In a world that creates more information by the second, it would seem that businesses have everything they need to cut costs, drive more revenue and better satisfy their customers.
But the reality is that most companies have their work cut out for them when it comes to benefiting from the data they collect.
How can organizations modernize their business intelligence? Follow these five tips to take your BI to the next level.
Data Initiatives Should Always Map to Business Objectives
According to Gartner, 87 percent of organizations have low BI and analytics maturity. These businesses are categorized as having “basic” or “opportunistic” score levels on Gartner’s scoring criteria. Basic is described as spreadsheet-based analyses and singular requests for data extracts. Opportunistic entails individual business units pursuing analytics initiatives via one-off projects without the oversight of any leadership or central governance.
For companies to progress their analytics efforts beyond these inefficiencies, data initiatives should always map to business objectives. Organizations shouldn’t change business objective to align with data programs. This makes it easier to implement processes across departments and eliminate communication silos.
Adapting an Agile Analytics Methodology
Another reason companies have low maturity rates in their BI and analytics efforts is because they haven’t enacted a central system for governing the data they collect and distribute. Data is immensely valuable, but it can also be quite useless if it’s not of quality.
Without a governance strategy in place, businesses risk introducing flawed or inconclusive data to the enterprise. This could have grave effects. Making decisions based on unreliable data is far worse than relying on past experience, anecdotal evidence and personal bias, which are all problematic in their own rights. The chief data officer and the analytics team need to work together to enact a foundation that factors in business objectives, risks, access permissions and quality assurance for any data that makes its way into the workplace.
In the end, governance is important. But you shouldn’t focus on governance to expense of providing value.
Democratize Data Access
Once employees across roles can interact with and communicate about data, they need to be given the tools to aid their workflows. Traditional BI processes involved employees submitting a report request every time they needed information to make a decision or better understand an issue. But this only drained the data team’s bandwidth and halted overall company productivity.
These days, self-search tools allow employees to ask questions via text or voice and receive instant answers. What’s more, embedded features allow answers to be shared among teams and departments with ease. Meanwhile, the data team can enjoy a more satisfying workload, focusing on higher-level projects that benefit the business over the long-term.
Leverage Artificial Intelligence for Deeper Insights
Virtually every industry is applying AI to improve something, and analytics projects are no different. The growing amount of data makes it impossible for humans to interpret everything that a data set offers. That’s why companies like ThoughtSpot are fusing AI with business intelligence technologies.
Their AI feature, SpotIQ, uses dozens of machine learning algorithms to uncover causal and non-causal relationships, identify key trends, create new data segments and highlight anomalies — things that most humans, especially non-technical end users, would miss. AI is also proving valuable when it comes to predicting business outcomes. This is especially useful for sales and marketing to score leads, personalize messaging to a segment or create new subsets of audiences based on nuanced traits.
Build a Culture of Data Literacy
Various entities make a business go ‘round. Naturally, teams and departments won’t be on the same page from the get-go. But that doesn’t mean companies should settle for disparate communication. If businesses are to get value from their wealth of data, they need to build a culture that allows for fluid communication and collaboration. This is known as data fluency, and it’s the most essential—yet challenging—step to becoming a data-driven business. The right tech can be implemented, but it won’t mean much if employees aren’t able to interact with data or collaborate around it in a shared language.
Modernizing your company’s business intelligence won’t be an overnight process, and that’s all the reason to start changing things now. Focus on these five tips and you’ll be enjoying actionable, operational-changing insights that’ll benefit your organization for years to come.
