It’s time to address the 175 zettabyte elephant in the room. While robotic process automation (RPA) and other forms of intelligent automation technology have unleashed a torrent of activity and conversation about the role of artificial intelligence in transforming the enterprise, most organizations and their vendors shrink back from the subject of unstructured data. Worse, they’re often resigned to the fact that unstructured data has historically been too complex and difficult to meaningfully ingest and make actionable. As its name implies, unstructured data by its nature does not follow an established format or model, making it challenging to search and analyze. It can be generated by humans or machines. It can be text based, or not. Examples range from business documents such as invoices, contracts, emails and call center transcripts, to rich media such as photos, videos and audio files. By avoiding their critical mass of unstructured data, enterprises risk this elephant inevitably rising up and crushing them. Consider the weighty facts about the expanding universe of unstructured data:
Big data has been mission critical for nearly a decade in document-intensive organizations such as financial services firms, insurance providers, and real estate brokerages. But today, facing the unprecedented data proliferation, as well as other intensifying factors this eBook will address, the unstructured data imperative for these companies is greater than ever. As they fail to capitalize on what could be their most valuable assets, the risks and opportunities are becoming too great to ignore.
The longer enterprises wait to act, the worse the challenges will become. Those who don’t heed this imperative risk finding themselves in regulatory non-compliance or left in the dust by competitors. Fortunately, as this eBook will explore, new advances in deep learning algorithms and AI platforms are making unstructured data not only actionable, but unlocking tremendous benefits for enterprises of all types, such as driving out cost and risk, expanding margins and accelerating revenue, and elevating customer experience. Read on to discover how enterprise automation leaders, their centers of excellence (COE) and line of business leaders can (and must) begin to successfully leverage their unstructured data.
Application forms. Supporting documentation. Pictures and audio. Documents and data are the lifeblood of financial services, insurance, real estate and other major industries. They power everyday consumer interactions and customer experience. Unfortunately, they also pose significant threats to these organizations, especially in the case of unchecked, unmanaged unstructured data. A perfect storm of new and established challenges exacerbated by the COVID-19 pandemic pose significant risks and amplify the imperative for action.
1. Regulatory compliance
Aptly named, unstructured data is by its nature unorganized. This creates a considerable challenge when it comes to complying with the requirements of complex privacy regulations, ranging from GDPR to HIPAA and state-level personally identifiable information or personal health information (PII/PHI) laws. And, as unstructured data continues to proliferate, so does the risk. Gartner estimates 65% of the world’s population data will be impacted due to privacy regulations by 2023, up from 10% in 2020. Right-to-know and right-to-be-forgotten mandates place additional burden to maintaining compliance. And the costs of non-compliance can be huge; one report suggests that financial services firms face costs of $2.5 million annually for unstructured data compliance. To make things even more complicated, data collected in compliance with consent laws could be compromised if analysis changes the nature of that data. As Mathieu Gorge, CEO of compliance specialists Vigitrust, stated in a 2019 ComputerWeekly article, “Most members of the public would, for example, support the use of CCTV for public safety or theft prevention, he says. But combining video footage with, say, facial recognition and loyalty card data, would be a serious privacy breach.”
An enterprise’s unstructured data could include sensitive information, such as intellectual property, employee’s personal information, or other strategic documents. This makes unstructured data incredibly appealing for hackers, thieves or other bad actors. If an enterprise can not manage its unstructured data, it can not know what to protect. And although enterprises have faced a continually rising onslaught of incidents over the past five years, the threat has grown even greater in the past eighteen months. Cybersecurity attacks increased significantly and immediately amid the COVID-19 pandemic – especially in the financial services actor. Last year, VMware Carbon Black’s Modern Bank Heists report revealed that financial services firms faced a 238% increase in cyber attacks between February and the end of April, during the onset and global spread of the virus.7
Odds are that even if you’re not taking advantage of your unstructured data, your competitors likely are beginning to leverage theirs. And that could mean significant competitive advantages for them in the future (advantages like those we will cover in the next section. How great are the odds? At least 50/50 now, and far, far higher over the next three years.
4. The war for talent
In March 2021, a Microsoft survey of 31,000 workers globally revealed that nearly half of the global workforce (41%) are considering leaving their jobs.9 In April, a record 4 million people followed through and quit; followed by another 4 million in May. Dubbed “The Great Resignation,” this mass movement placed job vacancies at a 20-year high.
