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For years, business intelligence (BI) has been the industry standard for helping leadership gain visibility into business operations and make data-driven decisions. Many companies saw the analysis of their data so vital to their brand that they created roles for ‘Business Intelligence Experts’ to vet the information and prepare it into easily understandable packages.
While the venture into BI wasn’t in vain, it is now at a nexus of change. At this year’s Gartner Business Intelligence and Analytics Summit, Frank Buytendijk said, in short, that ‘BI is dead.’
So what’s next? As the volume and complexity of data continues to grow, business owners must focus on how to extend that data across multiple departments and business functions, from the corner office to the remoter workers.
“Traditionally, BI has consisted of places to store your data, the plumbing to connect your data sources, ways to visualize and report on your data, the people who analyze the data and so on,” explains Nadim Hossain, BrightFunnel CEO. “ Typically each layer is offered by a different vendor, and requires heavy IT support. This 25 + year-old category is now being disrupted by cloud-based, predictive analytics companies that integrate every layer of the BI stack into a single platform.”
Analytics across an organization.
More targeted marketing was one of the biggest contributions enterprises welcomed when big data first hit. Big data allowed brands to create elaborate, yet personalized campaigns that evolved to become increasingly effective as salesmen and marketers learned how to actually use all of the data they now had access to. But now, big data has become so broad and complex it has outgrown its ability to provide tangible results without the translation of an IT department.
“If your brand is trying to accelerate revenue, it’s important for all departments to leverage data and analytics to take action,” explains Hossain. “Often, there is a misalignment that occurs due to lack of accurate , shared knowledge. Marketing needs to know which campaigns are effective so they can expand those, and scrap the ones that aren’t working. Salespeople need to be equipped with maximum intelligence on their target accounts, and fully benefit from the historical data on each account.”
Big data promises to have a profound impact on the marketing function, both to make analytics accessible to marketers and the capacity to automate business rules around centralized data sets for automated channel communications.
According to Gleanster, the average organization uses 3-5 marketing technologies: email marketing, web analytics, landing page hosting, search engine marketing, web content management, social media monitoring, etc. In most cases, these technologies do not integrate deeply enough to provide a central system of record for marketing data.
In business you must react rapidly to new information , and decisions often need to be made quickly , and with limited information. If you don’t make the right call regarding a sales or marketing activity , you don’t get a second chance at that interaction. Thus, analytics across departments is integral to accelerating revenue , by fostering alignment and making better, faster decisions with data.
As our data becomes too broad to wrangle in, so do our reports of that data. The current goal of a business intelligence dashboard is to display information in a way that helps executives make decisions without needing to make guesstimates.
However, there is simply too much data for businesspeople to know what is relevant to their department, or even organization as a whole.
Dashboards of the future will leverage smart data to be effective in human-facing communication. They’ll help marketers penetrate an entirely new market based on the analytics. Sales teams can break through to customers they’ve struggled with for years, thanks to niche data points. IT teams can address urgent problems in corners of the world before they engulf entire organizations.
According to Hossain, BI dashboards are critical because they allow everyone in an organization to summarize data and make sense of it. To run properly, dashboards must connect the entire department or organization, run from the same data source, update in real time and create a real partnership between humans and machines. This is done by triggering some actions in downstream systems and recommending other actions to humans. To benefit from this type of next generation platform, organizations must have an underlying system that automates data processing and cleaning that is intelligent and makes accurate inferences from the data.
Data is exploding. Predictive analytics companies will start specializing in singular use cases because the need to be niche specific is stronger than ever. The more specialized the BI offering, the more value it provides by solving more of the user’s specific needs.