Os inúmeros dispositivos que existem hoje no mercado produzem dados que podem, e devem, ser usados pelas empresas. Quer seja em processos internos, para realizar campanhas publicitárias mais eficientes, realizar transacções comerciais ou conhecer melhor os seus clientes.
Por outro lado este cenário reabriu o interesse por ferramentas como o business intelligence. Porque haver dados disponíveis não significa, necessariamente, ter boa informação. Há que saber filtrá-los e usá-los.
Aggregating big data from embedded devices is changing the analytics world
By Jason Tee
The Internet of Things has created an enormous upsurge in the amount of data available to businesses. The enterprise world is still trying to come to terms with this phenomenon—and they must move quickly if they have any hope of keeping up with this powerful big data source. The potential ramifications of the proliferation of embedded technology go beyond outward facing advertising to internal business processes including production and customer service. As Internet-enabled and wireless sensor technology is embedded in more and more devices, it becomes yet another source of insight that can be used to formulate and refine every aspect of business strategy.
M2M brings new value to internal BI
Machine to machine (M2M) embedded technology is coming into its own in areas such as research, manufacturing, retail, and logistics. For example, companies can use embedded technology to speed production and manage quality control at a previously unheard of level. According to Andrew Schofield, Chief Architect for IBM’s MessageSight division, “The driver here is that companies want to gain a competitive advantage and use this data to improve their business processes and efficiency.”
When machines are enabled with embedded technology, they keep businesses running more smoothly. They also make it much easier to improve performance over time. Pieces of equipment with embedded systems can monitor their own state of operation to provide real-time data about service requirements, providing instant notification if something is wrong (and even providing access for remote repair in some cases). They can communicate with other machines in the system, automatically adjusting for changing conditions. They can also record human/machine interactions to identify bottlenecks due to poor equipment or software design, or outdated procedures. Many embedded M2M solutions can be integrated with ERP, CRM, and supply chain systems to provide an even more comprehensive picture for analytics. The resulting business intelligence delivers insights from the physical world—not just the electronic one.
It’s not always about the big picture
While gathering all M2M data in one giant dashboard to see the overall picture might seem like the best approach, it isn’t always the smartest way to use the information. Schofield points to a new twist—embedded technology may begin using BI with minimal human involvement. With the Internet of Things, “devices can discover each other, interconnect, share information, and make decisions locally. Business systems take this information and apply the intelligence and perform analytics across the data. But they don’t necessarily need to connect all the data centrally.” This approach might be called micro BI, since it can be used to create incremental improvement at the level of each embedded node or cluster.
The consumer side of embedded BI
While embedded technology is becoming increasingly ubiquitous in company-owned assets, it’s the embedded tech in consumer-owned devices that has both Marketing and IT excited. Dr. John Barrett from the Cork Institute of Technology described the anticipated growth in embedded technology in his TEDxCIT talk. He revealed the startling statistic that, by 2032, the average person will be in contact with 3,000-5,000 smart thingsin their day-to-day life. The implications for business are startling. “When you know how individual people are using individual products, individually focused marketing becomes possible. And it will transform the marketing and advertising industry.”
Embedded data from the mobile world is providing access to a whole new set of metrics. James Neihaus from Ensighten said businesses are paying special attention to how consumer behavior changes as they move through their daily lives. “It’s mainly around user behavior across devices. What is the omni-channel experience? Is my user using a tablet during the day, a smartphone at night? What are their behaviors and patterns? Clients want to be able to serve the relevant experience and content based on the user and the device in the channel they prefer. You see a lot more interest in analytics trying to measure behavior across touch points.”
In fact, companies that distribute mobile technology to their customers have the opportunity to glean BI insights in two ways. First, they can rely on information (such as GPS data) that is made available by the embedded sensors in the device itself. Second, they can garner data through analytics and BI embedded in the very applications they serve up on the mobile platform. Combining these data sources provides a clear picture of how, where, and when consumers are interacting with applications and content. Embedded BI becomes enmeshed BI as the feedback loop shortens and businesses deliver an increasingly satisfactory experience to end users.
By Jason Tee
TheServerSide.com – 09 Aug 2014