The Million-Dollar Startup – Can Enterprises Adopt a Green Field Mentality?

  /  Industrial IoT   /  Connected Industry   /  The Million-Dollar Startup – Can Enterprises Adopt a Green Field Mentality?
a new business model 1

The Million-Dollar Startup – Can Enterprises Adopt a Green Field Mentality?

Why is it so hard for enterprise organizations to act like the startup companies they increasingly come up against? It’s a very good question. In every industry, across every vertical we see new businesses emerge from seemingly nowhere, impacting the market landscape. What is it that prevents our largest companies from adopting a similar path, rather than being victims of disruption? And, more importantly, what can they do about it?

An essential tool in enabling an established company to behave more like a startup is analytics. As we work with a diverse range of enterprises to deploy analytics solutions, we come across many situations that startup companies simply don’t have to face. We can summarize them in a single word: complexity. Technology-led startups really do benefit from that mythical ‘green-field environment’ denied incumbent organizations; they also lack the legacy thinking, operational models and related constraints that can tax even the most forward-thinking companies.

The first step along the path to acting like a startup, therefore, is to think like one from the very top. Enterprises have a choice: either they can adopt a top-down digital transformation strategy (we see many organizations telling their shareholders that this is the plan), or they can create a new business unit and give it the autonomy to work in the same manner as a startup.

In either situation, we believe that success comes from managing scale at every stage. No organization, big or small, can be all things to all people: too many technology options exist, too many potential markets to tap. Rather, the organization (or its nascent satellite) needs to adopt a step-wise approach in which strategic business ideas are identified, tested, and built upon. Think it,  test it, improve it, rinse and repeat.

The language around this approach does not matter. Some practitioners and commentators talk in terms of agile business practices, others use terms like ‘fail fast’ or DevOps, but they all boil down to an approach which sees the speed of innovation as the most important metric. When an idea works, it can be built upon; if it is less successful, then it will generate lessons for the future.

In our eGuide Putting Analytics in the Driving Seat, we advocate a business-led approach which incorporates a technical proof-of-concept exercise to determine what data is most valuable to the business, how it can be delivered and what its impact will be. Successful analytics only empowers the business if it delivers the right insight to ready fingertips: in many cases, lines of business need to learn what insights they need, even as they grow their own capabilities to use the insights to drive the organization forward. The more they experience the value of analytics, the more they’ll see new and diverse opportunities to use it.

In these situations, an innovation-led approach is as much about helping the organization to transform and grow in the data age, from the executive board to front-line staff, as it is about delivering the right technology infrastructure and platforms. Even in an uncertain world, it only becomes possible to create a comprehensive business case for new technical infrastructure if its costs can be weighed against clear business benefits.

Keep in mind that all disruptive startups have had to achieve ‘escape velocity’ – for every Uber or Airbnb, hundreds of well-meaning organizations with similar business models have failed to deliver, grown too slowly to matter, or simply run out of cash. Sooner or later, all organizations face a wall of complexity that only the strongest can surmount, and the companies that manage to breach this wall are in a minority.

We have helped many organizations efficiently manage and rapidly harness their data, with analytics success stories right up to advanced analytics such as deep learning and AI. We also speak to organizations that are reticent to try again, having hit challenges on the journey. In this rapidly changing digital landscape. While the path to data-driven success offers no guarantees, innovation-led approaches offer the best chance.

Learn more about how advanced analytics can help you transform your business, and what you can do to make it happen, by reading this new eGuide from Intel.

Find more information on data-driven insights and advanced analytics by visiting our Turn Data Into Insight website, where you can find it all in one convenient location.


This article was written by Jeremy Rader and originally it was published here. Jeremy, Director of Data Centric Solutions at Intel, is responsible for enabling business transformation by driving Analytics, AI, and HPC solutions, while driving next generation silicon requirements.