“We are no longer a bank, but a technology company": IOT in phases, the customer-centric and in
“I have the feeling we are no longer a bank, but became a technology company”, a CFO of a huge bank recently quoted. He might be right. Let’s see why.
In a previous article I mentioned the staggering economic impact IoT will have. However that assumes the issue of interoperability is further evolving into ‘the dinosaur’ of integrated IoT applications. For various reasons the interoperability of IoT applications will be evolving during time:
The adoption curve that enterprises have towards IoT; it will take time before enterprises fully realize the value of IoT to their market or industry. A huge amount of enterprises will wait for the market to become more mature before seriously investing in interoperable IoT applications
The technical complexity of IoT applications to get the interoperability in place. Today many queries regarding the technical complexity, TCO, development costs or roll-out plans are not fully understood causing enterprises to wait or focus on getting the info to the survey. The good news is that the required – cloud – platforms and analytics capabilities today are mature and ready to start on IoT.
Enterprises require proof: proof of the return on their investments and deployments. Due to the above reasons, enterprises today primarily decide to start IoT initiatives incrementally and focus on customer-centric or industry-specific IoT initiatives first.
Back to the quote above about the CFO feeling his bank transferred into a technology company. Of course his thoughts are built upon the Digital Transformation that his bank is going through. Digital Transformation is now a core strategy for almost all enterprises, and it better be. It starts with the mandate of the enterprises executive committees often driven by a fear of digitally enabled competitors. The starting point for Digital Transformation that enterprises typically choose is the innovating the customer experience. The focus first on offering their customers a new digital experience on their products and services. And IoT is an important way to do so. According to IDC’s Global IoT Decision Maker Survey, some 58% of global enterprises believe IoT as strategic to their business.
Phases of IoT
IoT initiatives as part of Digital Transformation will enter the market in phases. The first phase currently going on is the phase of innovating customer and consumer experience. Instead of being IoT projects, the initiatives are strongly related to use cases. Use cases that are Industry specific and deliver specific value. Analytics plays a dominant role here: not only to monitor and interpret the IoT-devices information, but also to apply the closed loop principle and start predicting and planning IoT insights. In the next chapter, I will highlight for industries with specific use cases that detail on phase I.
In a second phase enterprises will further leverage their IoT investments from phase I by adding more business value. Adding business value is done by adding, brokering and blending enterprise and environmental data to what’s already available via the IoT application. Here business analytics is core! Analytics though offers the capabilities to extend the IoT value from customer experience into product and customer optimization. With analytics enterprises explore the insights by combining IoT information to other business process data, or create business value by blending towards data from outside the organization like social media, weather or market information. In this phase, the IoT device insights are further enriched with corporate or non-corporate data to leverage of numerous domains like:
Product design and development
Supply chain optimization
Basket analyses in retai
The third phase of IoT applications will be to complete full interoperability with other IoT applications. This is the phase that has an enormous economic impact. Interoperability allows for complete new business models of which offering “products as a service” is a key one. Remind the compressor manufacturer that stops selling compressors but starts selling compressed air, of the hospital that starts reimbursing its patients based on health-added-value.
2016: Innovating the customer and consumer experience
2016-2018: Extend IoT business value
2021: Interoperable IoT
IoT in Phases: 4 Industries highlighted
A little deep dive on the first two phases of IoT – customer experience and extending business value – makes me define three groupings of use cases to which they apply:
To monitor the status, condition, movement or physical asset of the device in order to increase performance, efficiency, health or security of these assets. The focus is on the asset. Analytics is the way to get insights on this focus
Here the emphasis is on providing a contextualized and personalized customer experience based on information collected about this customer (B2C or B2B) or employee. The focus is on the experience solely.
Product and service experience
The focus is on enhancing a product or deliver a product related service on the IoT enabled asset. Typically a phase II use case since the enhancements are being created by combining IoT insights with other data. Supply chain optimization is an example
Recent studies showed 4 industries show specific intentions for IoT initiatives in both phase I and II. These industries are:
Consumer products (Food, beverage, beauty and health)
Discrete Manufacturing (automotive, defense, aerospace, farm, construction etc)
Consumer products is an industry that embraced IoT already at an early stage. The most applicable use cases here are engaging customers by understanding their shopping and consumption patterns. Examples are store shelf status, consumer pantry, but also actual home based product usage for customer replenishment.
