How To Move From Data Collection To Running Business Intelligence
Most organisations recognise data as a strategic asset and are looking for ways to maximise its value, however this also creates new strategic challenges for organisations. Using business data effectively requires progressing past collecting data to running business intelligence. Then, companies can actively depend on that information for better outcomes, rather than just compiling it for potential later use. Here we explore five ways to successfully run your BI efforts:
1. Use & Communicate Key Measures Effectively
Each business has key measures or key performance indicators (KPIs) that are important to know. A key performance indicator clearly articulates and provides insight into what your organisation needs to measure and achieve to reach your long-term goals. Collecting data may illuminate where weak points exist, making it easier to see the path to improvement. Regularly tracking your KPIs through the whole company is essential to running a worthwhile business intelligence model. Having universal agreement and documentation on how KPI’s are measured and calculated also avoids the common issue of one department calculating a measure one way and another department calculating it an entirely different way.
2. What’s Inhibiting Employees From Using Data Better
It’s not uncommon to find that adoption of data analytics models may be lower than expected or employees aren’t using the data you provide to its fullest extent. In the current business landscape, alerts, data refreshes and forecasts will need to occur more often, with the freshest variables. Empowering users to access data, insights and business logic earlier and more intuitively will enable the move from visualisation self-service to data self-sufficiency. In fact, Gartner showed that 48% of employees will likely work remotely at least part of the time now after COVID-19 compared to 30% before the pandemic. In addition, shared data, visualisations and story-telling are consumed more widely now. Therefore, providing up-to-date and business ready data are more important than ever before.
As the velocity of data increases, the speed of business needs to follow. Can we make “business-ready” data – data that is not only curated for analytics consumption but which has timely business logic and context applied to it – accessible earlier? And can we automatically trigger the end points, whether that’s an automated process or an action taken by a human? The infrastructure and applications are available, enabling a gradual transition to active intelligence. That will be a big factor in helping enterprises pre-act.
The ability of business leaders to quickly use data from operational applications to make strategic decisions and deliver on strategic outcomes will rapidly be seen not just as a potential competitive differentiator, but also as a fundamental requirement and strategic imperative.
3. Make Data Easy To Find & Understand
It’s a given that the data needs to be accurate and timely. So first and foremost, users have to have absolute confidence in the data set, so this should be the first task in getting the data accurate. Then the task is about defining and understanding key KPIs that need to be communicated to stakeholders and presenting the data in a way that makes sense. That means making data, reports and dashboards understandable and accessible to non-technical users.
Basically speaking different people in a company have different reporting and analytics needs. Whether you’re building a business intelligence dashboard for the executive team or an operational team, do your dashboards tell the story you want to get across or does the insight get lost in a sea of KPIs? When we’re designing and building dashboards in Power BI, we always consider the story we’re trying to tell in assembling the data. Choose and display the right metrics, develop dashboards in a responsive design that’s easy to manage and automate data integration and consolidation. If you then get this all right, a data literacy program should be put in place to educate users on how to best use the available data and dashboards.
4. Take A Top-Down Approach To Business Intelligence
Great BI helps organisations ask and answer questions of their data, with a view to making better decisions by showing present and historical data within their business context. According to an article by The Executive Connection, “Executive management, operations and sales are the primary driving forces behind the adoption of business intelligence strategies... Though it has been proven that the right analytic data can disrupt entire industries, many C-suite executives aren't clear on how the data is able to do so." At the heart of the challenges facing CEOs can be a general lack of understanding of BI and data analytics. Rather than taking steps to understand these concepts and develop a systematic approach to a company's data, CEOs are often so busy putting out fires that they are relegated to reinventing the wheel each quarter and relying upon IT to produce complex reports upon demand. Engaging support of the CEO upfront in any strategic BI initiative is crucial to its success.
5. Ensure Business & User Needs Drive The Technology
Use the business need as the driver of the technology, not the other way around. You don’t want to be deploying a tool without a problem to solve. You want to understand the immediate needs of your customers, or users, and ensure those concerns become the focus. In the BI space, everyone for the most part, is intelligence poor – drowning in a sea of data, but with very little timely, actionable, accurate intelligence. So, the ability to now equip employees with useful and useable reports, that can immediately help them perform their jobs better, is again like gold for many.
If you’re looking for ways to maximise the value of your business data then reach out, BoomData are Microsoft data and analytics specialists that design, build and maintain agile data, analytics and business intelligence solutions for medium to large organisations and Government departments.