Worse, employers are facing a shortage of skilled labor to fill the roles. Corporations from McDonald’s and Walmart to Starbucks and Amazon have boosted wages or offered new incentives to drive recruitment and retention. Companies ranging from stalwarts like Nationwide Insurance and Mastercard to Silicon Valley giants Google and Facebook have moved to prolonged or even permanent work-from-home policies.
But, as one Gallup report10 shows, the exodus is not necessarily about any given industry or its pay. It’s about engagement. What does this have to do with unstructured data? Quite a lot, actually. For employees who have been mentally or physically burned out by the pandemic, and for the many more who have reassessed their personal priorities amid a once-in-a-century health crisis, the prospect of taking or remaining in a job that does not make them feel valued or deeply fulfilled has taken its toll.
Consider data entry and data processing professionals who spend hours of their work lives keying and rekeying unstructured form data. Enterprises that don’t consider how they can augment the roles of these individuals risk losing them. And, they risk being unable to recruit against other most satisfying digital jobs in software development or project management.
5. The unknown
When it comes to unstructured data, enterprises don’t know what they don’t know. And that presents tremendous risk on several levels. First, as noted above, there is risk of a data security breach or regulatory non-compliance, both of which can lead to significant financial loss or damage to a brand’s reputation.
Consider CapitalOne’s breach in 2019, which affected 100 million customers across North America; cost the firm $150 million11, including paying for credit monitoring for affected customers; and resulted in the company’s stock dropping 6% following the incident’s announcement. Less obvious can be the uncalculated costs of growing process inefficiencies and lost productivity. Consider the thousands of work hours spent on manual data processing that could be accelerated or eliminated – and the value created, not to mention errors reduced – by empowering teams with unstructured data automation technologies.
At the same time, to remain competitive in their markets and attractive on The Street, enterprises need to act now. Or else, they’ll be forced to face the music when digital disruptors steal share and outshine them thanks to their impeccable expense ratios.
“We are a data company.”
“Our data is our most valuable asset.”
These mantras permeate the mission statements and annual reports of modern enterprises of all kinds, not just those whose business models are digitally native. But, if this is the case, the vast majority of so-called ‘data’ companies are wasting their ‘most valuable asset’ by leaving 85% of it untouched. Unstructured data offers enterprises a potential goldmine of valuable insights and opportunities to drive both top line and bottom line revenue growth, as well as superior customer experiences.
Consider the power of predictive analytics for streaming services like Netflix and Spotify. In fact, by analyzing their subscriber data, Netflix and its AI algorithms have been able to influence 80% of the content viewed by its 100 million subscribers.12 It’s not only the media and entertainment that outperforms thanks to fully leveraging its data.
Deloitte Insights research shows that using AI and predictive analytics has given some firms “an early lead in realizing better business outcomes, especially in achieving revenue enhancement goals.” AI leaders in financial services have demonstrated:
Delottie further states that the advantage for these financial services pioneers will grow considerably if competitors do not move quickly.
Unlike RPA or other automation technologies which deliver bottom line improvements, unstructured data can also unlock topline revenue through new product or service opportunities. Consider the unlimited ways an enterprise could leverage the untapped potential of unstructured data.
By structuring unstructured data, enterprises can make their data more valuable to use and leverage across its technology stack, maximizing existing investments in everything from business intelligence (BI) tools to CRMs, ERPs and more. Consider these use cases:
ERP and insurance: accelerating the underwriting process
Assume you’re an insurance carrier, receiving requests for quotes from commercial brokers. You receive a raft of document bundles, each in different formats. The sooner you can get the pertinent information in front of your underwriter and respond to the opportunity – and increase your chances of winning. There’s a limit to how much a human can process.
Imagine if you had unstructured data technology to immediately ingest and structure this data, reducing turnaround time and helping you win more business, more quickly.
RPA and commercial real estate: mitigating interest rate shifts
Assume you’re a commercial real estate firm. Your deal desk is responsible for making sure all paperwork around a customer deal is in good order, and that it gets routed to and approved by the appropriate people. The deal review process involves people assessing a multitude of complex documents, many of them 10 to 100 pages in length.
