The emergence of business intelligence (BI) tools should come as no surprise. The value of leveraging data within organizations big and small can no longer be ignored. Businesses are using data to identify bottlenecks, streamline workflows, more efficiently allocate marketing spend and improve the overall customer experience.
Data is making business decisions smarter, and the applications are only going to continue to grow as the collection of data explodes. According to WhatsTheBigData.com, humans now produce five exabytes of data every two days, approximately the same amount since the dawn of civilization up until 2003.
As the amount of data at our disposal continues to grow exponentially, the principles for making it a foundational component at Laughlin Constable have remained constant. Here are six ways to more effectively use data within your organization.
1. Connect Your Datasets for Powerful Insights
The amount of data that organizations have available to them is virtually limitless, including Customer Relationship Management (CRM) data, Point of Sale (POS) data, sales data, web analytics data, email, social and traditional and digital media data. This information comes from different data sources and is often viewed and analyzed separately. As a result, organizations are left with an isolated view of their business performance.
Industry leading BI tools such as Microsoft Power BI, Tableau and Domo have made the aggregation of data easier than ever before. With the ability to connect to popular data sources, including SQL Servers, Hadoop, Facebook, Google Analytics and Salesforce, BI platforms can give a cohesive story of an organization’s performance. Juxtaposing these separate data sources can be extremely powerful for your organization. Building an all-inclusive, cohesive data source can enable you to make deeper and more powerful insights.
For example, an organization that heavily relies upon weather to determine the profitability of their business may want to see how changes in weather patterns affect things like revenue and website engagement. Attaching weather data to your data-set could also help make marketing spend more efficient.
2. Establish a Business Purpose for Your Dashboards
Far too often, reports and dashboards become so cluttered with information that their original purpose becomes terribly unclear. Now that there is so much data available, it is important to identify the specific business questions that each data report will help answer.
At Laughlin Constable, we use the following format below as a framework for creating our dashboards:
Question: What is the essential business question this dashboard is aiming to answer?
- Action: Identify that action you will take once the business question is answered.
- Metrics: Choose the data points that will answer the essential business question.
- Visualize: Identify the best way to display these data points.
- Segment: Pick the dimensions to segment the data points for further insight.
3. Choose the Right Visuals
The essential component of telling a story with data is knowing how to visually present that information. Choosing the right visual often comes down to two factors. First, in order to have the information resonate with your audience, you have to understand their familiarity with data. With most audiences, you will often find that “simple” visualizations are better. Second, you need to know the point you are trying to convey. Each visual has a distinct purpose in analysis. We’ve included a few of our favorites below.
4. Look Forward, Not Backward
Organizations often have the habit of only looking backward: analyzing trends and correlations from past performance instead of using data to forecast the future. This is easier said than done. But with the new predictive analytics and machine learning capabilities that BI platforms are now featuring, predicting future performance is more possible than ever.
Looking forward allows organizations to be proactive instead of reactive. When we know what future performance is expected to look like, it becomes easier to track if we are on pace to reach performance goals or if we need to adjust strategy or marketing budgets to get there.
5. Automate Everything
Gone are the days of manual data pulls and intricate spreadsheets. Automating the data pulling process eliminates the time wasted on tedious data aggregation. This allows organizations to drastically reduce the time it takes to produce reports and dashboards, making it available whenever they need it. When data aggregation is automated, it allows organizations to react to that information real-time rather than having to wait weeks or months.
One of the largest value propositions of leveraging a BI tool is the ability to automate what used to be manual processes. Companies that used to spend hours manually pulling data can now focus on providing further value with better, more real-time analysis. Updating the data that matters most should now take seconds, not hours.
6. Empower Stakeholders in Your Business to Answer Their Own Questions
Have you ever been pestered to pull numbers for the latest marketing campaign only to receive the same request a week later? Enter self-service BI. These tools, such as Microsoft Power BI, Tableau and Domo, help put individuals in charge of meaningful data in a way that can be understood by all: visuals. Interactive dashboards empower users within your organization to get the data they want, when they want it so they can quickly and easily answer their own questions when they arise.
Imagine a dashboard that gives marketing managers the ability to view campaign performance over a particular quarter, dive into marketing spend allocation and understand if we are on track to meet our conversion goals, all in real-time. Self-service dashboards like this are putting the power of data in the hands of the actual decision makers.
Business intelligence is transforming the way companies use data to make decisions. It is quickly becoming the differentiator between those that thrive among their competition and those that fizzle. In 2017, it is crucial to prioritize using data effectively to drive change in your organizations.
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