How BI Tools Use Company Data to Deliver Goods on Time
When Adopted Properly, Businesses Improve Their Data Agility
It’s likely you’ve heard about the digital transformation, and there is a lot of information about the latest and greatest when it comes to using data. What technologies are a fit for the transportation industry you might ask?
Business intelligence solutions are a good place to start. When you think of business intelligence (BI), arguably the most popular buzzword in business analytics, you might think of simple data collection, such as used in warehouse management.
But true business intelligence involves transforming data into useful guidance through the power of visuals. What also impacts businesses now is that BI is no longer only for large trucking corporations who can afford it; in fact, custom options tailored to all sizes of business in the industry are within budget. Essentially, BI tools offer answers to big questions that matter through visual reports, KPIs, and trend-reviewing. BI software allows companies to gather their data points involving many aspects of transportation – drivers, trucks, shipments – into one program, rather than manual input into Excel. BI software typically stores data in warehouses, allowing for easier collaboration and collective decision-making within a company.
Again, there are many exciting trends in BI that show promise in small-scale trials but haven’t had enough real-world usage to prove their worth to enterprise. Adopting too early puts companies at risk of losing their investment. On the other hand, waiting too long leaves them in their competition’s shadow. Luckily, there are a few that fall right in the middle when it comes to improving a very important core component of the transportation business: delivering on time.
Knowing which business analytics trends have reached the stage where a company can gain a competitive edge by using them, while sidestepping most of the usual risks inherent to early adoption is key. When adopted properly, businesses improve their data agility.
Basic reporting has been a feature of software for decades. Every accounting and management program has an option to download its data as a spreadsheet. Embedded analytics takes things farther, providing not only access to data but an approachable platform to interpret it. It’s likely you’ve been exposed to embedded analytics and didn’t even realize it with programs you’re currently using to manage fleets, finances and HR and more.
These tools should provide visual breakdowns of these business efforts to give you a picture of growth, initiative success and other metrics they provide. The term refers to advanced reporting software that is integrated into the software you’re using so completely that a user experiences it as a single tool. Embedded analytics is now the standard rather than a bonus feature. Users expect to be able to view and analyze their data on a dashboard without exporting it to an outside program. The technology has grown past its trial phase into a comfortable state of invisibility. Users don’t notice its presence anymore so much as its absence, which makes it a very safe bet for investment. If any software you are using in various parts of the business doesn’t include embedded analytics, it’s likely time for an upgrade.
Predictive analytics as a field has existed since the late 1600s, when Lloyd’s of London used it to estimate insurance rates on seagoing vessels. Until the rise of computers though, it wasn’t a practical means of steering business. There were too many variables for a human to consider in time to form more than broad predictions.
With the advances of cloud storage and increased processing power, the field has seen a resurgence as the most efficient way to maximize data usage and feed a data-driven decision-making process. There’s still a long way to go before the full potential of predictive analytics is realized, but its current capabilities are more than mature enough to justify its adoption.
Predictive analytics detect deviations in patterns, generate insights based on evolving activity, and reliably predict future outcomes from gathered data. In the trucking industry, predictive analytics can optimize routes for drivers, track vehicle maintenance schedules, optimize shifts, and analyze distance traveled per driver.
Real-Time Streaming Analytics
Streaming analytics give enterprises a living visualization of their operations through a central dashboard. In the traditional analytics model, information is stored in a data warehouse before analysis is applied. This causes a gap between collection and results where time-sensitive opportunities are lost. There’s no rule that says data has to be stored first. It can be analyzed mid-stream to sift out data that will only stay relevant for a short time. For example, corporate headquarters can track if a driver is en route and where they currently are, if goods and packages are delivered, and predictive analytics can help determine if weather is causing delays in shipments.
These analytics trends have demonstrated their utility and staying power, especially when applied to streamlining the logistics of shipping and delivery. Each is at a point where a company can expect a respectable return on investment. The world of data and analytics is moving quickly, and becoming much easier to digest. A proactive and ongoing investment in analytics means the most accurate and comprehensive look at how you’re delivering for customers.
Humberto Farias, CEO of Concepta, is a seasoned technology professional with over 18 years of experience guiding companies around the world through the custom software development process. He leads a team of highly skilled software engineers and developers providing tailored web and mobile applications to enterprises.
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