Imagine if you had an unstructured data technology to convert these documents into a structured format, enabling an RPA tool to then enter the data into downstream customer relationship management (CRM) and enterprise resource planning (ERP) systems – and cutting deal times by more than half in the process.
CRM and consumer banking: shining a light on best practices
Assume you’re a consumer bank. To assure regulatory compliance, you need to record every customer call and maintain audio recordings and transcripts, associating them with the corresponding customer account in your CRM.
Imagine if you had an unstructured data technology to review those conversations to look for not only bad or non-compliant behaviors, but to identify language or interactions that deliver positive sales or customer service outcomes. You could then take those learnings and incorporate them into your trainings, improving customer experience and sales effectiveness.
Enterprises have long struggled with their unstructured data. Though effective with structured data challenges, RPA vendors and point solutions have fallen down or fallen short with traditional approaches to automation. But now, the tide is turning thanks to breakthrough deep learning technologies.
At its simplest, deep learning is a type of machine learning that simulates the behavior of the human brain, allowing it to be trained and learn from very large data sets. It can adapt and recognize patterns in unstructured data in ways that RPA can’t – enabling it to take unstructured documents and then restructure them for utilization. At the forefront of this revolution is Indico Data and its pioneering Unstructured Data Platform.
Through its innovative AI and ML software, the Indico Platform allows enterprises to ingest unstructured data at massive scale and add structure, enabling them to do what’s been impossible with traditional automation and analytics tools: realize the unlimited potential of their unstructured data. With the Indico Platform, enterprises can:
For the first time, Indico gives enterprises a single solution that allows them to ingest and structure a diverse range of unstructured formats – text, CSVs, videos, audio files, PDFs, contracts, emails, and much more – and gain rich insights, as well as maximize the value of their existing software investments, including RPA, CRM, ERP, analytics, and more.
Real-world success stories
At a time when only 20% of AI-enabled initiatives make it to production, Indico’s approach has delivered a 97% success rate in moving customers’ unstructured data projects successfully into production. From there, the business impact of the Indico Unstructured Data Platform has been immediate and pronounced. Here are just a few examples of how document- and other data-intensive enterprises in insurance, financial services, commercial real estate and more are turning their unstructured data into unlimited opportunities with Indico.
Based on recommendations from automation leaders at some of the pioneering enterprises above and several more Indico Data customers, here are a few first steps you can take to address your unstructured data imperative.
1. Admit you have a problem
The first step to finding solutions is always admitting there’s a problem. Treat unstructured data as its own category of challenges with its own set of process requirements and necessary technologies. Understand and embrace that it is uniquely difficult and that other platforms in the market typically can’t address it.
By the same token, take early steps to engage your line of business and IT partners to understand their needs and make the case for change. Too often, the “tyranny of the urgent” prevents organizations from tackling big challenges or opportunities. Teams feel they’re too burdened with supporting current processes that they can’t dare take on initiatives that may actually drive greater impact for the future. Get everyone on board with unstructured.
2. Identify areas for automation
Leverage those conversations with business units and practice areas to develop a roster of viable problems you could solve through automation. And, don’t feel that you need to take on the biggest challenges right away.
In fact, many companies recommend the opposite – failing and succeeding fast with smaller projects that prove immediate impact. Find the big unstructured data use cases; then determine the smaller question you could ask that would enable meaningful automation right away. Demonstrate feasibility, and then scale up and out.
3. Build the business case
Line of business leaders will want to understand the real-world impact of the projects you take on together. Demonstrate how your project can:
4. Find partners you can trust
You don’t have to go it alone. Look for expert partners who understand the specifics and nuances of unstructured data, who know why it is so difficult to solve, and who have the right technologies to unlock the potential of your data and maximize your existing technology investments as well.
About Indico Data
Indico is The Unstructured Data Company, enabling enterprises of all sizes to automate the intake and understanding of unstructured documents, emails, images, videos and more; analyze unstructured data, extracting actionable business insights and intelligence; and apply this data to create new application experiences to transform manual and inefficient processes into powerful solutions to solve complex business challenges. Through the Indico Platform, enterprises can gain rich insights and maximize the value of their existing software investments, including RPA, CRM, ERP, analytics and more. Indico serves leading insurance, financial services, banking, real estate and other document-intensive organizations, including MetLife, Chatham Financial, Cushman & Wakefield, and Waste Management.