In 2019, the old axiom Good Data Equals Good Decisions has never been more relevant. It’s hard to make intelligent business decisions if you don’t have all the facts and perspective you need. The ability to more easily capture, comprehend and capitalize on the value of information is at the heart of digital transformation. One potentially lucrative resolution this January is not just collecting more and more data, but gaining insight and advantage from the business intelligence the information can provide. The next frontier of business intelligence requires the most precise data from the get-go.
Banking on Business Intelligence
The term “Business Intelligence” was first coined back in 1865 to describe how banker Sir Henry Furnese gained profit by understanding and acting upon information about the market prior to his competitors. As computer systems evolved in the 1960s through the mid-1980s, the notion of Business Intelligence re-emerged to become an umbrella term to describe modern business decision-making using digital fact-based support systems. Regardless of the technology used, the ability to collect and react accordingly based on information retrieved remains at the very heart of what we call Business Intelligence today.
Advanced capture and AI-driven tools transform raw data into meaningful information that can be used to gain business advantage.
Modern techniques use advanced capture and AI-driven tools and systems to help transform raw data into meaningful and useful information that can be used to gain business advantage. The technologies include document classification, data location, extraction and verification as well as text and image analytics, analytical processing and predictive modeling, among others. Together, these technologies are directed at handling large amounts of both structured and unstructured data to help identify new strategic business opportunities and to fine-tune existing processes.
Just as Furnese discovered in the 19th century, identifying new opportunities and implementing an effective strategy based on these insights can provide businesses with a highly competitive market advantage. Indeed, Nucleus Research examined a number of cross-industry case studies to determine exactly how much companies were getting back from their investment in technologies and techniques that boost Business Intelligence. Their study found that for every dollar spent, $13 is made back – that’s a return on investment of over 1300%!
Wide Ranging Strategies
Business Intelligence can be used to support a wide range of business objectives and strategies, but it’s only as good as the data upon which it is built. One of the biggest challenges of large enterprises is getting accurate data into their business systems from the high-volume, constant influx of incoming documents—especially for unstructured documents.
Hence, document automation is key, but encoding expertise into a software application that accurately extracts data can be time-consuming and often leads to suboptimal results since the extraction rules once created are inflexible and can’t handle dynamic production environments so the data still needs to be manually verified. Automation that still requires a lot of manual data handling has led to increased interest in using machine learning algorithms to create rules automatically. In this way, advanced capture powered by machine learning can ensure accurate data results even in the most dynamic production environments.
With verified data, business intelligence becomes reliable even for short-term operational decisions, such as product positioning and competitive pricing. Long-term strategies concerning things like brand positioning and market share are more successful as well. The approach is most effective when it combines external data culled from the market in which a company operates with internal data found within the company like financial numbers and operational information. When external and internal data are combined together the perspective creates an “intelligence” that cannot be derived by any singular view or set of data.
Aspects of Advanced Business Intelligence
The technologies and methodologies behind Business Intelligence are all aimed at providing historical, current and predictive views of business conditions. A variety of technologies and capabilities can come into play; things like reporting, data and process mining, complex event processing, business performance management, and benchmarking, among others. Here are three important aspects of Business Intelligence to consider:
Predictive Analysis – Predictive Analysis is one way that companies get value out of information by virtue of the ability to predict the future. The analysis provides concrete predictions grounded in statistics and specific outcomes. Consider the value of an enterprise selling athletic shoes knowing that a certain season accounts for the highest sales volume. Or the power of knowing that customers in the Pacific Northwest are much more likely to buy your shoes versus customers in the Northeast…and that customers in the Midwest are extremely unlikely to buy at all.
Consider the power of knowing which customers are most likely to buy your new product…and which ones are extremely unlikely to buy at all.
Real-time Monitoring – Another important is the use of near real-time monitoring to help close the gap between data acquisition and data analysis. One example of near real-time monitoring includes using transportation ticket data to match passengers with the most appropriate flight, bus, or train. Another example is using data about emergency patients to trigger the quickest essential care at a hospital or urgent care clinic. This is the type of real world business intelligence that transcends the technology involved by allowing organizations to take pro-active approach, in real time, to conditions that otherwise would have triggered a crisis, problem or unseen inefficiency.
Knowledge Management – Knowledge Management is another aspect that companies use to drive success. The idea is to get more “knowledge” from the data that you already have. This involves using information internal to the organization to drive strategies and insights based upon that proven business experience. By its very nature, Knowledge Management is closely intertwined with business administration systems and information management systems, and as a result can often become quite complex. But the fundamental tenet is a greater focus on the management of knowledge as a strategic asset and a focus on using that knowledge as an enabler of organizational learning and decision-making.
Let’s consider a new axiom for 2019: Business Intelligence Equals Business Advantage. The organizations that gain advantage in 2019 will be those that adopt these advanced capture technologies and strategies. The approach enables executives and decision-makers with the information and perspective needed to make quicker, more informed decisions based on what is happening within their environment and market – hopefully, before their competitors do. Organizations that can benefit most include those in financial services, health care, manufacturing, retail, telecommunications, transportation, and utilities. Look for solutions and partners that provide the right mix of experience, vision, and advanced capabilities that leverage the full advantage of Business Intelligence.
# # #
He is the managing director of Craine Communications Group. For more information visit CraineGroup.com.
If you found this article interesting, you might want to do a deep-dive into Machine Learning for Advanced Capture: