The world economic forum at Davos two weeks ago declared the Internet of Things is here and proceeded to agonize over the potential perils of the Fourth Industrial Revolution. There was recognition that whilst digital transformation will create a better world, there are significant challenges such as changes to investment cycles, consumer trust, regulation, privacy and employability to be navigated.
At SAS, we see IoT as the future of technology that can make our lives more efficient. It embodies the concept of everyday objects ranging from industrial machines to wearable devices that use built-in sensors to gather data and take action on that data across a network. Implicit is the analytics that fuel IoT. As Tom Davenport declared, “To make the Internet of Things useful, we need an Analytics of Things.”
We now have a wealth of big data projects that can help us design better IoT analytics journeys. There are typically three categories of challenges to negotiate.
Data congestion. It always starts with the data, and managing data is harder than anyone anticipates. With IoT, the complexity of real-time and location sensitivity will add to the challenge of acquisition, cleansing and management of data required for analysis. And we have seen the predictable ‘who owns the data’ debates before too.
Golden use cases - Inspiration to design differentiating algorithms requires radically different thinking. Including an open culture and a supportive environment for play and experimentation. As Andreas Goedde pointed out, facilities like big data labs will help your scientists and business users re-frame their possibilities and generate new value to your business.
Deployment and model management - The IoT analytical lifecycle is likely to be highly iterative and interactive. It will require operations teams and business users to be enthusiastic about re-imagining their workflows or customer values.
The business model challenge
Ultimately pervasive analytics have led to business model changes. These model changes will be more profound as IoT powers more insights, faster. For many companies, a global economy that is 25% digital will mean erosion of profits; efficiency is a beautiful concept unless your business profits from these inefficiencies.
Traditionally, analytics has been seen as a back-office function. Implemented in isolation by different departments and lines of business. The full promise of bigdata and IoT will drive the embedding of analytics into real-time business decisions by deploying predictive models into transactional systems and customs facing processes. Realizing this promise will challenge many traditional business models.
We expect companies that are successful in today's business environment may need to collaborate with unconventional partners in order to discover new addressable markets. As my colleague Oscar Lindquist points out the IoT will be wasted without appropriate risk taking about those seeking to profit from it.
IoT and the massive digital avalanche will also favour companies and teams that master the art of doing. Just as software developers have embraced agile methodologies which challenged conventional development cycles, we see business leaders needing to adapt to faster turnaround of ideas. We expect scrum masters to become popular across organizations.
IoT analytics maturity
Recent research of US businesses suggests that the most digital companies are widening the gap between themselves and the rest of the market. These companies have increased their productivity and boosted profit margins by two to three times the average rate over the past 20 years. Digital capabilities are closely linked to innovation, growth, productivity, and even business model disruption. IoT will become an increasing component of this ‘digital quotient’.
Given the speed of change, we believe more knowledge sharing is needed. Which is why our analytics subject matter experts have done a study across EMEA to explore critical success factors for exploiting IoT. Read the e-book Internet of Things: Visualise the Impact and learn more.