Invention Evaluator

Invention Evaluator launched last year but is already finding success in the university sector – both here and overseas – in addition to servicing corporate clients and mum-and-dad inventors.

Invention Evaluator was founded by Michael Manion, Heather Kelley and Gerard Manion, with the aim of helping individuals and organisations analyse their inventions.

“We provide a 30-40 page analyst report, which looks at the technology, intellectual property and commercial potential of an idea or invention,” Michael Manion says.

“Our first year has been the typical thrilling ride of a start-up and we’re growing our bootstrapped company quite nicely.”

Manion talks to StartupSmart about forming an idea around the ideas of others.

What inspired the idea for Invention Evaluator? What gap did you see in the market?

The way industry is sourcing new technologies for products and services is increasingly coming from outside their own R&D – university research labs, innovative SMEs and start-ups, and independent inventors.

This megatrend of “open innovation” is still in its infancy, with much inefficiency in the process of transferring technology, leading to significant areas of opportunity.

Michael has been commercialising technologies for universities both here and in the US for many years, and saw that there was very inconsistent management of the early analysis of a new idea from researchers and inventors.

Inventors come up with ideas all the time, but to make a great commercial success, the technology has to ultimately be developed into a product or service, the IP has to be able to be protected, and there needs to be a compelling and accessible unmet market need that is addressed by the invention.

Of the many inventions people come up with, only a small percentage fit these criteria. Deciding which ones are worth investing resources into, to cultivate a commercial opportunity, relies on proper analysis.

Through observation and research, Michael saw that the handling of invention disclosures is often biased, ad hoc and quite often not done at all.

According to some university surveys, up to 10% of disclosures do not even get processed due to labour and time constraints. There had to be a better way.

Gerard had been developing online solutions for many years that enabled companies to do things more systematically and thus more efficiently and cost effectively.

The “light bulb moment” was to apply these principles to the open innovation landscape to provide systematic efficiencies to the analysis of inventions and their commercial potential.

Information could be disseminated much easier, and the tools could be used to engage and educate the inventors.

Heather had built and run several successful businesses both here and in the US, the latest being an online system to promote outdoor activities and social clubs.

Using a practical approach and bringing two worlds together, Heather devised a system which could provide an efficient way of managing analysts to complete a standard assessment of an invention disclosure through an online portal.

With these collective experiences, Invention Evaluator was created.

How long did you work on the business before you launched it?

We started building the business in October 2010 and launched the site in January 2011. We used known contacts to do a soft launch and test the product.

During this phase, we gathered lots of feedback and refined our reports accordingly.

Over the past year, we have also been building a knowledge base, custom report builder software, and an internal system to manage our analysts and their reporting capabilities more efficiently. 

How did you fund the business?

Once we understood the potential of the business and the start-up requirements, we channelled our own internal funds into it.

We consult to a number of companies on business growth and commercialisation and, as a business, use a development fund to commercialise our own IP.

The business is now completely bootstrapped. The initial costs have been over $200k as well as more than 4000 hours of founder time.

The funds have been directed to vendors and development contractors to build the systems.

How do you promote the business? 

Initially, Michael’s network in “tech transfer” was utilised to get us into some universities where we started to get many referrals.

Since then, many of the university tech transfer organisations across Australia and the US have been using us. We are doing our first trade show in the US in March.

We are also expanding our marketing from just university tech transfer to corporate R&D and investor groups who need to screen large numbers of new technologies to find the next “gems”.

We are also beginning to work with patent attorneys and IP law firms, and innovation houses for cross-referrals.

We do a lot of online marketing as well through Facebook, LinkedIn, Twitter, blogging and so forth.

How many staff do you have?

There are 11 of us working in the business now, and growing. Our analysts all work in-house and have expertise across life sciences, physical sciences and IT.

We have a pool of candidates wanting to join us, and we will bring them on as we scale the business.

What are your revenue projections for 2011/12?

We will make a little over $500k this year, which is about a 100% increase over our first year.

What are your points of difference?

It’s a big statement but we challenge ourselves daily on this: “We are the simplest way of getting the smartest, most cost-effective, quality invention analysis in the world.”

To get a good analysis done, there are several options. Consultants cost way too much to do this early stage analysis. We only charge $199 per report.

Patent attorneys are great, but they really only focus on one element – the intellectual property. Our reports provide a thorough analysis of the technology, intellectual property and the market potential of each invention.

In-house analysts may be good but for less than the price of one junior analyst, you can access our entire pool and have a broad capability across different technology landscapes.

Besides, one of the main benefits of what we provide is complete objectivity and an independent look at the invention. This is difficult to achieve in-house.

What has been your greatest challenge and how did you overcome it?

Our reports are thorough and come out at about 40-50 pages in length.  Producing quality reports in this way takes a lot of time, which is difficult to do profitably.

We are overcoming this using technology. We are developing systems to cultivate our knowledge base and build the reports in the most efficient way possible.

We have invested heavily in development of scrapers and bots, and some AI elements, to enable the analysts to produce a bespoke report in an efficient way.

We have become very efficient through the development phase so the time it takes to produce the reports is minimised without compromising the quality.

Even better, the analysts are now able to completely focus on the information they have to assess, instead of doing all the menial tasks of building the report.

The system is logical and follows a set sequence to enable consistent results and affords us great control of the quality.

What’s the biggest risk you face? 

The biggest risk is making sure we can scale effectively. Part of this was building the system to enable the analysts to complete the report as efficiently as possible.

With every report we do, this gets better as our knowledge base builds.

The other part is to make sure we can find, hire and train analysts as efficiently as possible. Again, we’re building online systems to do this that leverages the latest technology.

If we get a big client tomorrow, and they submit 1000 disclosures straight away, we need to be able to add additional staff and have them productive within 10 business days to meet the turnaround criteria for the reports.

Is there anything you would have done differently?

The internal systems were not built in the early stages of the business, which made training new staff a slow and challenging process.

Pressured by time constraints and deadlines, our analysts had to process a lot of new information in a short amount of time.

This slowed the processing of each individual report greatly, as our thorough control systems had to ensure a quality product was being delivered.

An early investment to build some semi-automated software to facilitate building the reports might have been the answer.

Yet, at the time, we were determined to test the concept before investing too much.