Raw data by itself does not hold any value. You need to know how to take advantage of that data. Structured data provides definite classification of information, so businesses find it easy to access, manipulate, plot, extrapolate, and infer unknown trends from known data. Intelligent capture software with transformative technologies such as AI and Machine Learning offers businesses the opportunity to capture and take complete advantage of business data.
Organizations are increasingly focused on managing information and data resources, which have become their primary assets in business development. All successful businesses have one thing in common: they are quite adept at syncing people, processes, and data for more strategically informed decision-making and business solutions.
In order to use information effectively in a continually evolving business landscape, organizations must have access to data anytime, anywhere. The inability to get access to ready-to-use data is one of the primary factors impeding companies from achieving true digital transformation, and the BFS sector is especially lacking in this respect at 19% compared to other sectors (at 15%), according to a recent HFS Research survey. Companies large and small are confronted with a huge volume of incoming information that is often unstructured, and unprocessed. Unstructured data refers to any information that cannot be used instantly and directly without refining it and sorting into definite fields in a database.
Elements of a structured data source are allocated precisely to every field or label in a database, making it easy for organizations to search and retrieve information. This is called indexing. Indexing becomes especially important as your repository of data sources and information grows. Structured data and efficient data management starts with intelligent data capture.
Intelligent capture technology employs cognitive solutions like AI and Machine Learning. Machines should be able to read and decipher data that is sorted and classified, in order to provide the necessary inference that businesses can use. This is where Machine Learning and AI come into play and are most effective.
Manual data capture is labor-intensive and time consuming. Also, manually keying in data can introduce errors such as missing or wrong data entry and duplicity.
Another important aspect of traditional data capture is that it was essentially a back-end process — for instance, data entry from invoices would be made only at the time of making payments to vendors, in which case data entry was merely an exercise in archiving. With intelligent capture, data entry is ideally a front-end process — data from paper and digital documents is captured or extracted, classified, and sorted almost instantly, so the data entering business applications is clean and structured.
Having processed data enter organizations right at the beginning ensures not just easy data availability for various business applications, but also reduces incidence of businesses relying on falsified or incorrect information. This strengthens a company's audit trail and ensures regulatory compliance at all levels. Inefficient and error-ridden data entering business applications such as ERPs and ECMs can do more harm by forcing organizations to ‘read’ and ‘interpret’ the data wrongly. Data-intensive processes such as finance & accounting, records management, and IT, all qualify as good use cases for intelligent capture. Functions such as invoice processing, customer sales order management, inventory control, and all processes that are deemed data-intensive along the commerce chain from the buyer to the seller need an intelligent capture tool to reduce information chaos and data mismanagement.
Processed data has the power to propel businesses to infer, calculate, manipulate, and change ongoing functions to service the larger organizational goals and objectives — as an example, invoicing patterns captured from a particular vendor reveal insights on that vendor’s viability and usefulness with respect to an organization’s overall objectives.
A few pointers to note when incorporating intelligent data capture technology to manage your business:
Structured data is the genesis of effective digital transformation within organizations — and intelligent capture technology is the starting point.