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The Future ofDocumentManagement

A WHITE PAPER FOR SWISS POST SOLUTIONS

FEBRUARY 2019

Introduction

Digital transformation is now front of mind for senior executives (CXOs) across virtually all industry sectors and is being driven by a number of objectives, namely:

The Future of Document Management Page 2

An overriding emphasis on taking an outside-in view of organizational processes with a strong focus on enhancing the customer experienceA desire to switch to machine-first delivery, increasing levels of straight-through processing and reducing cycle timesAn enhanced ability to extract actionable insight for business advantage from all documents, interactions, and touch-points.

Document management is no exception to this. Indeed, a greater focus on document management transformation is being driven by organizations looking to extend their operational transformation with a holistic end-to-end approach instead of a narrow IT focus. Accordingly, the nature of document management will transform massively between now and 2025. This white paper maps out the future shape of document management, looking at:

The evolution of documents & channelsThe increasing role of unstructured dataDocument management process transformation (establishing a transformation roadmap, transformative technologies, and build vs. buy)Document management in 2025.

The Evolution of

Documents & Channels

Below is a forecast for the global document management market over the next four years:


This modest decline in the managed document management market is a result of the migration from traditional paper-based interaction with customers, suppliers, and employees to digital interactions; for example, using online portals. However, these overall numbers mask the deep underlying changes taking place in document management, developing from archiving and recognition into data capture and information processing. Finance & accounting, for example, is currently dominated by the need to process invoices received either in paper form by post (or as pdfs by email) and largely captured and processed manually. This is now changing rapidly, with organizations looking to apply Natural Language Processing (NLP) and RPA to automate invoice data capture and processing.

At the same time, the move to digital channels is sharply illustrated in the area of customer service, as shown here:


The use of traditional voice is expected to decrease by around 2% per annum over the next seven years, while the use of digital non-voice is expected to increase by around 13% per annum. Although the voice channel will remain dominant through 2025, by then traditional voice will only account for a minor share of overall transactions. Web chat, both assisted and unassisted, has been the fastest growing channel in recent years and will continue to grow rapidly, fueled by ever-improving machine learning and NLP technologies. Indeed, this mix of document types is starting to change even further with Alexa chatbots now starting to complement the now established text chatbots, and even video imaging which is being used, for example, in support of automotive and building insurance claims and for component inspection on the assembly line. The principal requirement here is to move to a digitalized and optimized multi-channel environment, replacing human involvement in simple interactions with automation and/or service factories, while retaining it for complex and high-value interactions. This simple principle applies across touchpoints and is equally applicable to supplier, partner, employee and customer interactions. However, this increased emphasis on digital does not necessarily reduce the emphasis on unstructured data. Indeed, most customers have a strong preference for an unstructured interaction with companies rather than a highly structured form-based approach. So, digitalization supported by the application of RPA, analytics, and cognitive technologies is critical to transforming the experience, quality of service and service cost-effectiveness, and to make a major impact on service turnaround times. Mass personalization is also important, with AI increasingly providing the first level of interaction and/or supporting human prompts.

Digital is increasing 13%

per annum

Digitalization supported by the application of RPA,

analytics & cognitive technologies is critical

The Increasing Role of

Unstructured Data

Unstructured data capture and processing is key to the future of document management. Only a few years ago, paper documents were still commonplace in many organizations with, for example, large volumes associated with employee records in the HR department and customer agreements in financial services. More recently, organizations have typically digitized (scanned) and indexed these records so that they can be more readily accessed and processed online. Leading organizations are now starting to take this to the next stage by ensuring digitization and structuring of information, employing NLP technology to go through these archives and extract and create structured databases of key fields. However, this technology is still relatively embryonic. At this stage of technological evolution, NLP can only be realistically applied to a relatively standard set of documents for relatively well-defined use cases, and the technology requires assisted learning whereby the documents/fields that the technology cannot handle are passed to manual processing. Although the technology will learn and become more accurate over time, there will remain a need for the technology to be trained by (and the not inconsiderable level of exceptions to be handled by) humans for the foreseeable future. Therefore, companies that can achieve a mix of technology and humans working in a seamless process have a great advantage. Indeed, NLP will, for the next few years, be better suited to case-by-case implementation across relatively homogeneous and semi-structured transactional document streams in areas such as supplier and catalog management, purchase invoice processing, and 3-way matching than to data extraction across a totally unstructured and heterogeneous document base.


Companies with a mix of technology & humans working in a seamless process have a great

advantage

Unstructured data capture & processing is

key to the future of document management

Even here, an element of manual processing will remain for some time. Accordingly, deployment or outsourcing of technology alone will be insufficient to handle the growing volumes of unstructured data. Companies will need a mix of technology, human workers and process excellence. So, while the market for traditional document management services is relatively static in value terms, the demand for digital transformation of document processes is growing very rapidly. In particular, the use of RPA and AI technologies within document management is increasing fast, as shown in the table below. This indicates the growth of information processing services associated with document management.


