hear where you're at and see if I can provide you some actionable ideas on how to reduce the friction / improve adoption of your analytics product.

Ian's answer is great. He outlines how you can begin determining the potential customer interest in this which is very helpful. But even if customers respond favourably to this idea, I think you have to be really confident in the economics of the business which, just thinking quickly, I'm not. The measure of a healthy business like this this is a much higher LTV (life time value of the customer) then your CAC (customer acquisition cost). Uber has the advantage of knowing that once they acquire a customer, that person is likely to use their service many many times over the course of years. By contrast, how many people will need your service more than a handful of times over the course of 3 years? There are other even more practical concerns around the marketplace economics and behaviours that I'd be happy to address in a call. I think that social roadside assistance is likely a feature of a bigger opportunity.

In my experience coaching hundreds of people, anytime you go against your gut (aka intuition) you will lose. Data is important to consider, but your gut often knows the path.

Hmm .. Interesting that you say your sector isn't being addressed. Wonder why ... But if so, then that's an opportunity. I've spent the past 4 years specializing in probably THE hardest market for making accurate appraisals: the domain name industry. For me as an engineer, that has meant crunching numbers. So I'm intimately familiar with the issues involved in making inferences about value from partial list-price and sale-price data. In fact, I spend much of each day compiling raw data and building database-driven tools to organize and analyze it. So I don't know the auto industry at all, but I know a thing or 2 about figuring out the value of assets in obscure areas. Certainly a model can be constructed for extrapolating value from list prices. It only remains to be determined how wide the margin of error would be and what kind of latent bias might exist. If you'd like my help, just ask.