The internet of things revolution is in full swing; IoT devices are everywhere and becoming more significant in our lives. These devices can report back how they are being used and what issues they encounter. A real flood of data is available from connected devices and might be profitably used, particularly by companies that understand the real value of the data. A new world is opening its doors, offering opportunities for companies who want to improve the customer experience, and to create new business models, based on big data technologies and analytics. The future and real value of the IoT is in the data. The winners will be those who can collect and analyze the data, and innovate, becoming data-centric.
The prospect of becoming a data-driven company is alluring because of the expected ROI created by product optimizations, lower operating costs, customer service improvements, and so on.
The first step to achieve this goal is to design and build an effective data factory that can rapidly grow and dynamically adapt itself to future challenges. The rules are simple: be able to ingest tons of data streams, store everything on the fly, and enable data scientists to query the material.
The second step is to define a way to extract meaning from the huge amounts of collected data, to improve decision making. Comparing all analytics possibilities might be a daunting task but, in broad terms, they can be categorized into three types:
Descriptive – Uses data aggregation and mining to provide insights on past or present events.
Predictive – Learns from historical data and builds relevant statistical models for future insights.
Prescriptive – A set of techniques attempting to quantify the consequences of future decisions, providing recommendations based on predictions.
There are many domains in which data and analytics could achieve a company’s goals by enhancing the capability to collect, analyze, and report data about how the customer uses a device. This capability might help in generating actionable insights:
- Moving to consumer-centric products. Companies might give added value to their products by understanding real-world usage and consumers’ needs, so they can design better, more useful products, instead of creating redundant, unattractive, or hard to use features.
- Implementing effective and proactive maintenance. Companies may learn about problems directly from their own products, and remotely discover, diagnose, and fix issues as they happen. Taking such action will reduce warranty claims and achieve greater customer satisfaction.
- Integrating with third-party data providers. By adopting standard protocols and data formats, companies should integrate with third-party data providers to produce more accurate and precise services. For example, a home security company would like to sell sensors that warn about window glass breaking, but won’t produce false alarms due to bad weather. One solution might be to integrate its data with the data for weather forecasts, or even with real time meteorological events. In this way, IoT companies could commit to delivering top quality precision services.
- Making use of predictive analytics and preventing issues before they happen. Companies should learn from their historical data. The effective way to do so is to collect substantial specific problem related data, and, thanks to the efforts of talented data scientists, build learning models that will be able to predict future behavior. These statistical models could, for example, optimize the role of service technicians by designing routes including geographically grouping of the areas anticipated to need visits. On the commercial side, predictions based on customer data will improve marketing campaigns by making audience targeting more effective; for example through classifying needs by gender, usage, geographic, or even demographic properties. These types of procedures could be the best strategical answer to customer churn, by paying attention to customer dissatisfaction before it turns into customer loss.
Every action of a connected device creates new information that can be transmitted, crunched, munched, analyzed and, at the end, can be actionable. Every such piece of information can participate in a new strategic process, creating deep business insights. As we enter a new era of technology, nobody knows what the winning business models are going to be, but surely, “it will be those companies that view data as a strategic asset that will survive and thrive.” – Bernard Marr.
At Essence we aim to give IoT data real value. We connect devices to the internet, collect their data and build models that produce business insights. We turn companies into data-driven innovators.
The writer of this post is Gabriel Benaily, Essence’s Big Data & Analytics Director, responsible for designing and managing big data solutions.
