Michael Lissack
informed their decision to begin developing streaming capabilities years before broadband penetration made it commercially viable. Later, Netflix’s data gathering revealed emerging patterns in viewer behavior that sug- gested original content could become a competitive advantage. This in- telligence led to their transformation into a content creation powerhouse. The difference between these companies wasn’t just the quality of their intelligence—it was how effectively this intelligence was integrated into organizational sense-making and decision processes. In today’s com- plex digital environments, this integration has become both more chal- lenging and more essential. The Evolved Intelligence Landscape Traditional intelligence gathering focused on competitive analy- sis, market research, and environmental scanning—relatively struc- tured processes aimed at collecting information about known variables. Organizations would dispatch scouts (often in the form of market re- searchers or competitive analysts) to gather specific types of information according to predetermined frameworks. Today’s intelligence landscape is fundamentally different in four crit- ical ways: First, information volume has exploded exponentially. The amount of data generated globally each day now exceeds what entire or- ganizations could process in years using traditional methods. This volume creates both opportunities (unprecedented access to information) and challenges (overwhelming signal-to-noise ratios). Second, intelligence sources have democratized. Valuable insights no longer come exclusively from official reports, industry analysts, or formal research. Crucial signals might emerge from social media conver- sations, open-source software repositories, customer reviews, or sensor networks. The boundaries between “formal” and “informal” intelligence have collapsed.
206
Made with FlippingBook. PDF to flipbook with ease