With the startup world so fragmented, how should you as a corporate innovation scout approach it?
Our research process focuses on organizing the chaotic startup landscape into sector reports (such as Financial Technology) comprised of smaller functional categories (like Business Lending, Consumer Lending, and Retail Investing). Each category is in a different state of innovation and thus requires its own game plan.
We have developed the Venture Scanner Innovation Quadrant to act as a framework to guide you in the startup scouting process. Our Innovation Quadrant organizes categories into four states of innovation by plotting the sector categories on two axes. One axis uses average age to show maturity. The other uses average funding to give a sense of traction. These scores are then normalized to draw out distinctions. Knowing which quadrant each category sits in our Innovation Quadrant will help in developing your scouting strategy.
As an example, here is our Financial Technology Innovation Quadrant that is part of our Financial Technology dynamic report.
The four quadrants are Pioneers, Disruptors, Heavyweights, and Established. Each quadrant presents a viable and unique innovation opportunity for a corporate startup scout. In the table below we summarize the four quadrants and opportunities that exist for corporate innovation.
In summary, categories at all stages of traction and maturity present innovation opportunities for your corporation. Dive deep into the Pioneers categories to explore experimental new technologies, scan the Disruptors categories to ensure your company has the right defensive plans, identify possible cash cows in the Established categories, and look for big growth opportunities in the Heavyweights categories. A successful scout will continuously be executing across these quadrants. Leveraging the Venture Scanner Innovation Quadrant as a framework will jumpstart the development of your innovation strategy.
Successfully engaging with the startup community will not only give corporations a competitive advantage but can also mean the difference between future relevance or demise. As a result, corporations of all sizes are launching innovation programs. The corporations’ objectives are chiefly to understand the innovation trends, identify potential disruptions in their markets, and find startups to partner with, invest in, or acquire. These efforts are typically run by a head of innovation, a chief strategy or digital officer, or a corporate development function.
So how should corporations engage with startups and what pitfalls should they avoid? Based on our interactions with corporations of all sizes and from all industries, we see engagement models that work well and others that leave room for improvement. We summarize our key findings in three themes here.
EDUCATE: Gain a broad understanding of an emerging market’s scope and activity and define your corporate objectives in response.
ASSESS: Research the startups that compete in the market and create an unbiased shortlist of candidates based on your corporate objectives and investment parameters.
ACT: Engage with the best startups that align with your corporate objectives and desired business outcomes.
1. EDUCATE: Gain a broad understanding of an emerging market
Often times when a corporation looks to make an innovation play or a financial investment in a particular category, the immediate impulse is to reach out to startups that they have seen repeatedly in the media. Similarly, the corporate “scout” might reach out to venture capitalists or an accelerator in their network, which by design leads to biased referrals. Other paths may include sponsoring an incubator or arranging a Silicon Valley tour.
All of these tactics limit your exposure to the startups within your network and thus cloud your view of the market as a whole. And while they may help spark some innovation inside an enterprise, they by no means remove the hard work needed to gain a complete picture of an emerging market. The absence of that broad perspective will introduce risk into your process, whether you’re looking for M&A, equity investments, or strategic partnerships. When done right, this step with foundational market intelligence sets the stage for the mission critical decisions that follow.
2. ASSESS: Define an unbiased shortlist of startups
Understanding an emerging market is one thing but narrowing a field of hundreds – if not thousands – of startups down to a manageable shortlist for your objectives is hard to do. The key to the shortlisting process is to avoid bias. The inputs into this step should include your unique corporate and product strategy, as well as the startup characteristics that will best align to that strategy. As part of this filtering process, it’s wise to conduct interviews with startup candidates to gain a deeper understanding of their product roadmaps and sources of differentiation. Most organizations are not well resourced for this, so an objective partner is invaluable. The output of this step is a shortlist of startup candidates based on an unbiased process that brings to the forefront the companies that have the strongest strategic fit. Once a firm shortlist of startups has been established, it’s time to move into the action phase.
