Analytics is a transformative tool for business. According to Hanover Research, four of every five users consider analytics integral to their business role. Three of four data pros claim they’d adopt a new analytics platform embedded into their existing workstream. As employees are relied upon to make more data-informed decisions more often, it’s imperative that they fully understand the insights that analytics provide. Equally critical is that those analytics contextualize data and bolster data literacy among everyone along the chain of command.
The desire for user-friendly data analytics in easily accessible formats is strong, and supplying them makes data analysis less overwhelming, more precise and, ultimately, profitable. To accomplish this, implement three key priorities to ensure the chosen analytics suit their purpose, are fully adopted and are continuously utilized.
Priority one: Build-in analytics
Well-established and enterprise organizations likely have more data at their disposal than they know what to do with. That’s both good news and bad for small, medium or large businesses. It’s great they have so much intelligence and terrible if it can’t all be used properly.
Users need and want deep, substantive interaction with the data at their disposal. Give it to them, with built-in analytics that’s integrated directly into their regular workflow. Create no need to swivel in and out of applications to obtain, analyze or then report on data and what it’s revealing.
Build a powerful analytics platform that offers contextualized intelligence within the ordinary workstream. That means more than analytics that provide comprehensive data. It should also be rich in content and reflect all factors influencing the information.
When designed sufficiently, such analytics allows users to distill data into actionable decision-making.
Priority two: Contextualize data
Embedding analytics is not enough. Dashboards, visualizations and other ways in which data is surfaced for users must create an engaging experience that serves a dual purpose: expose context and attract regular, repeated interaction. This greatly enriches the user experience, streamlines workflow and increases productivity.
As significantly, context-rich data presentations boost user comprehension. The more data insight and familiarity gained with the analytics tools, the better that users can conceptualize the intelligence. Without needing to master complicated procedures or earn an advanced degree in data systems, this level of analysis unleashes a robust understanding of intelligence and how to leverage it best when decision-making. It’s how a well-designed app translates directly to business success.
Priority three: Intuitive self-service
Analytics occupies so much bandwidth in today’s business discussions because organizations recognize the need to make information available to everyone in the enterprise. No longer siloed for a select few, new hires to veteran leadership need access to intelligence to make informed decisions. It cannot be limited to only the technologically savvy. Nor can vacancies be occupied only by a select few whose technological skills match or surpass their business acumen. That’s counterintuitive to business success. Business skills and specialization must be matched to needs and responsibilities. The technology must adapt, and it can with powerful embedded analytics.
Thus, embedded analytics must be intuitive to each user regardless of skill level. Customizable, self-service capabilities to match its users’ skillset puts the app in a position for quick and widespread adoption. Further, as users gain familiarity and skill, they’re positioned to leverage the full power of the tool.
The self-service component is crucial in business intelligence. Users rely on the analytics application, its dashboard and visualizations, and spend less time needing technological assistance to perform their analysis responsibilities. This allows time and resources to be dedicated to productivity rather than repetitive problem-solving and troubleshooting. Imagine that: a help desk short on demands.
Speed of business
Development teams that focus on enriching UX and leveraging analytics to drive business value are rewarded with soaring adoption rates. The more people at all tiers in an organization feel comfortable with their tools, the more often they’ll use them. Employees come to rely upon analytics, which manifests into wielding the app to deliver even more information to become more valuable. Productivity soars and businesses succeed.
Unlike traditional BI, embedded analytics are designed to create such streamlined experiences. Sooner than later, businesses will be conducting all their assessments, planning, forecasting and decision-making from their embedded analytics. The time and cost savings that come from working with a well-designed, powerful tool lead to decisions made at the speed of business.
Photo Credit: Artem Samokhvalov/Shutterstock
Seth Hutcheson is Product Manager at Logi Analytics.