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.
Easier BI data collection and querying
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.”
Providing a holistic picture
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. To truly enhance the user experience, they required a near-instant understanding of how their providers and customers were using the website. Sisense, a data analytics platform, was able to take disparate data sources to provide a “single version of the truth.” This allowed Fiverr to make numerous website and user-focused improvements to increase engagement and demand for services. In order to make a website more responsive, you should pay attention to this, as these lessons can be applied to just about anyone.
Slava Borodovsky, Fiverr’s senior BI director and data scientist, says that flexibility is key to his company’s approach.“We are constantly changing the way we need to look at our data. We change the schema, we add tables, columns, and calculations because everything is dynamic and we need as close to real time results as possible.”
Fiverr’s data team routinely works with tens of millions of rows of information, stored across several servers. Today it’s all consolidated via a series of Sisense-powered dashboards, with each one running over a dozen complex queries multiple times each hour. “Within seconds we can run a report with over 20 queries and see real-time results,” Borodovsky boasts.
Critical for business operations and support
Operational processes, product development, and customer support are all becoming more demanding. Increasing diversity and complexity means businesses need to adapt if they want to stay competitive. Innovation is now a requirement for survival, not just a “nice to have.”
BI can drive this innovation by providing deep insights and measurable ways of tracking the improvements your business makes. One of the key differentiators for successful businesses is customer service and providing value-add to clients. That was the challenge facing Pacific Gas and Electric, and they used analytics from the Internet of Things to improve how their customers use energy.
PG&E has installed smart meters across the entirety of its vast network, consisting of over 70,000 square miles and 9.4 million residential and commercial properties. Analyzing the data from these smart meters provides powerful information that PG&E can use to influence customer behaviors and save them money on their energy bills. That means better energy efficiency, a more transparent, reliable service for everyone, and better relationships with customers.
“When people understand how they use gas or electricity, then they have clear direction on how to optimize their own usage, with positive effects on their monthly bills and the environment,” says Jim Meadows, director of smart grid research at PG&E.“ And smart meters mean more visibility for us into our own operations, too, as well as lower costs in meter reading and management.”
Tapping into previously unused sources
Areas like the Internet of Things and dedicated process measurement are creating innumerable new data points. Those data points tell a story, and the democratization of analytics tools means anyone can read that story and draw conclusions.
Evolv, a specialist recruiting company that was recently acquired by HR tech platform Cornerstone OnDemand, makes use of new data sources in order to optimize hiring and employee retention processes.
CEO Max Simkoff recently told Fast Company that “Using analytics to identify the right people for given roles helps eliminate long held human biases and helps companies base decisions on fact, not gut instinct.” Evolv reports that though using data, its clients (including Xerox and AT&T) can see cost reductions in HR of $10 million.
Wrapping it up
As you can see, big data and business intelligence have been liberated from just being a way to measure a business process. It’s now become a key driver across the whole of the business. Used in the right way, it can provide powerful insights to drive change, increase efficiency, reduce costs and create more profit.
