Trendscape :: Crowdourcing Future Trends Monitoring
For most of my career at Intel I’ve been a contributor to the processes it has used for future trends forecasting. Not long ago, I was asked to take the reigns of the program and do a total re-design.
01 Background and Goals
Intel Corporation, my former employer, has a long history of incorporating future forecasting methodologies into its strategic and product planning processes, driven both by the 3-5 year length of its product development cycles and the massive investments of time (3+ years) and capital (>$1B) it takes to build new manfacturing “fabs”. Intel Labs, Corporate Market Research, and Corporate Strategic Planning have all collaborated in this process since the early 2000s, and I have been a contributor for most of that time in my role as a UX researcher. In 2017 I was asked to take over its management and totally redesign the methodology for collecting trends signals and disseminating those to the various business units. A heavy emphasis was placed on actionability, and much of my charter was focused on driving these trends observations into the corporate planning process, incubating new product ideas, and launching major corporate initiatives.
02 Methods
Getting Started - Although we were given an ambitious charter, we also had a much smaller budget for primary research than in years past, so I was forced to develop a new solution that increased actionability of results without sacrificing quality of insights. After doing some benchmarking, I developed a recommendation to crowdsource the effort of sensing trend signals across the company. I split the task of “reporting” into 8 “beats” similar to the figure on the right. And rather than doing all the work within my team I recruited “beat reporters” from across the company from functions as diverse as economists, ethnographers, research scientists, and product strategists. This helped us leverage the vast amount of content expertise and networks across the companies as well as increase buy-in from different groups we waanted to influence.
Managing Bias - Working with a regular set of contributors as “reporters” within their area of expertise allowed us to build the function around this cross-functional set of contribitors.
We put them all through futures analysis using intact training from Institute from the Future, so that we were all working from the same methodologies for trend sensing.
We met regularly as an editorial board to review each others’ signals and provide input. To insure that we were not overly weighted on technology or social trends given the expertise of the panel, I facilitated discussions using tools like PESTEL (right) to insure a diversity of viewpoints.
We also did an annual review of our own trends observations, comparing them with those from sources like industry analysts (Gartner, IDC), social scientists (Pew, IFTF) and other companies.
Tools and Scalability - As the success of the program grew, we needed to install a set of processes to insure accessibility of the materials we were publishing.
We developed a standardized template for summarizing our trends observations (right), which we used to socialize the high-level analysis across the company.
We adopted a knowledge management platform developed specifically for trends sensing, which we used to capture the underlying “signals” data we were using in our analyses.
We adopted AI-based analytics tools to help us do quick analyses of news articles or technical journals to help us detect emerging trends
03 Insights/Actionability
TrendScape has been a huge success for the planning community at Intel, as it has been an effective vehicle for injecting into the corporate strategy discussion of emerging opportunities and threats facing the company. This analysis was really the beginnings of these discussions…if we uncovered a trend of major interest, an executive would frequently sponsor a more in-depth analysis of the topic at hand. We can count as successes having spurred high-level executive discussions on topics like ethical AI, the growth of AI in edge applications, trust in technology, and sustainability.
04 My Learnings
Thinking productively about the future should not be the domain of a single individual like a CTO.
In fact, technologists, businesspeople, and social scientists all have valuable perspectives on the evolution of the business, and the work of understanding the future of a business is best done by a cross-functional team.
That said, to make the process of futures thinking productive, its best to consistently use time-tested analytical frameworks (like PESTEL), as well as build processes and infrastructure that plug into existing planning processes in the company if possible.