Of course, processing existing imaged documents and incoming paper and pdf documents is just the tip of the iceberg for handling unstructured data. Customers in both B2C and B2B environments have a strong need for real-time capture of information across channels such as chat and social media, ultimately including video. Accordingly, the volume of unstructured data will continue to grow exponentially with every interaction, whether by voice, web chat, social media, or emailed pdf potentially being captured to provide greater customer or business insight and improve the commercial effectiveness of the organization. Cloud data storage will become a critical part of the overall architecture as will data lakes.

The volume of unstructured data will continue to grow exponentially

with every interaction

Document Management

Process Transformation

In undertaking a digital transformation of document management toward information processing, it is important to be driven by business outcomes and KPIs rather than process SLAs. Then, bearing target business outcomes in mind, organizations should take the opportunity to reimagine document management and to take into account the opportunities created by new digital technologies in both the short-term and the long-term. The transformation roadmap needs to be strongly focused on business outcomes. Typically, while cost reduction is always a significant hygiene factor (and extensive deployment of intelligent automation combined with business process service factories can be expected to deliver cost savings in the range 30%-50%*), the most important business outcomes to enable document management to maximize its contribution to the business will be:


Digital transformation of document management

should be driven by business outcomes &

KPIs, not SLAs

Establishing a Transformation Roadmap

Increased customer satisfaction (CSAT)/Net Promoter Score (NPS) & reduced customer effort, whether for customers, employees, or suppliersReduced processing time and levels of manual/exception handlingIncreased revenuesImproved access to information and decision-makingBuilt-in compliance and quality.

* Source: NelsonHall 'Business Process Transformation through RPA & AI'

At the same time, the framework needs to allow for agile process transformation. Times have changed in the world of IT projects, and the same applies to operations and document management. The key words are now agile and modular. While some foundational architectural and enabling enhancements may be necessary, it is important that the document management transformation can then be rolled out as a series of short time-boxed sprints addressing individual opportunities or use cases, with new use cases, channels, and technologies introduced in sprints rather than multi-year projects. Each technology and channel should be effectively a single module, probably cloud-based, that can be plugged in or out of the wider document management architecture. The channel environment is changing at an increasing pace, with new channels appearing, old ones disappearing, and enabling technologies undergoing a phenomenal rate of change. Accordingly, responsiveness to change and speed of adaptation of the document management ecosystem have become critical organizational success factors.


It is critical that the architecture

adopted is modular

Transformative Technologies

Because of the rapid rate of technological change, individual platforms may need replacing and additional emerging technologies will need to be introduced. The precise nature and mix of channels and AI technologies that will be required in 2025 cannot be known with any precision at this stage, and so it is critical that the architecture adopted is modular in nature. In addition, multiple channels should be largely interchangeable so that each channel can potentially be used at each point in the process without loss of data or intelligence. Accordingly, a digital backbone is required that can both interface with core business systems and knowledge bases and with individual channels.

Key technologies will include OCR/machine vision, NLP for text extraction, RPA for handling simple rule-based transactions, analytics and machine learning/deep learning, with (by 2025) technologies such as distributed ledger gaining increasing acceptance in verification of multi-party transactions. Once the document has been identified increasingly in conjunction with the extraction of key data, workflow/case management technology will then be key in routing the document/data to the appropriate application or human for processing.

Of course, all these document capture and processing technologies will need to interact with multiple existing legacy platforms, which may or may not be scheduled for replacement. Accordingly, it is important that the new document management infrastructure sits on top of legacy systems and can interface with these or their replacements. In some cases, with more modern applications, this will be via API; in other cases, RPA will be required to mimic data input or transfer by a human. These systems and their successors, like the wrap-around technologies now being introduced, will increasingly be cloud-based to provide improved flexibility to handle seasonality and variable document/transaction workloads. However, for the foreseeable future, it is likely that there will be two fundamentally different styles of document management and information processing, which will need to be addressed in differing ways. First, there is transaction processing in support of a particular process, e.g. accounts payable or claims processing. Here, the documents associated with a particular process, though unstructured, will all relate to a single use case and technologies such as OCR, NLP, and RPA can be applied in a way that only a modest, and declining, number of exceptions will need to be handled manually. Second, there is the general-purpose mailroom, where the traditional emphasis has been to digitize incoming documents and then route them to the appropriate department or workflow. This situation will require a much greater level of manual intervention than single-purpose document streams. However, in both cases, the increasing amount of unstructured data requires new processing models. Best practice here is digitization at first touch-point, enabled by intelligent automation combined with manual handling, and directly flowing through information processing workflows, ideally processed by service factories.


