Innovation and IT: Making Data work Harder

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Innovation and IT: Making Data work Harder

Making the most of IoT involves building new applications and services based on data. Implementing sensors, devices, and networks is the first step to getting value from IoT – by Innovation and IT.

by Martin James

The term “Internet of Things” has been around now for nearly twenty years, but the level of understanding of its potential is not fully embraced across all industries. While some companies have started on Industry 4.0 deployments and smart supply chain implementations, there are still many that are only dipping the proverbial toe in the waters of IoT. Why is this? What is holding many companies back from making better use of IoT across their operations? In most cases, it is due to difficulties around making use of the data that IoT creates.

Innovation and IT: Martin James - RVP Northern Europe - DataStax

Martin James: is Regional Vice President, Northern Europe, at DataStax.

Connected things feed back detailed data to the business. By collating all information from multiple devices, patterns in behavior or usage become apparent. In theory, at least, this data should lead to more insight and therefore better decisions over time. However, simply gathering data will only take decision makers so far. For instance, getting granular data on energy use, or location of assets, can support more accurate decisions than might have been made previously. A utility provider may be able to forecast demand more precisely, while logistics companies can reduce waste or loss. However, if this data is used solely for getting more detail on one facet of operations, then other opportunities to be innovative are missed. Getting the right approach to analytics in place can help by using the data to generate in-depth insight for operations. In practice, this means linking IoT data up with other sets of information. These may be external sets like weather or consumer behavior. However, this creates its own set of problems that cross over from the technology side into areas like business process and people skills. For example, how can the company bring the sets of data together in real time, so that they can be used effectively? What sets of data does the company have, and what can be brought in from outside? And what questions can be answered using that data combination?

Innovation and IT

Answering these questions requires more thought on how the business functions and what its goals are. Looking at device data on its own won’t be enough to show all possible applications, so exploring how to use other internal and external data sets will probably be necessary.

For example, many businesses are looking at how to improve customer service and loyalty, but the link between better customer experience and IoT data may not be immediately obvious for, say, utility companies. Getting more insight into the status of smart devices over time can help highlight possible problems with assets. In the utility sector, boilers or heating systems can be tracked and companies can proactively recommend service in advance of possible equipment failure. Providers like First Utility in the UK use data analysis to see energy reduction opportunities for customers, helping them cut their bills.

Combining these different approaches to analytics should add up to a wider improvement in customer experience. Stopping device failures and helping customers reduce their spending should increase long-term loyalty and keep customers happier over time, which should then result in higher average revenues per customer for companies.

Innovation and IT - HTAP info graphic

The right mix: A combination of different approaches to analytics can lead to improvement in customer experience.

In the logistics sector, increased accuracy can help with customer service through more in-depth tracking. Rather than simply providing generic information, information from sensors can provide real-time insight into where each delivery is. For customers, this level of insight should be a valuable extra, while the logistics company should see how its overall network is performing.

Making it all work

Getting data and using it effectively does mean thinking about new applications and how those services are delivered. Gradually, it may mean building on existing IoT data alongside other sets of information. Scaling up from initial IoT projects, therefore, requires an integrated approach to data, processes, and implementation where further applications or different use cases for the same operational data can be added over time.

Innovation and IT Outside views infor graphic

Outside views: Insights must be drawn from both internal and external data sets in order to provide true value.

Whichever approach your company has around new ideas and innovation, it’s worth looking at how to devote more time and resources to supporting internal research and development. Using data from IoT devices, companies can power new and interesting services for their customers. However, getting the approach to innovation balanced across the business requires a combination of the right people, the right data, and the right platforms to pull it all together.

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