Having the time to vet the increasing number of promising startups is a common problem manufacturers face. But what if companies could harness Big Data and highly technical algorithms that could save time and money while delivering the most promising and relevant startups to their conference tables?
Enter: The Classifier from crowdfunding investment platform CircleUp.
Collaborative Fund, which has played a role in food and beverage investments like Hampton Creek, SOMA Water, and Beyond Meat, recently partnered with CircleUp to create a new fund, Collab+Consumer. Collab+Consumer’s primary focus will be on companies in the consumer space, including food and beverage, that are making an impact on the world.
CircleUp’s contribution is providing its proprietary machine-learning algorithm tech, The Classifier, which the company has been developing for years. Collab Fund will use The Classifier to vet potential companies based on a wide range of economic, market, and experiential factors. It will apply its own "impact" filter on the targets proposed by The Classifier to identify companies that are among the most promising and also fulfill the fund’s mission.
The Collab+Consumer fund and its use of CircleUp’s Classifier technology demonstrate the power Big Data will have on investment decisions and how manufacturers can optimize due diligence processes going forward.
Benefits of data-driven due diligence
Computing technology and machine-learning algorithms like The Classifier are enabling companies to consider more data points (over 92,000 in the Classifier’s case) more quickly to better tailor their potential investments while freeing up time for other pursuits.
Implementing deep data science during the due diligence process offers a number of benefits:
- Can include more pieces of data from more sources (including those that would be tedious to use, such as online ratings and reviews)
- Can more easily filter data to tailor which startups to look at
- Saves time on data collection, calculation, and analysis
- Improves effectiveness and efficiency in target identification
- Removes human bias and inaccuracies
- Enables investors to spend more time strategizing growth plans and creating value for the startup rather than having to do the legwork to find the right targets
"It’s an incredible thing for an investor be able to focus on fewer, better fit deals and also know that you’re not missing something by looking at all of the rest," said Katie Johnson, manager of business operations at CircleUp.
Digging deep: Big Data at its best
With Classifier, while the 92,000 data points and algorithms are proprietary, Johnson said that general categories of data the technology takes into account when vetting startups might include:
- Company financial performance
- Management team, including background and experience
- Industry and competition data
- Category growth and trends
- Competitive nature of the category
- Category’s M&A potential
- Distribution, on a deeper level
- Product and brand ratings and reviews
- Pricing information
- Customer distribution
- Social media engagement, on a deeper level
- The deal’s exit potential
"Going through reviews and ratings can be really cumbersome, but Classifier allows us to go a lot deeper and use a lot more data," said Johnson. "It’s not to say that investors don’t already care and look at distribution when they’re looking at a consumer business. It’s just the depth that you can go into and the amount of data that you have at your fingertips are elevated by the Classifier."
Whether through Classifier, another existing algorithm, or proprietary technology developed in-house, manufacturers can harness the power of Big Data to make better educated decisions while improving the efficiency of the vetting process.
Who stands to benefit
A capital infusion isn't always enough to seal an acquisition or investment deal. A more data-driven approach offers various benefits to different investors that can help them be more competitive in the acquisitions race.
Strategic investors (manufacturers)
In recent months, several major manufacturers have announced the founding or expansion of their investment arms, from Hain Celestial's Cultivate Ventures and Campbell's Acre Venture Partners to General Mills’ 301 Inc. and Coca-Cola’s Venturing and Emerging Brands (VEB) segment.
If manufacturers could capitalize on the efficiency of a more data-driven approach to vetting startups, they could land on golden opportunities before competitors, which are growing in number. But it’s still crucial for manufacturers to trust in their due diligence process to weed out seemingly good investments that may end up fizzling, as many startups do. Bringing more data into the equation in a manageable and efficient way gives manufacturers the advantage in this space.
Sometimes it can be harder for private equity and other investment firms to compete with manufacturers for the best investment and acquisition targets, Anthony Valentino, deputy editor at Mergermarket, told Food Dive. Investment firms, which may be more removed from the industry itself, don’t always offer the value add that manufacturers can bring, such as distribution or supplier relationships.
To remain competitive, investment firms can use a data-driven vetting approach to identify startups not yet on manufacturers’ radar or that the firm feels it can offer specific value to, based on the investors’ experience and relationships.
Other potential benefactors include food and beverage industry accelerators like AccelFoods, which debuted a new $20 million fund in February, and Food-X, which recently announced its latest cohort of startups. Anheuser-Busch InBev also recently launched an accelerator, Techstars Connection, a partnership between Techstars and AB InBev’s venture arm, ZX Ventures.
Accelerators are often the first step for startups before they end up in front of an investment firm or major manufacturer. Data-driven approaches could help accelerators solidify their position as innovation identifiers and make them a go-to resource for investment and acquisition targets by other investors.
When harnessed through algorithms like The Classifier and other premium vetting technologies, Big Data has the potential to revolutionize the due diligence process for manufacturers. It can enable them to make strategic investments and acquisitions that expand their portfolio and ensure their growth capitalizes on current and future trends.
"Within early stage consumer, historically this was an underserved segment where entrepreneurs with really interesting consumer businesses were struggling to efficiently raise growth capital," said Johnson. "So we are creating a marketplace that allows for that investment and that fundraising for earlier-stage consumer companies to happen — and to happen more efficiently and more effectively."
Check out our Food Startups Directory to find some of the brightest innovators in the food and beverage industry.