Top 10 yet2 Blog Posts of 2018

AI, machine learning, tech scouting, CVP & more

Our team wrote a number of widely read blog posts in 2018, spanning the topics of artificial intelligence (AI) and machine learning, adjacency in tech scouting, startups and their comparative value proposition, anonymous searches in tech scouting and more. Here’s a recap of those blog posts.

Tech Scouting Blog Posts

Tech Scouting: When to Initiate an Anonymous Search

Many of our clients engage yet2 for “traditional” tech scouting services – Strategic DealFlow, where we source step-change opportunities for clients, Topic Specific Scouting, which is when we are focused on finding the right solution to solve timely challenges with specific requirements, and Innovation Tours or Virtual Hubs, which has us scheduling meetings with 10-15 promising potential partners, or where we develop a regional innovation hub for a client.

Adding to that roster of open innovation services, over the past 12 – 24 months, several of our subscription clients have asked us to perform anonymous searches for them. There are a few general reasons why a company might be searching for new technologies, products, or ideas and not want to reveal who they are (and we’ll go into them below). In all anonymous searches, the client has decided they need more information in order to make a go/no-go decision. The challenge for many companies is how to get necessary information without the risk and exposure inherent in revealing their identity to opportunities of interest.  In essence the company does not want to show its cards, yet must keep playing the game. Hence the need to engage a partner like yet2 to conduct an anonymous technology search or due diligence inquiry.

Exploring Adjacency in Innovation & Technology Scouting

Scott Simpson Cohen, co-founder of Innovation Leader recently wrote about challenges in scouting for technology and emerging trends, based on his organization’s new research, “Best Practices: Scouting Trends & Emerging Tech.” One of the issues Cohen cites is “identifying the right areas to scout” and that “what’s holding large corporations back … is that they don’t know where to look – many only hunt near their headquarters, or at their annual trade show.”

This is certainly true, and it is why technology scouts and organizations must embrace the concept of adjacency in their scouting efforts. That means looking not just beyond your region, but to other continents, and not only at your industry’s annual tradeshow, but also at other industries’ tradeshows and emerging technologies conferences.

 

AI and Machine Learning Blog Posts

Applying AI and Machine Learning to Patent Data Analysis

Artificial intelligence (AI) and machine learning techniques are changing the world of patent data analysis.

A patent document is a well-structured document, with title, abstract, claims, and description all clearly defined. Patents and applications are also classified using one or more standardized classification codes. These facts make patent data very suitable to be processed with machine learning techniques. Indeed, computer science researchers and service providers in the patent industry have been using AI in patent data analysis for a long time. For example, patent landscapes created with the assistance of text clustering methods were already commonly available before 2008. However, 10 years ago, AI methods didn’t play any important role in patent analysis because a large number of people either didn’t pay enough attention or just didn’t think about it; and for those who did, they often felt that the algorithms were difficult to implement and the results were not very accurate. In short, patent data was ready for AI, but not the other way around.

Is the Tipping Point for AI Here?

Artificial intelligence (AI) is poised to change how we work, play, and live, but it may not change things nearly as quickly or as impressively as today’s hype claims it will. In the words of Gary Marcus, commented during the Open Data Science Conference, “We wanted Rosie the Robot and we got the hockey puck Roomba.” The reality is that AI, machine learning (ML), and deep learning (DL) capabilities today lie somewhere in the middle.

The hype around AI is nothing new; in fact, this is actually just the latest wave of the “AI will solve/change everything” excitement. From Alan Turing and his 1950 paper, “Computing Machinery and Intelligence,” to AI flourishing from 1957 to 1974, to resurgences in the 1980s, 1990s, and 2000s. Clearly there’s been no lack of interest, expectation, and promotion around the promises and potential of AI. The pitfalls have been in the expense, processing power, and context for AI to become a reality.

The first question we should ask is: are we finally at the tipping point for AI and machine learning?

 

Bolstering Startups’ Comparative Value Proposition

The world of startups is fast moving, exciting and innovative.  The agility of a small business and the enthusiasm of founders executing on their cherished ideas means startups move fast, pitch often, and put investment dollars to work quickly. The most successful startups have identified an important problem to tackle, and even more importantly, they have developed a clever way to solve that problem.

At yet2, we have the privilege of speaking with innovative startups, researchers, and inventors daily as we reach out to the community to find the best partners to solve our clients’ technology and partnership needs. Over the last 19 years, we have had the opportunity to review and hear the best and worst pitches, product brochures, and websites, and if we could provide one piece of advice to the startup and inventor community, it is this: know your comparative value proposition (CVP). More importantly, know how to convey your CVP in a way that goes beyond “marketing speak” to specific, quantitative, truly comparative points.

 

Industry Spotlights

Trends Shaping Innovation in the Personal Care Industry

There are a number of global trends in the personal care industry that are shaping the open innovation needs of both mid-sized companies and large global brands. How these companies embrace innovation can have a big impact on their bottom line. The global personal care product market is forecasted to reach more than $650 billion by 2024. In the U.S. alone, the personal care market is more than $36 million annually, with an expected annual growth rate of 9.3%. User penetration is at 28.3% and is expected to grow to 33.1% by 2022. The Asia Pacific region holds the largest market share and is expected to maintain its dominance in the market.

Technical Trends in the Oil & Gas Industry

The oil & gas industry faces a fundamental challenge: managing the business in what is an intrinsically volatile sector. It is often difficult for any business to balance both short-term and long-term goals with inherent volatility; understanding the enduring and emerging trends within the oil & gas industry is essential for layering meaningful innovation on top of the complexity of the business. One might easily shy away from innovation because of the unstable nature of the industry; however, that is exactly the wrong approach to take. Innovation is the key to optimizing productivity, developing new revenue opportunities, and uncovering unexplored approaches to enhancing the business.

 

Innovation & Retail Blog Posts

The Future of Retail: Embracing the Experience Economy

The death of the mall – and traditional brick and mortar retail – may or may not be over-exaggerated. But today’s environment certainly creates an opportunity for traditional retailers to change how they approach their business, and even possibly change their entire business model.

For the most part, brick and mortar stores cannot compete (and win!) with online retailers based on price or convenience. Whether it’s shoppers selecting products in-store, and then purchasing them from an online retailer at a cheaper price, or free(ish) next-day or same-day delivery from Amazon or Walmart, traditional retailers who try to compete there will more than likely lose. Instead, the retailers who will win will be those who embrace the experience economy and do so in ways that are on-brand, enhance customer engagement and exploit customer enthusiasm.

Can Innovation Save Retail?

For Baby Boomers and Gen Xers, the stores of their youth are disappearing. While Toys ‘R’ Us is the latest major retailer to liquidate and close, the U.S. retail market has also seen Sears and J C Penney close many locations. Claire’s, a mainstay of many shopping malls, recently filed for Chapter 11 bankruptcy protection.

There’s a widespread perception that malls across the U.S. are dying. But according to “Consumers Match Analysts’ Confidence in Malls,” research shows “about 165 million consumers went to a mall in the past three months” and that “82% of adults believe that shopping malls will still exist in the next five to 10 years.