3. ACT: Take meaningful action that drives results
At the core, corporations and startups have very different cultures. Large companies are typically process heavy and exhibit an overabundance of caution. To a startup, large companies can seemingly spend an enormous amount of time and resources on analyzing, while showing little to no signs of acting. On the other hand, startups are resource constrained, so they must invest those resources only in places that can lead to immediate traction as measured by revenue, customer growth, or the next round of funding to keep their nascent business afloat.
Therein lies the major challenge. In order for startups to justify spending time with a corporation, they will want to see skin in the game. Whether it be by becoming a paid customer, engaging in a paid proof of concept partnership, or some other commercial relationship, a startup will take the corporate partner who takes real action seriously and will be quick to shy away from those who want to spend endless hours in meetings without taking action. Corporations that make early bets on startups will gain the loyalty of the startup as their company and product mature. Startups will treat such corporate partners like family, for they not only took a risk, but they did so with skin in the game that did not guarantee a future return. The common ground in these situations is typically the “fail fast, fail cheap” mantra.
So, if you think you spot a startup that can give your corporation a competitive advantage, think through the three steps above and answer these key questions: Are you sure you’re starting from a broad understanding of the market? Are your information sources unbiased and credible? Are you willing to engage with a sense of urgency and take meaningful action? These are critical considerations as you attempt to drive profitable innovation inside your organization.
The future success of incumbent corporations across all industries rests on their ability to successfully monitor, assess, and engage with an increasingly chaotic startup and innovation ecosystem. We are excited to announce that Forrester and Venture Scanner have formed a strategic partnership to help you in every step of the process. To learn more, join us at our upcoming Podcast in November, or reach out to Carl Doty (firstname.lastname@example.org) and Nader Ghaffari (email@example.com).
Artificial Intelligence (AI) technology startups seem to be in the news all the time. Is that hype, or are AI startups truly seeing major interest from investors? Using our research platform, we can conclude that interest in AI absolutely exploded in 2017.
We come to this conclusion from the following takeaways, each of which tracks a different metric for interest in AI startups:
AI funding grew exponentially in 2017
The number of AI deals is increasing
Investor interest in AI is growing
We’ll illustrate these takeaways with a series of graphs to show the extensive growth in AI.
AI Funding Grew Exponentially in 2017
Let’s start off by looking at AI funding trends over the past 6 years. Here is the annual amount of AI startup funding, stacked by quarters.
AI funding has been on an upward trend over these past few years, with a rapid explosion in 2017. Total funding in 2017 was over 3 times the size of 2016 funding. The Compound Annual Growth Rate (CAGR) in funding grew by a whopping 85% in the timeframe of interest (2012-2017).
This funding growth is substantial news on its own, but are there other metrics showing a growing interest in AI? Let’s see what the total number of deals looks like.
AI Deal Numbers Are Up Over 5 Years
The following graph shows us the annual number of AI startup funding deals, stacked by quarters.
Over the past five years, this graph shows an increased interest in AI via the number of deals in that startup ecosystem. Whereas the rapid growth in funding occurred in 2017, the rapid growth in deals occurred in 2014. The six-year CAGR on the number of deals stands at 23%. 2017 is also the highest year on record, beating the previous high in 2015 by around 2%.
So, we’ve seen that total funding and the number of deals are expanding, how about investor interest?
Investor Interest in AI is Growing
To gauge how investors are feeling, let’s look at the total number of AI investors who participated in each financing round. For example, if 5 investors participated in funding one company, and 4 investors participated in funding another, the total investor interest metric would be 9.
This graph clearly shows increased investor interest over the past few years. The six-year CAGR is 31%, and the 2017 total is 21% larger than in 2016 (the previous annual high-water mark).
Conclusion: Interest in AI is Exploding
In summary, we’ve seen significant growth in the total amount of AI funding. At the same time, the total number of AI funding deals has been steadily growing. Moreover, the investor interest in AI seems to be on a linear upward trend line. Taken together, we can say the AI sector is experiencing a rapid growth in interest over these past few years. It’ll be interesting to see if this trend continues into 2018, or if we travel into the “trough of disillusionment”.
What are your thoughts on this? Let us know in the comments section below.