When operating in increasingly competitive and complex trading conditions, many organisations are turning to data to deliver the insights needed to drive competitive advantage. But, with multiple sources and disparate data points, often many businesses struggle to make sense of all the data available to them, and lack the systems and strategies to benefit from what the data is telling them, to the extent that they become data rich, but insight poor.
So, with all this data now available, how can businesses take this deluge of information, derived from multiple sources and disparate data points, and channel it into a user-friendly format for diverse audiences within the business? And critically, how do organisations harness the potential of Big Data to drive insight?
User empathy - presenting the right information, to the right people, in the right format so they get real value from the insights - was just one of the ways organisations can leverage data to deliver the insights needed to drive performance.
Making data deliver
The first rule in user-empathy strategies is to consider your audience.
No matter what sector a business operates in, operational colleagues need pre-filtered data, presented in an easy-to-understand format. An organisation can have the best Big Data analytics program around, but if the end user is blinded by science or overloaded with information, and unable to quickly and easily understand what the data is telling them, then the investment in data analysis has been wasted.
You should also consider the role of the data itself – embarking on a successful analytics programme of any size requires clarity at the outset. Clearly set out what information you’re trying to learn from the data, and, more importantly, the outcome you’ll be able to achieve once you have it. By starting strategically and asking why the data is needed and what it should achieve, before moving to the practical ‘how’, means the outcomes will be clear and compelling, allowing for greater buy-in from internal stakeholders.
Don’t proceed without data visualisation
Another key consideration when tackling Big Data is data visualisation, which can help solve the end user empathy conundrum.
By investing in a process of converting large amounts of analysed data into an easy-to-understand visual format, professionals across any function of the organisation – from marketing to finance and beyond - can begin to put insight into action to drive business performance and work towards delivering competitive advantage.
Data visualisation strategies can deliver faster, more effective communication as people are, for the most part visual learners. Salesforce research suggests that 65 percent of us are visual learners, with our brains developed to receive infographic style data faster – explaining why many organisations are using vsiualisation strategies to bring data insights to life in a business context. Indeed, research shows that big data visualisation tools are becoming business-critical to organisations looking to deliver value from their analytics programs. 73% of high performers strongly agreed analytics tools are valuable in gaining strategic insights from big data, according to another recent Salesforce study, which might explain why the visualisation market is tipped to grow exponentially, worth $6.4 billion by 2019.
Do it with a dashboard
Real-time dashboards are invaluable in bringing together the functionality that enables users to interact directly with data. For example, the dashboard might process multiple incoming data sources simultaneously, or apply filters to frame the data in ways that relate to specific tasks or job functions – whether that be reviewing up to the minute sales trends, forecasting the ROI of a new service, or benchmarking costs by region.
The best dashboards are developed with the following considerations in mind:
- Remove the noise – Focus on metrics that truly measure business performance. Keep it simple by only including the most valuable and actionable metrics for that particular individual or job function
- Choose metrics that matter - Hone in on metrics that solve a problem, answer a business question, or pinpoint opportunities and that are matched with clear next steps and calls to action to enhance performance
- Know your audience - Tailor metrics for the end user’s functional needs; someone in one area of the business will need a very different set of data and insights to those operating in another team, so bear this in mind when setting up filters on your dashboards
- Make it shareable – Partnerships are a powerful ally when it comes to driving value from data, as many organisations are now discovering to their advantage. By being more open with data insights with slected commercial partners, it opens the door to driving competitive advantages for both businesses and can elevate your data insights above what you might have been able to achieve on your own
Don’t confuse data visualisation with data science
Data visualisation serves up rich and relevant insights to end users, supporting the operational, business improvement and customer service aspects of an organisation. Critically, however, this should not be confused with data science, which sits atop of operations to investigate and analyse data and its sources, to see where it can be used to provide strategic insights.
Data scientists research what and how data can be gathered to support this; and finally they build the models that will provide those day-to-day operational dashboards that can impart key actions that deliver value to the end-user and, ultimately, drive business performance.
Best practice dictates that investment in data science should be for fine-tuning and future-proofing a business. Its task should be to decide the most productive ways for data to be used, and how best to package that data to optimise use by colleagues in operations. The data scientist’s role is all about exploring possibilities and discovering new ways data can help a company reach its goals.
Taking care of data’s front-end usability, and respecting the findings of data scientists are two fail-safe ways to ensure Big Data isn’t wasted, and instead becomes the lifeblood of an organisation, driving its long-term health and delivering competitive advantage – even in competitive and complex trading environments.
John Cooke, MD at Black Pepper Software
Image Credit: Wright Studio / Shutterstock