How wearable and mobile technologies extend the benefits of embedded BI

As devices, networks, and connections improve, so will the value and practicality of embedded BI via wearable technology.

By Sheila Kennedy, contributing editor

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Business intelligence (BI) and analytics originally catered to strategic decision makers. Today, advancements in mobile and wearable technologies, enterprise software, and communications are allowing BI to become embedded in the daily operations of all levels of an organization.

“For many years, the BI/analytics process had a very distinctive place within the decision support strategy, and that created a lot of limitations,” says Jorge Garcia, senior business intelligence analyst at Technology Evaluation Centers (TEC). “It was a separate step within the decision-making process, making it very difficult to spread adoption. It was also very centralized, limiting the ability to make it accessible and easy to use. Nowadays, because of the ability to embed analytics within different stages of the business, BI is no longer just a strategic tool for business leaders and executives; now you can use BI and analytics to make operating, tactical, and strategic decisions — not just long-term decisions, but short-term decisions as well.”

For example, buyers ordering parts can see a real-time embedded analysis of how the suppliers have performed in terms of quality, on-time shipments, and cost, and they can optimize their purchase decisions on the spot, directly leading to a better result or perhaps avoiding making mistakes.

The benefits of embedded BI are further extended when the information is accessible from mobile or wearable technologies. “Previously, a supervisor or worker would need to find a computer, log in, and navigate to the desired information. Now it is available at a touch on the cell phone that they carry anyway,” remarks Alex Ivkovic, systems administrator at CDF, a manufacturer of packaging, storage and shipping products.

Not all BI is embedded

Dispatching process comparison
  • Traditional BI: Each morning, technicians pick up a printed route sheet from the service center with a to-do list based on information available that time. As priorities change throughout the day, the route sheets are marked up or revised sheets are printed.
  • Embedded BI with mobile technology: Technicians refer to their mobile devices for real-time direction on where to go next, rather than referencing static paper instructions. Calls are optimized based on current GPS location, skills and qualifications needed, urgency of the call, contract service level, and expected transit time based on current traffic conditions. They are rearranged in the background as priorities change or traffic challenges arise.
  • Embedded BI with wearable technology: Smart watches can perform the same functions as a mobile device while leaving the technician’s hands free. Wearable devices or garments that sense the current weather conditions and technician’s health status can feed data in real time to the analytics engine, allowing severe storms to be avoided, the risks of dangerous environments to be monitored, and alerts to be sent if the technician falls ill or stops moving. Special glasses can display real-time analytics on the specific part or machine being serviced.

In the age of the Internet of Things, embedded BI helps to distill all of the information coming in all the time from every direction, and you decide what you need to act on right now in order to improve your business results.

“Embedded BI enables in-context analytics,” says Rick Veague, chief technology officer at IFS North America. “Whether you’re using traditional, transactional type applications or mobile apps, the objective is the same: real-time insight into what and why things are happening in order to improve reaction time and decision making, which leads to improved business results,” he explains.

“It’s different than traditional BI, which is almost always after-the-fact,” says Veague. “I want to see that something is happening right now while I can still affect the outcome. With embedded BI, you are monitoring and presenting information to the user in a much more real-time situation and in a much more natural setting, so they can react quickly and gain advantage.”

Embedding BI provides three key advantages, according to TEC’s Garcia:

  1. It boosts user adoption.
  2. It encourages the effectiveness of BI.
  3. It closes the gap between operations and analysis so that the time to decision is shorter.

“For me, the concept of embedded BI and analytics is two-pronged,” remarks Garcia. “First, you find a way to perform analytics directly on your enterprise software solution, and then you assimilate it within your business processes. When it is embedded, you can use that intelligence for many things.”
For instance, many manufacturers are using real-time performance analytics in their plants to analyze the status of each step of the manufacturing process and also the quality of manufacturing. They are using BI not only for strategy, but for daily operations.

Wearable technology’s role in embedded BI

With an embedded BI approach, you take a device, whether a wearable, mobile phone, or laptop, and say here’s what you need to know right now. “Wearables alert what is going on while it is going on, so you can intervene in the process if necessary to prevent bad things from happening and take advantage of good things that are happening while you can,” suggests IFS’s Veague.

“The most important advantage of wearables is that they improve the data-to-decision cycle,” says TEC’s Garcia. “I think they will become increasingly important within many companies as they make operations and analysis more efficient, the business cycle even shorter, and the effectiveness of information-to-action even greater. We’re talking about Google Glass eyewear, smart watches like Samsung Gear 2, gloves that measure specific information, and even shirts that monitor temperature and physiological conditions. Wearable technologies are the ultimate user interface, aside from mobile devices. It’s something that you already use, so they have a very low learning curve. Most of the time you won’t need training, or the training won’t be as specialized.”

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