The business landscape is moving faster than ever, with transformative technologies fueling innovation across industries. Professional services organizations – from data providers and publishers to consulting and investment management firms – are no exception, with digital acceleration promising to unlock all-new routes to growth. However, the full potential of transformation is currently hamstrung by issues with the very lifeblood of digital-first organizations: Data.
While ever-growing volumes and diverse data sources enrich market intelligence profoundly, there is an opportunity to generate further business value from data resources and unlock optimal growth. Several challenges – from high collection costs and integration issues to scalability and long refresh cycles – hinder information management, with stale and irrelevant data obstructing the emergence of accurate, real-time insights.
Overcoming these challenges can fundamentally transform the fabric of an organization: Research shows that companies operating in real-time achieve 97 percent higher profits and 62 percent higher growth than competitors.
This blog explores how future-facing enterprises are harnessing the latest in Generative AI (Gen AI) and hyperautomation to keep data fresh, remove bottlenecks and revolutionize the content lifecycle for a new era of real-time data processing.
Addressing the Data Quality Conundrum
As digital transformation re-shapes industries at pace, data has never been more integral to the success of an enterprise. Data accuracy, consistency and availability are crucial to making informed decisions at speed, ensuring actions are being taken based on rigorous and real-time intelligence rather than yesterday’s insights. However, despite the data explosion, the quality (of data) isn’t necessarily following suit.
Data quality represents the single biggest enterprise data challenge when creating better data ecosystems, according to research from WNS in partnership with Corinium Intelligence. Identified as an issue by 57 percent of C-suite leaders across different industries, data quality encompasses several dimensions, including completeness, conformity, accuracy and integrity, determining whether organizations can enable incisive insights, foster better decision-making and catalyze innovation.
The same research reveals that the most important aspects of data preparation to consider are maintaining data integrity and quality (60 percent), categorizing or classifying data for easier analysis (48 percent) and cleaning data to remove noise and errors (46 percent). A significant gap exists between enterprise’s perception of best practices and their existing capabilities.
Overcoming Challenges for a Real-time View
The gap arises from reliance on time-consuming and error-prone manual data collection and an inability to seamlessly integrate raw or unstructured data from multiple sources. This lack of seamlessness can create bottlenecks when increasing product coverage or attempting to scale. At the same time, the absence of a single source of truth means many organizations are left without a means of measuring, monitoring and improving data accuracy.
Promisingly, next-generation solutions that combine the power of technology with human expertise are emerging to help organizations overcome these issues. These solutions excel in intelligent data research, extraction, summarization and publishing to enhance information processing with speed, accuracy and scalability.
Harnessing AI and Hyperautomation in Data Management
Such solutions can transform the entire end-to-end content lifecycle, so let’s start with data collection. By harnessing AI-powered tools, organizations will find themselves able to automate the collection of data from structured and unstructured sources, researching at speed and scale. Applying the latest in AI and Machine Learning (ML) means this data can be seamlessly contextualized and intelligently extracted to ensure intuitive understanding across the enterprise.
With Gartner estimating that more than 80 percent of enterprise data today is unstructured, this first step alone can prove transformative. But from this position of strength, further evolution can be experienced through Gen AI and Large Language Model (LLM)-powered research, translation and summarization, providing people with the right insights at the right time. By automating these processes, professional services organizations can limit errors, reduce costs and accelerate data refresh cycles to near real-time.
So what kind of results can be achieved? By harnessing platforms that enable intelligent information processing, teams can expect to locate information four times faster. More specifically, one leading legal publisher reduced its refresh cycle for more than 6,000 data points from six months to just 24 hours, while a UK-based financial services company improved its efficiency by 45 percent and accelerated time-to-market.
Human assistance, however, remains integral, with oversight required to overcome blindspots and ensure quality output. It’s an area that many organizations are currently overlooking.
Unlocking New Opportunities with Enhanced Intelligence
Professional services organizations must develop advanced data capabilities to fully unlock the potential of a digital-first era. Real-time intelligence provides companies with an accurate reflection of the industry landscape, enhancing innovation, enabling better decision-making and driving measurable success, including additional revenue streams.
Beyond these benefits, real-time intelligence opens doors to untapped opportunities. Gen AI exemplifies this potential: 40 percent of enterprises cite concerns about insufficient high-quality training data for Gen AI solutions, while 62 percent turn to third-party expertise to optimize enterprise data training.
By partnering this way, organizations can instantly access the data, digital and domain expertise required to generate optimal business value from their data resources, automating the content lifecycle securely and cost-effectively. In doing so, enterprises can build new capabilities, reach new heights and deliver greater value for all.
Discover how Gen AI and hyperautomation can revolutionize your organization’s approach to data processing.