Executives need insight into their companies to better understand what they are working with and to:
However, with 80% of data locked away in Unstructured Data, getting to and leveraging it has proven difficult for many companies. In the context of limited budgets and prioritizing immediate infrastructure needs, making sense of complex data may seem like a nice-to-have versus a need-to-have.
What Exactly is Unstructured Data?
Information that falls neatly into rows and columns that can be sorted, like a spreadsheet, is considered structured data. It can be easily accessed and modified. Images, threaded emails, PDFs, and paper are examples of unstructured data because value within this information is difficult to search and extract without the correct tools.
Automation and artificial intelligence (AI) solutions effectively decipher unstructured data and yield almost immediate results; there are consequences when waiting to implement them.
The best way to avoid regulatory non-compliance is to proactively identify and mitigate risk within contracts.
However, historical contracts—often unstructured, unsearchable, and unusable—are a risky proposition when compliance is in question. Companies largely don’t know where their contracts are, or what is in them.
Relying on manual efforts to analyze thousands of records in time to meet compliance demands is an expensive and losing strategy.
It is estimated that the cost of non-compliance is
3 times higher than the cost of compliance.
Contract Lifecycle Management (CLM) became a trend in 2018, where more and more businesses see real operational benefits associated with digitizing and analyzing contractual agreements. Rightfully so!
Most companies make significant investments in technology platforms, like BI and analytics solutions, designed to help make businesses run more efficiently. The quality of business insight for these solutions depends on the quality of the data fed into them, and the statistics are rather daunting:
Considering that 80% of company data is hidden away in unstructured format and is not accessible by analytics solutions, it almost seems obvious why these statistics exist. How can data insight projects succeed with only a fraction of data available to analyze?
With intelligent data, companies realize the ROI of these systems and processes faster.
Every inch of data needs to be stored either in the cloud or on-premise, whether structured or unstructured. No matter where it is housed, data storage is costly and has become big business.
According to a survey conducted by AFCEA, top 3 data storage concerns were:
This signifies that IT leaders understand the value of their company data by prioritizing its safety, but according to the Seagate survey of mid-large enterprises, only about 25% of company data is actively leveraged, while the rest remains largely unutilized.
When businesses tackle their unstructured data by implementing automation tools to remove duplicates, legacy, and useless information, they can cut data storage costs up to 50%.
Agile digital competitors will win market share because of their ability to use data to deliver superior customer experiences and the services they demand. But legacy organizations find it hard to compete because so much of their content is tied up and not consumable by analytics engines or usable in automated workflows.
Data-driven organizations are 23 times more likely to acquire customers than their peers.
Only 15% of business leaders surveyed consider themselves very effective in delivering relevant and reliable customer experiences.
Enterprises that implement effective Unstructured Data Analysis methods to feed more and better content into their systems are the ones who will see significant competitive advantages.
Rather than assemble teams of subject matter experts to comb through mountains of unstructured data manually, businesses can implement intelligent automation to leverage the most relevant and valuable information.
By getting the first step in the document lifecycle right (i.e. the Discover stage), Adlib customers are one step ahead of the game.
How are these organizations improving capture processes so that ALL of their information is gathered, standardized and stored appropriately for easy access and long-term preservation? In a few different ways, including:
A global leading insurance provider relies on Adlib to increase data quality for analytics resulting in improved decision-making and reduced underwriting risk.
Adlib Transform intakes all company contracts, agreements and policies from various sources such as Microsoft Exchange inboxes, SharePoint sites and other Enterprise Content Management systems, leverages the best-of-breed OCR to convert the documents into searchable PDFs and feeds clean key metadata into insight analytics tools.
A Fortune500 petroleum organization leveraged Adlib to digitize well log data to help the executive team better assess drilling opportunities.
The reality is that not transforming dark data into intelligent data is a sure-fire way for enterprises to leave money and opportunity on the table. Organizations that use Adlib’s Document Transformation Platform to discover, enrich, and evolve complex content will experience a whole new level of performance and profitability.