Internet of Things (IoT) is the most talked about and pervasive technology that is about to impact a wide variety of industries and future businesses. The purpose of this blog is to share tips on planning an IoT Analytics (IoTA) setup.
Part – 1 introduced the four pillars of an IoTA setup. Here we list the essential building bricks.
Of multiple available options in how to build an IoTA setup, following is some essential elements in most of them.
Step-1: Streamlining the Data Supply Chain for smooth data acquisition, sanitization, extraction and integration
- a) Build Big-Data architectures (will need quality check-point defined data lakes, not data warehouses)
- b) Setup platforms that can process semi-structured or unstructured data e.g. MPP Databases, Hadoop
- c) Socket up the data to NoSQL databases – document databases, graph, key-value and wide-column stores
- d) Invest in platform which can blend multi-source, multi-format data e.g. MicroStrategy, Domo, Chartio
- e) Acquire BI tools which can learn and run rule engines in analyzing that data e.g. MS Power BI, Tableau
Step-2: Creating an intelligent learning analytic ecosystem for a seamless handoff from manual to intelligent automated systems which will need increasingly lesser interventions. Need to harvest expertise in the following:
- a) Machine Learning and Deep Learning – from created rule engines to self-adapting ones
- b) Customer Journey Mapping – knowing his entry, exit and the path – so we know where & how will he go
- c) Knowing the Customer, even before he thinks – emotional and cognitive computing
- d) Intelligent Data Curation – enhancing data value and increase its shelf-life
- e) Being Connected (companies will increasingly need to co-invent the customer e.g. restaurants sharing CRM data with apparel companies so both can benefit symbiotically)
Step-3: A different class of output should be the end result where data visualization will become more user friendly, dynamic, relevant, location sensitive and predictive
- a) Real-time Dynamic outputs – information that will be for here and now
- b) Multi-platform Interactive formats (e.g. the profit chart customized to show up on your smart watch)
- c) Design Thinking based solutions – objective driven outputs
- d) Anticipatory Action triggers (e.g. Amazon wants to deliver products at your doorsteps as soon you think about it, or even before that!) – linking output to its consumer
- e) More and more personalization – listening to your needs, and even to the extent of defining them at times
Few components of the IoT ecosystem
IoTA Use cases leveraging sensor data
With the steady invent of new concepts and techniques to engage IoT sensors around us, we will soon be living in an intelligent IoT embedded ecosystem. While newer ways of where and how to engage them will be invented, there will also be innovations in how and where to use that resultant data deluge. Here are few real possibilities:
Improved underwriting processes
Biometric and positional sensors will generate physical, performance, and behavioral data for individuals and businesses lacking a credit history and create new underwriting opportunities.
Finance the lease or purchase of many physical items
Sensors monitoring goods' condition will offer customized solution like proactive credit offers to individuals if their purchased items begin to show noticeable wear or tear.
Tailored investment decisions and asset allocation
Using information from a client's IoT "ecosystem", to identify the truly interested prospects based on behaviors, preferences, transactional and location data.
Predicting the potential for internal fraud
Better risk management by monitoring FSI employees' stress levels, patterns of movement and other factors feeding a relevant statistical fraud predictor
Understanding a new client's true Risk Tolerance
By replacing client questionnaires with algorithms using IoT-enabled inputs from client's life pattern and behavioral and credit data
The Smart Retail Store
An IoT beacon at entrance will trigger store's app on clients' smartphone with exclusive offers based on her shopping background. Connected shopping carts will guide to her aisles of choice. Smart mirrors in trial rooms will suggest product pairing. Automatic billing follows. The smart app will instantly provide spend analytics with related coupons.
The final part of this discussion will answer if the IoT and IoTA buzz a reality or fad. Few supporting business cases will guide home IoTA success stories.