Big data, when handled properly, can lead to big change. Companies in a wide variety of industries are partnering with data analytics companies to increase operational efficiency and make evidence-based business decisions. From Kraft Foods using business intelligence (BI) to cut customer satisfaction analysis time in half, to a global pharmaceutical company using predictive analytics to increase employee retention and meet market demands, data analysis is creating new opportunities for businesses to gain competitive advantages.
By the end of 2013, around 64 percent of organizations had already invested in or were planning on investing in big data technology, a six percent increase from 2012. While data analysis can be a powerful tool when properly handled, some companies just aren’t ready to add business intelligence to their competitive arsenal. Data analytics insight isn’t as straightforward as purchasing and downloading software. There are a lot of considerations that must be made before a company invests in BI.
How do you know if your company is ready for a BI system? By assessing where you currently stand, where you want to be, and what you need to get there, you can more confidently determine if your company should invest in data analytics tools. These questions can guide your assessment.
Before you invest in business intelligence software, you should know what you’ll be using it for. Collecting data and establishing a system for analysis isn’t productive if you don’t know what problem you want to solve.
Consider areas of your company where the current process isn’t as efficient or effective as it could be. How effective are your current marketing campaigns? Do you want to gain insight into your customers spending patterns? Are you looking to improve the efficiency and quality of production? Deciding what questions you want answered prior to investing in a BI solution helps you select the appropriate partner for your company.
To perform data analysis, you have to have data; enough relevant and trustworthy data for your analytics to be dependable. If your company hasn’t already acquired sums of data or lacks access to workable information, you first need to determine if you can afford to and have the ability to aggregate such information.
This can quickly become expensive. Beyond the cost of labor for the hours spent organizing and cataloging information, data storage itself is often costly. Large enterprises can spend as much as 40 percent of their IT budgets on storage infrastructure – an average of $25 per gigabyte per month. Typically, these front end costs pay for themselves because of the increased insight data analysis provides. Regardless, the costs of data aggregation and storage should be thoroughly considered before moving forward.
The price range for business intelligence software varies greatly depending on your needs as a company. Some BI vendors offer data warehousing, which can become expensive but is a good option for companies with a larger budget that require data storage and analytics. Other BI vendors offer visualization systems, both on-premise and in SaaS form. Because visualization systems come in a variety of price ranges, your company will likely be able to find a solution that fits your budget.
But the software cost is only part of the overall expense. In fact, the rule of thumb estimate for the cost of effort and services is 5 times the software cost.
Adding these expenses together, the total cost of a single business intelligence report could end up being around $20,000. This estimate reveals how expensive performing multiple reports can become. In fact, the average cost of business intelligence software for a department is $150,000. This estimate can change depending on the size and depth of the project, but it’s important for your company to thoroughly understand the full array of costs involved with data analytics prior to investment.
Data analytics aren’t going to appear out of nowhere. While many BI systems are intuitive, they still require user interaction and management. For best results, your company should have a data analyst or data scientist who is responsible for managing data and performing analytics. Having a single point of contact for analytical decisions will help avoid departmental confusion. Additionally, this person will be able to devote continued time and resources into monitoring and creating reports.
If your company can’t afford a full time data analytics employee, then you should select an existing employee (preferably one with data experience) to manage the BI software and act as the voice for projects. Without having a designated person capable of working with the data, you won’t be able to utilize the full capabilities of your BI solution.
At this point you’ve gathered data, identified the problem you want to solve, invested in BI software, and performed insightful analysis. To make all of this investment worth it, you have to be prepared to act quickly and effectively.
Implementing a new project or campaign can be expensive upfront. With your newfound data insight, you have the knowledge necessary to effectively change operations in your organization. It’s important to be prepared with the resources necessary to implement this change.
For example, Eurac, an international brake disc manufacturer, utilized Logi Data analytics to improve their reporting and manufacturing system. The intent was to make short term improvements, but also to consistently use the system to realize the company’s long term goals. What they experienced was an immediate ROI of more than 50 percent due to the reduced number of ERP licenses needed, in addition to crucial insight for improving operations.
Data analytics through business intelligence can be a powerful tool to improve the efficiency of your company, but not every organization is ready to responsibly integrate a BI system. By asking yourself these questions, you can better determine if you’re prepared for the influence of data analytics at your organization.
By Keith Cawley
