To have the insights to make better decisions for their organization, knowledge workers today need swift access to the data they actually need and the ability to analyze the information.
Integral to this are tools powered by artificial intelligence (AI), so they can quickly search and identify relevant information they can use to resolve business issues and deliver customer care.
Without these AI-enabled solutions, employees will struggle to gain the insights they need to do their job.
As it is, 33% of workers feel they waste too much time gathering data, according to an IDC study. Another 22% point to a lack of knowledge of data sources as a challenge. The IDC research further reveals that workers spend 44% of their workday on unsuccessful data activities.
And while enterprises are realizing the importance of data, prompting many to collect and store customer and transaction information, few actually make use of the data they have on hand.
On average, 60% to 73% of data inside an organization remain untapped for analytics, according to Forrester.
A Veritas study also reveals that 52% of information stored by companies are of unknown value or are "dark" data. Another 33% of an organization's data are deemed redundant, obsolete, or trivia, the reports finds, with just 15% of stored data categorized as business critical.
Left unaddressed, unused data can prove costly. The Veritas report estimates that storing 1000TB of non-critical data can run up a bill of at least US$650,000 each year for an average midsized organization.
Organizations can avoid falling into the data trap if they deploy the necessary tools, powered by AI, to unlock valuable insights that already are sitting within their reach.
Surface domain knowledge so more can access it
Australian oil and gas company Woodside Energy, for one, did not have a systematic way to unearth insights from 30 years of engineering and drilling knowledge. This information was buried in unstructured documentation and among its most experienced engineers.
It then worked with IBM to navigate this complex environment, tapping IBM's Watson technology and cognitive computing prowess to drive data-driven decision-making across its organization. IBM Watson Lab Services put together the architectural plan and deployment strategy, while IBM Research developed ways to ingest Woodside's engineering expertise from its existing documentation.
Application programming interfaces (APIs) were built encompassing IBM Watson Natural Language Classifier, IBM Watson Discovery, and IBM Watson Assistant. Collectively, these tools enabled Woodside employees to search a corpus by asking questions as if they were speaking with a person. The datasets retrieved from the corpus then were ranked according to their relevance and best matches. User experience also was enhanced as engineers could interact in their own sector-specific language.
The IBM solutions enabled Woodside to chalk up AUD$10 million in savings, gleaned from providing employees with faster access to engineering documents and more intuitive analysis of the data. In addition, Woodside's geoscience team slashed the time it took to read and search through data sources by 75%.
More importantly, all its employees now have unlimited access to 30 years of domain knowledge, ensuring that the company can retain as well as build on its expertise.
Just like Woodside, organizations from different verticals can turn to IBM Watson to train analytics tools based on their sector's unique dialect, across multiple disciplines or job segments. Each of these can have its own terminology or sublanguage. Feeding this specialized knowledge into Watson also will further enhance the accuracy of its responses.
This is possible because IBM Watson is a cognitive computing system that continuously learns while it is in use. Hence, the results it generates will improve with age, as opposed to traditional software that typically degrades over time and becomes less efficient.
Forrester Report: Accrue USD 6.13M in Benefits Over 3 years- Learn how Customers Achieve a 383% ROI
Read this paper to learn how Watson can reduce costs by finding specific answers and trends from documents and websites using search powered by AI.
Download NowThis high level of performance is critical in ensuring knowledge workers have quick access to quality analytics, so they are empowered to make meaningful decisions and resolve complex business problems for their organization and customers.
IBM Watson Discovery enables companies to rapidly build cognitive, cloud-based exploration applications that surface actionable insights hidden even in unstructured data. The award-winning AI-powered intelligent search and text-analytics platform eliminates data silos and retrieves information buried inside enterprise data.
The platform uses innovative, market-leading natural language processing to uncover meaningful business insights from documents, webpages, and big data.
IBM Watson Discovery is also powered by features such as smart document understanding, giving organizations the ability to label text and better grasp critical components residing within their documents, such as headers and tables. Content mining also is based on contextual understanding, so document searches will identify patterns, trends, and anomalies more relevant to your line of business.
In short, IBM Watson Discovery truly understands the language of your business. Organizations that deploy the IBM platform alongside Watson Natural Language Understanding have enjoyed benefits totaling $6.13 million over three years, according to a Forrester Consulting study commissioned by IBM. They also achieve a 383% returns on investment and slash the time spent on data-gathering tasks by half.
IBM Watson solutions deliver AI-powered search and text analytics that will arm knowledge workers with the right information, at the right time, and in the right context.
Every enterprise has valuable data sitting within its environment that can provide the insights its employees need to make more impactful decisions.
IBM Watson delivers the capabilities businesses require to unlock this untapped value within even unstructured data, so they can identify the answers to remain competitive in their industry.