In discrete manufacturing the focus is regarding visibility or tracking and eventually progressing to more sophisticated processes that require automated or predictive workflows and responses and provide a level of resource or outcome optimization. IoT-enabled change through connected products is here or very close for most discrete manufacturers — to collect and analyze actual product performance data, influence future product development, improve service delivery, and increase customer satisfaction. Similarly, the integration of IT assets and information with operational technology in the plant and the supply chain is also on the road map or already started. The most successful investments will create significant business advantage and digital transformation.
Healthcare focus is telehealth, focusing on initiatives like remote health monitoring, fitness and activity tracking, medication adherence or personal emergency follow up. Healthcare organizations across the globe are in the midst of a significant transformation as a result of health reforms, which has led to reimbursement focused on value, not volume. Under this new paradigm, healthcare organizations must become more efficient in how they deliver care. They must also strive to engage consumers to play a more active role in managing their own healthcare because consumer behavior (e.g., diet, exercise, compliance with therapeutic regimens, smoking, and alcohol and substance abuse) influences overall health status. It is already clear that once IoT is embraced to its fully potential in health care, that same IoT will be the disruptive force. The ability to monitor consumers remotely or conduct a virtual visit via video is transforming how care is delivered. Providers have discovered that it can be more cost effective to send a patient home with a tablet and remote health monitoring device to detect complications before they become so serious that the patient must be readmitted, thus avoiding 30-day readmission penalties for certain conditions.
For retail the most common use cases are about connecting consumers to products and product related information. It is all about the experience strongly driven by analytics. The consumer of the future requires that retailers provide engaging, personalized and digital experiences. Something that can only (!) be done based upon a strong analytics-driven foundation using insights and predictive models.
Below some thought (source IDC 2016) on specific uses cases for phase I and II for the 4 groups.
Assets include finished goods and components; electrical and mechanical systems; IT and operational assets, including fleets; rental goods and equipment; medical equipment and supplies (e.g., wheelchairs, gurneys, crash charts); and larger systems of assets, such as a network of plants, facilities, stores, or warehouses.
For healthcare: Combining connected vehicle technology with a real-time location system (RTLS) to enable equipment and supplies to "come when called" or sense when needed based on data collected from other devices or systems
For discrete and consumer products manufacturing: Preventive and predictive maintenance in the plant and supply chain; the ability to dynamically reroute or optimize real-time supply and demand trade-offs; ensuring process safety and security objectives are intact
For consumer products and retail: Sensor technology to track and geo-position promotional end aisle displays to ensure that the displays are in the correct place and fully stocked
Influencing the experience of the customer/consumer/employee in the context of multiple environments, including healthcare centers, retail stores, and any operational facilities, as well as in customer-specific locations
For healthcare: Monitoring medication adherence with escalating reminders and alerts for refills; ingestible sensors to track consumption, combined with mobile health apps and remote health monitoring devices to evaluate drug and care efficacy; using sensor-enabled clinician badges to track handwashing, hours logged on a shift, movement through the facility, and training attendance; remote health monitoring, wearable activity, and wellness trackers
For discrete and consumer products manufacturing: Controlled access to location, equipment, or equipment capabilities based on operator role; direct monitoring/input of user preferences for the product innovation process based on actual usage and buy/no-buy selections
For consumer products and retail: Consumer insights, interactions, and marketing in-store based on consumer location and product in proximity; dynamic replenishment model based on actual product usage or store shelf status
For retail: Determining optimal product positioning, digital fitting rooms, and augmented reality fitting
For retail and healthcare: Personal lifestyle planners and purchasing assistants (based on contextualized dietary, exercise, and health requirements)
Product & Service Experience
Most applicable to discrete and consumer products manufacturing
Adaptable product-enabled services (personalized, prepared, and finished products)
Adaptable product-enabled services (personalized, prepared, and finished products)
Remote condition or location monitoring and preventive maintenance
Automated replenishment of consumables
Warranty and service contract compliance and delivery
Source of actual product performance in customer environment
Input for future product innovation and development of services and new customer experiences
Tracking and traceability information from all suppliers and contract manufacturing and owned factory locations to maintain product quality and product-related compliance objectives
ANALYTICS AND IOT
In all phases of IoT evolvements it is crystal clear that business analytics is the compelling factor when IoT needs to be successful. Only driven upon a rock solid data foundation with personalized and tailored insights, the user experience and business value extensions can reach the levels enterprises are aiming for. I already liked analytics a lot, but this conclusion makes me even more passionate.