3 Ways to Get the Most Out of Business Analytics
Businesses, especially those in the manufacturing sector, have more information than ever before, stored in more systems and locations, being produced in increasingly varied forms and being used in strikingly varied ways. Advances in information technology have fuelled this explosive growth creating both opportunity in new ways for manufacturers to reach new markets and customers and complexity in trying to collect, manage and interpret data and into information that can help guide them to success. Technology, a two-sided coin, also can provide tools to handle the complexity in the form of analytics.
For manufacturers or any other business wishing to improve their performance through business analytics, here are recommendations to get the most out of your business analytics.
Look for business analytics tools that are easy to use and flexible.
Usability and functionality—that is, business capabilities—stand out as manufacturing organizations’ most important considerations in selecting business analytics regardless of company size, individual role or functional area. These should be central focuses in evaluating tools. To be usable and functional, analytics systems must provide a range of options for how to include the information in presentations, which are increasing; participants indicated an interest most often in the standard charts, reports and tables. However, documents, visualizations such as gauges and sliders, text, Web pages and maps were also identified as important by one-third to one half of these companies. Determine which of these are important to your organization today and may be tomorrow.
Don’t let inferior data undermine use of business analytics and metrics.
Business analytics should be about determining what is happening and will happen to an organization. But the research shows almost seven in 10 manufacturing organizations spend the most time waiting for data, preparing data and reviewing it for quality and consistency. Conversely, only 28 percent spend most of their time on true analysis processes such as assembling scenarios, searching for causes and determining how changes will impact current business. If these preparation obstacles could be addressed, the amount of time people work with analytics could be reduced; currently, 60 percent are spending more than 25 percent of their time with them. Take steps to ensure your source data for analytics is both fresh and correct; if it isn’t, you risk undermining the use of metrics and KPIs as business improvement tools.
Replace spreadsheets as tools for business analytics.
Spreadsheets are well established as a tool for analysis in organizations of all kinds and sizes, but they are ineffective for repetitive analyses shared by more than a few people. Yet research shows that along with business intelligence technologies (for querying, reporting and performing analysis) and analytic warehouses and databases, spreadsheets are the tools manufacturing companies most commonly use to generate analytics. Indeed, spreadsheets are used universally in 38 percent and regularly in more than half of these organizations. While they may be familiar, research shows that organizations using spreadsheets least have more accurate, timely data—and they deliver periodic reports about 40 percent sooner. Organizations should limit the use of spreadsheets as data stores and for repetitive analyses, particularly in cases where the results are reported to and used by more than a few people. Their failings, limitations and necessary work-arounds undermine the needs identified by participants to simplify analytics and metrics and ensure technology usability in the process of producing business analytics.
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