How to extract business value from IoT data
Interview with mnubo’s Aditya Pendyala, Co-founder and Head of Growth, and Jean-Francois Martin, Head of [...]
Interview with mnubo’s Aditya Pendyala, Co-founder and Head of Growth, and Jean-Francois Martin, Head of Products. mnubo, a partner of Electric Imp, provides IoT Data Analytics services.
Question: What are the main obstacles that have stopped companies from entering the IoT?
In engaging with companies around the world, across a diverse range of verticals, we have seen three major obstacles:
- Lack of connectivity – It is a significant hurdle to connect objects to the Internet and many companies do not have the resources or expertise to add connectivity.
- Focus on technology – When companies talk about the IoT they focus primarily on the technology but it is as important for them to translate technology into meeting their business objectives and understanding the ROI.
- Underestimating investment – Companies that are thinking about entering the IoT, especially the larger players, over estimate their speed of innovation and are often over confident that they can do everything on their own.
Question: What are the top compelling use cases of IoT-driven data?
At a high level, IoT-driven data insights enable operational efficiency and product development.
- Product feedback and service monitoring – Today, the data for product life-cycle is primarily historical e.g., when was it manufactured, where was it assembled and purchased, etc. however, now with connectivity – lifecycle management extends to live states of the ‘product in use’ e.g., how frequently is it used, when was it last used, when is it due for servicing based on usage behavior, etc. IoT-driven data provides service feedback efficiently, which improves product development decisions to advance product quality, behavior and performance.
- Consumer brand engagement – By having access to data, companies can assess product usage and user interactions which they can then apply to build and enable use cases such as service-enabled marketing to target new markets and segments. We are also interested in the emergence of new business models such as outcome-based pricing, facilitated by connected product data streams.
- After-market service optimization and end-to-end lifecycle monitoring – There are many after-market service options that, with data, can improve customer satisfaction, extend product life cycles and optimize balance sheets. For example, aftermarket warranty services can be data driven, based on usage, which may increase adoption of service plans. Products can analyze wear and tear and then communicate directly with CRM/ERP systems, including filing their own tickets, instead of relying on the consumer – a transformation shift from reactive servicing to proactive maintenance. Additionally, IoT data can improve overall inventory management and improve supply chain efficiency.
Question: What is something that you have learned from IoT data that was unexpected?
The major ways in which IoT data have enhanced our customers’ products, experiences and businesses are:
- Improving product design and helping R&D understand what to focus on in the next versions of the product. Connected product usage data helps our customers understand what are the popular and less popular features of their products. Additionally, trends and patterns can help product management understand usage variations over time, by location, by product type and other factors. This data not only helps with product enhancement but also contributes to messaging and positioning refinement. For example, a company may promote one feature but then the usage data may demonstrate that other features are used more often, which may make the company rethink which features to promote in their messaging.
- Understanding which clients are likely to churn. By analyzing IoT data trends, our customers can explore their client engagement cycles and identify triggers of when clients are likely to churn. With the data, our customers can create proactive outbound campaigns to re-engage with the client before it is too late.
- Providing predictive replenishment and predictive maintenance. By analyzing product performance insights and sensor-based anomalies, product manufacturers and service professionals are able to take proactive measures to service and maintain commercial and industrial equipment. For example, scheduling replacement of HVAC filters, identifying lock-out conditions in boilers before they happen etc.
- Boosting opportunities to upsell services and creating new services. Some of our customers are traditional manufacturers where they just sell hardware and with connectivity they are realizing that they can start selling services on top of their hardware.
Question: What is the best IoT product that you have seen and why do you think it tops the list?
We are especially excited about two products:
- The world’s first smart beer fridge – Not only is this a sexy product physically but it provides companies with invaluable brand engagement insights and the ability to understand actual consumer behavior on how, when and where their connected products are being used. Understanding consumer behavior provides companies opportunities to monetize their data assets and upsell services and products.
- Connected precision irrigation controllers – We are excited for the agtech evolution, transforming from a commodity into a continuous service which enables resource optimization and higher revenue potential – a service-based model links precision irrigation insights directly to farmers’ outcomes.
mnubo provides IoT Data Analytics services that help IoT manufacturers ingest, organize, store, and analyze IoT sensor and events data. It delivers rich insights, predictive analytics and IoT data science to extract business value from IoT data.
To learn more about Electric Imp, visit the official website.
Aditya Pendyala, Co-founder and Head of Growth
Jean-Francois Martin, Head of Products