Lost With Big Data? Smaller Data Can Be Just As Valuable
As mobility and the world becomes more connected, with M2M (Machine to Machine) and the IoT (Internet of Things) also coming into play, an increasing number of businesses are facing data overload. Too much information from different sources, too little insight and all the discussions around “Big Data” seem to be all set far off into the future. If Big Data makes you feel lost, then looking at small bits of data can provide a great way of finding those golden nuggets of insights within specific areas of the business to help you act in a fast and repeatable way.
Data analytics is only as good as what you’re asking it to achieve and it’s important that you know the value of the results it may bring. At Peak-Ryzex, we try to analyse relevant enterprise data that relates to, for example, devices out in the field. We look at, but not exclusively, the below factors as part of our analysis:
Which devices are idle and why? What are they interacting with? What are the device application and what data is being stored in these? Location Signal strength at certain locations Battery levels Processing power
We use cloud-based analytics tools such as Elemez™ from B2M Solutions to enhance our managed services by giving us real time operational views of mobile technology. Broadly, we break down our analytics into a few categories; traditional descriptive analytics, predictive analytics and advanced prescriptive analytics. The below examples relate to a customer in the Transport & Logistics industry, but they are applicable to multiple industry sectors.
Descriptive Analytics Example: We helped the client improve the battery use of their devices during the day by assessing battery performance and usage. This enabled maximum uptime with their devices and ultimately saved the client money.
Predictive Analytics Example: We forecasted device returns with a 75-80% accuracy rate over a 12 month period. This was taken a step further and device returns at branch level were predicted on a monthly basis. This enabled the client to maintain sufficient buffer stock and again helped reduce the downtime of their mobile estate.
Prescriptive Analytics Example: We worked alongside the client to investigate device faults within their mobile estate. Both parties tested the devices in question and the data obtained proved that it was not a manufacturing fault. It was discovered that user behaviour was responsible, and this insight was addressed and acted upon through user training to reduce device faults.
As part of our intelligent managed services we let our customers know about potential or actual issues like the above and advise them on a course of action. This is an intrinsic part of our standard service reports for customers – we advise them on how they can optimise their mobile investments and ensure 100% uptime. The real value of data analytics can be seen here – trying to spot trends before things happen.
Ultimately, data analytics can tell you how to use your devices in the most productive way, optimising your estate and driving various efficiency gains.
Want to know how to get the best out of your mobile data? Contact us via [email protected] for a free demonstration.