CRAIG STEPHENS Companies can use the data they have always had to streamline operations and gain strategic competitive insights
The traditional use of analytics to analyse large-scale projects is changing to a faster and more immediate use of near-real-time analytics to inform the daily decisions in a business.
The near-real-time analysis of business information in modern analytics systems can provide a platform for established businesses to reinforce business systems with a wealth of contextualised and real-time information and control mechanisms, says analytics company SAS principal solution manager Craig Stephens.
Increasing use of analytics also provides a good platform to experiment within a production-like environment to determine whether changes will be beneficial, while enabling companies to become more dynamic and flexible, he adds.
“For example, users can experiment with changing the company’s supply source and then follow the changes throughout the model, based on the company’s true historical performance. This enables users to empirically motivate their decisions, based on the predicted impact on the business resulting from the proposed changes.”
There has been a marked shift in the past decade in analytics use – from review tool to monitoring tool. Currently, it is moving towards real-time, dynamic business-process analytics that are closely related to corporate strategies and execution.
“For example, banks are using real-time analytics to prevent fraud, while online retailers use analytics to boost sales through targeted and limited offers. This highlights the operational nature of modern analytics as a strategic assessment tool and to execute the long-term strategy, while retaining business agility,” says Stephens.
Further, modern analytics enables real-time assessment of the effectiveness of corporate strategies, which can be changed if they are ineffective, compared with the retrospective analyses of conventional analytics.
“Companies can then use the data they have always had to streamline operations, to do more and waste less, and to gain strategic competitive insights into their customers and their own business operations. Modern analytics support the execution of a long-term business strategy, while retaining the agility to respond to short-term opportunities and trim the sails when necessary to chart the path to the business goals,” emphasises Stephens.
Companies will compete through their use of analytics, with analytics broadening from its current stilted use in separate business divisions to ubiquitous use by all departments and for all functions – from accounting to call-centre support, he explains.
Further, analytics systems can also help to automate certain functions and impose corporate controls over human actions, such as prompting sales people to offer suitable additional products or services and to verify that resources are bought within the price range set out in the company’s buyers’ guide.
Although in-depth data analytics skills are in short supply, this effect is lessened as analytics tools become ‘democratised’ and used by all staff, regardless of analytics capabilities.
“Everyone in your company will use analytics tools to do his or her work. While the architecture of analytics systems and in-depth, detailed support must be done by data analytics specialists, all functions will be expected to use analytics tools in the daily, routine execution of duties.”