Another key distinction is between synchronous and asynchronous information capture and processing. There are still many areas where asynchronous information capture and processing is appropriate, though the cycle times for asynchronous processing will continue to come under considerable pressure. Media such as mail that were formerly handled asynchronously using the idle-capacity of operations will increasingly be handled in a quasi-synchronous manner to meet end-user expectations of speed and turnaround time. Elsewhere, many areas of interaction are now largely synchronous. This is particularly marked in areas such as speech-to-text and automated webchat, where the next best action or response needs to be provided in real-time.

Key technologies include OCR/machine vision, NLP , RPA

& machine learning


A key factor in considering outsourcing is a lack of skill or

bandwidth to reimagine & implement digital document management & information

processing technology

Build vs. Buy

So, when should an organization consider building its own document management and information processing capability and when should it use a third-party for implementation and service provision? The key determinants in building an in-house document management capability are:

The initiative is core and a strong USP for the organizationThe in-house expertise exists, and resources are available, to implement the document management backbone and technologies with a global footprintThe organization requires a unique approach to document management which is not available from a third-partyAbility to establish critical mass to justify investments in technologies, service platforms and delivery centers on- and offshore.

The key factors for considering using a third-party in support of document management are:

The document management and information processing service is considered non-core to the organizationThe organization lacks the skills or bandwidth to reimagine and implement digital document management and information processing technology or the ongoing investment required to stay up-to-date with changes in document management technologiesThe number of different digital channels is growing and changing rapidly and produces increasing amounts of unstructured data that must be handled cost-efficiently, speedily and at high-quality levelsThe number of documents is expected to decline overall, or in support of individual activities, and it is not considered worthwhile to invest in support of either document management overall or in individual run-off areasThe organization wishes to benefit from industry best practices and economies of scale it cannot or doesn’t want to achieve by itselfThe organization wishes to implement a new approach to document management and information processing in support of specific urgent use cases faster than can be achieved in-house due to transformation priorities.

In order to standardize a document or transaction stream, it is necessary to achieve a certain threshold of transactions, and this threshold increases if machine learning is to be applied to the ‘document’ stream. This is true for both in-house transformations within Global Business Services (GBS) organizations or shared service centers (SSCs) and third-party services. However, by 2025, there will be an increasing number of business process factories offered by vendors, each specialized for particular processes, transactions, and document types. These factories will offer heavily standardized processing in areas such as accounts payable, contract management or payroll processing, and will be multi-tenant in nature with a degree of parameterization provided to support client-specific customization. Factories will be based on best practice process models, leveraging combinations of cloud-based technologies including OCR, RPA, and AI and potentially will be supported by personnel based in multishore centers. While nearshore centers will still typically be required for local language capability, the majority of back-office processing work is likely to be handled from low-cost offshore centers. The increasing levels of automation within document capture and processing will also facilitate handling peaks and troughs of document activity by reducing the numbers of personnel required and typically shortening the training times for additional personnel. At the same time, there are many processes where investment in new forms of document capture and processing may be hard to justify. In these areas, an organization may achieve a more rapid increase in process effectiveness and return on investment by using a third-party business process factory.


By 2025, there will be an increasing number of business

process factories offered by vendors, each specialized for

particular processes, transactions, and document types

Nearshore centers still required for local language

capability

Offshore centers will handle back-office

processing

Document Management

in 2025

Document management is currently changing at a more rapid pace than at any time in the past 20 years, and this pace of change will continue through 2025. The table below summarizes some of the key developments in document management between now and 2025.


Document management is now no longer about largely batch-based manual and OCR-based indexing of paper and pdf documents and extracting a few key fields. It is an increasingly strategic element in digital transformation incorporating much greater ability to analyze and process both incoming and historical documents in-depth and in real-time across a range of channels to enhance customer service, reduce processing times, and obtain revenue uplift. By 2025, it should be possible to automate many of the major use cases within transaction processing with reduced manual handling and leveraging a combination of new technologies like RPA, machine learning bots, and service platforms, resulting in steadily decreasing numbers of exceptions.


research.nelson-hall.com

About NelsonHall

NelsonHall is a global industry analyst firm dedicated to helping organizations understand the ‘art of the possible’ in IT services (ITS) and business process services (BPS), and specifically how to identify, adopt, and optimize the next generation of digital technology and services for their business. Founded in 1998, and with industry analysts in the U.S., U.K., and Continental Europe, NelsonHall has a 20-year track record of providing the highest quality market research to both the buy-side and supply-side of the ITS and BPS markets. All our research is onshore and in-house, and we are highly valued for both the insightfulness of our research and the quality and ready accessibility of our industry analyst inquiry/support service. To find out more, contact [email protected].