By applying analytics to the sensor data, it will be possible to communicate remotely with ‘things’ to alter their state, and repair and prevent malfunctions. Which means ‘things’ manufacturers can spread their wings and become value-added service providers by applying analytics (Analytics of Things), and predicting failures and enabling preventive maintenance. This saves money, keeps customers happy, and enhances revenue. In addition, it will lead to the disintermediation of the after-sales-service industry by allowing them to provide their product-as-a-service.
Consequently, the customer experience will be improved on all fronts. Customers will have greater choice in markets like automotive service providers – Tesla versus traditional car manufacturers, dealers, aftermarket accessory suppliers, service & repair shops, and so on.
So, how do established industries keep ahead of the curve?
While product-as-a-service may sound new and interesting for manufacturers, many industries have enjoyed a lifelong advantage of not keeping physical products or inventories – Financial and Telecom service providers who view service, itself, as their product, for instance. It allows greater flexibility and agility in creating service products at different price points to match the market-segment mix.
Analytics helps mature industries keep ahead of the curve.
This is in complete contrast to products (goods) that require significant up-front investment to fund production and operational expenditure for the sales distribution network and inventory. Physical goods rely on engineering design quality and reliability to keep customers satisfied.
Always at your service
Whereas with service products, customer satisfaction is a by-product of reliable service infrastructure. Just think; how frustrating is it when the set-top box you ordered fails to deliver the soccer final you’ve been anticipating for weeks? Or when the ATM is out-of-order when you’re all out of cash? And what if your mobile service provider repeatedly refuses to let you make that emergency call?
Analytics helps mature industries keep ahead of the curve. Path Analysis is great for predicting failures of Consumer Premises Equipment (CPE) and/or infrastructures before they arise, helping to manage customer expectations, too. Path Analysis is also good for predicting path-to-purchase and path-to-out-of-stock-situations during the acquisition stage of customer lifecycle management.
Outside-in, not inside-out
Creating a competitively-priced service product is relatively simple compared to manufacturing CPEs (which require break-even points to be profitable). However, many organisations create one-size-fits-all service products. Mortgage financing and mobile price plans are typical of this kind of inside-out product development thinking.
I mean, why not develop a personalised price plan that fits the individual customer’s lifestyle instead? This type of outside-in thinking requires the application of discovery analytics to investigate and understand customer buying decisions / behaviours, and to fashion a properly-aligned service product. Every Telecom service provider has detailed data from their customers’ service usage which can be used to simulate various tariff plans, and calculate the best margin they can achieve while helping customers save into the bargain. This weapons-grade knowledge is intel that the enemy doesn’t have – a silver bullet in the war against churn.
What can IoT do for established industries?
Telecom service providers are best placed to take advantage of IoT by offering end-to-end service (communication, sensor data collection / management in the cloud, and Big Data analytics) to vertical industries such as Health, Mining, Automobile, and Electricity Distribution.
Financial service providers can reduce liability risk and optimise lending revenue by performing geo-spatial analytics on geo-fenced mortgage collaterals such as ‘fleet of vehicles’ and mining equipment. This means they can predict performance and levels of wear & tear using multi-genre analytics on IoT sensor data.
Car insurance companies can offer personalised premiums in exchange for data collected from driver behaviours and driving conditions. Transport and logistics companies can track traffic violations, and improve the safety of drivers and road users on a continuous basis. And there are many other examples of traditional industries using IoT to keep both new and existing competitors at bay.
Sundara has been a Telecom professional for over 30 years with a wide range of interests and multi-national experience in product management, solution marketing, presales for new generation networks and services, information management strategy, business intelligence, analytics and enterprise architecture development.
At Teradata, Sundara focuses on Business Value Framework, Business Outcome, Business Value Consulting, Business Intelligence, Discovery Analytics and Customer Journey / Experience Management solutions.
Sundara has a Master’s Degree in Business and Administration with research on economic value of information from Massey University, New Zealand.
For the last 20+ years, Sundara has been living in Sydney, Australia. In his spare time, Sundara enjoys walking and maintaining an active life style. Sundara is an inventor and joint holder of an Australian patent with his clinical psychologist wife. The invention is an expert system in cognitive mental health that applies machine learning algorithms.