Major Optimization Opportunities Hiding in Your Business Data

By now we all know that big data and powerful analytics are changing the way businesses work. Executives don’t have to rely purely on experience, “best practices” or instinct anymore. Instead, the business intelligence gained through querying datasets and creating actionable metrics is driving stronger decision-making, and that makes for significant operational improvements.

The question is, though, are you going far enough? Is business data informing the way you operate in as many areas of your company as possible?

As the tools, techniques, and processes for business intelligence mature, its use in decision-making is diversifying. BI was once confined to measuring marketing ROI or making continual improvements to manufacturing processes. That’s no longer the case. The value of business intelligence has been proven, and the power is in the hands of the decision makers. It’s time to push your business data further.

Let’s explore some of the key drivers behind these new manifestations of business intelligence and look into some case studies that shed light on how it’s being applied in the real world.

It’s never been easier to gather and consolidate business data from across the business enterprise. Querying and reporting tools are developing at a similar pace and can quickly analyze data and pull out meaningful factors from large datasets. This is important since we’re getting hit by an avalanche of data on a daily basis – mobile apps and web applications are generating loads of information and are becoming the primary source that’s feeding the analytics. There are two reasons for this. One is simply the fact that the world is going mobile, and getting increasingly connected. The second reason is that the programming languages and protocols enabling all this are becoming not only more powerful but also streamlined and easier to get into. A couple of decades ago, programming was something that only a few people tackled with; nowadays, popular programming languages are drawing in thousands of new people every day.

Access to this technology is transforming the way big business works. It creates surprising insights that lead to significant improvements and much better customer satisfaction. One area that has significant issues with customer satisfaction is public transport.

Siemens is aiming to change that. As one of the largest train manufacturers in the world, they use big data sets to enhance transport infrastructure – even small improvements to efficiency can create big improvements in maintenance needs and reliability. Siemens combines train component sensor logs with predictive modeling and data analysis to create a proactive maintenance timetable.

This had almost immediate results. Working with a train operator in Spain, the company was able to reduce the failure rate of trains to just 0.4% over 2,300 journeys. This translates into a big competitive advantage, as Gerhard Kress, Director of Mobility Data Services at Siemens says, “We are heading towards next-generation maintenance. It is a whole new business model. Instead of selling our customers a train, we sell them its performance over a certain period of time.”

Thanks to today’s self-service tools, with drag-and-drop support for any number and type of data sources, it’s becoming easier to connect disparate datasets together. Linking customer insights with support and marketing databases, or the sales process with onboarding, for example, can reveal powerful insights.

Fiverr, one of the largest online “gig economy” service marketplaces in the world, needed a way to connect all of its data together.