The end game of Enterprise Information Management (EIM) is refining raw information into a valuable enterprise asset. What makes information/data valuable is a function of:

• The nature of the information/data in question
• The ways the proprietors of that information/data can envision using it
• The technology available
• The insight, talent, and skill of those charged with executing EIM strategy.

Thus, while it’s common to think of EIM as tech-driven, the most successful EIM strategies are actually far more business-driven than one might expect. Here’s a look at best practices planning and executing an EIM strategy:

Approach it from a pain-point perspective

Perhaps your marketing department is mired in data inconsistencies and duplications, making communications-driven campaigns unwieldy and inefficient. Perhaps the rapidly evolving set of regulations and standards applicable to your business means your compliance program is straining to aim at a moving target. Perhaps you’re a provider, and the six different payers with whom you’re under contract have six different sets of forms and requirements. If you’re thinking about adopting EIM, you probably already have in mind some of the challenges you believe can be addressed through better information management. Such challenges can create concrete business cases you can present to potential executive sponsors and which can form a foundation for assessing the success of your strategy.

Get your stakeholders involved from the get-go

Involving your stakeholders in brainstorming and strategic discussions is, itself, a low-tech form of information management. That’s because EIM is best positioned as a way of supporting critical business activities. Where do your identified pain points interfere with the key business priorities of your stakeholders? How can they be addressed through information management?

Assess your baseline

What’s your baseline level of information management? What are the systems you’re currently using? Who are the vendor(s)? How long are the contractual relationships meant to run? What’s your organization’s approach to information governance?

Secure executive sponsorship

One or more strong executive sponsors can be helpful in securing the necessary funding and support for an EIM initiative. You’ll want to marshal your allies right at the outset, keeping them informed and on-board and available to manage points of friction.

Cultivate enterprise awareness

Congratulations, you understand the need for EIM. But not everyone does. At least not yet. Communicating the need for EIM, the challenges it addresses, unrealized value of information as an asset will go a long way toward readying the people in your organization for the changes envisioned. Overall, your organization needs to be “ready” for EIM, and here are some factors to consider in assessing that readiness.

Adopt a phase-in approach to implementation

You may have a global/big-picture vision of what your organization can achieve as a result of implementing comprehensive EIM, and while EIM is, at its core, an enterprise-wide strategy, it can only be accomplished in manageable bites. But your overall plan should be global and take into account how each phase may affect the next one and the big picture overall. For more specific guidance, each of the factors identified here are equally applicable to EIM as they are to digital transformation in general.

Come up with objective standards for measuring success

The best argument for moving from the first phase to the second and the second to the third, and so on, is results. Ideally, you’ll come up with a way of objectively measuring those results before you begin EIM implementation.

Start with a quick-and-easy win

Starting with a project that’s relatively quick to implement and evaluate, and that’s likely to be a win, will go a long way toward cultivating the continued support and cooperation of your sponsors and stakeholders.

Choose the right partner

EIM implementation requires more than a technology vendor and more than a service provider. EIM implementation requires a strategic partner, one that’s experienced in all aspects of comprehensive EIM planning and implantation. Ideally, your EIM partner will have experience in EIM planning and implementation within your particular industry, as well as in working with customers around the same size as your organization.

As a global leader in business process optimization, Exela works with over 4,000 customers in more than 50 countries and in numerous industries, including banking, finance, healthcare, legal, manufacturing, the public sector. Although we count over 60% of the Fortune® 100 among our customer roster, we work with organizations of all size and on projects of all imaginable scale. We’d welcome the opportunity to talk to you about your organization’s specific challenges and needs.

Information is in abundance, and it’s only becoming more so. The availability of information presents opportunities to create new value and optimize experience for both customers and employees. But leveraging information as an asset presents challenges and risks, including:

• The sheer volume at which data, and especially unstructured (data not easily parsed by basic algorithms) is entering organizations, which volume is only accelerating
• Inconsistent data sources
• Data duplication
• Data inaccuracy, including data that was, at one time, accurate, but no longer is
• Data content inconsistencies
• Data security
• Data privacy
• Compliance with global regulations and industry standards.

The good news is these challenges and risks can be met via “Enterprise Information Management” (EIM), which is also known as “Enterprise Data Management” and “Master Data Management.” EIM is an aspect of Information Governance (IG), which is also known as Data Governance and refers to a business’s overarching policy for handling all information in any form, received from any source or generated by the enterprise, with the end game being the optimization of that information (i.e. maximizing value while mitigating risk associated with the information). You can learn more about IG here.

How is EIM different from IG?

IG addresses an enterprise’s overarching policies and strategies with regard to information. EIM addresses how those policies and strategies are carried out within the enterprise.

So what is EIM?

EIM is an integrative discipline for structuring, describing, and governing information assets across organizational and technological boundaries to improve efficiency, promote transparency and enable business insight. In other words, it’s not any one thing, and it can’t be achieved through the “plugging in” of any one solution or platform. EIM may be best understood as the following four pillars that support the structure of your business:

• Enterprise Content Management (ECM), which is a system for managing information flows across a business, from ingestion to archiving and disposition. Included within ECM is content digitization. Content digitization addresses, among other things, the challenge presented by inconsistent data sources and unstructured data. Also included within ECM is content organization and storage, which establishes rules for storing, sharing, securing, and culling information for use in business analytics and process automation. Exela’s ECM solutions leverage artificial intelligence (AI) and machine learning (ML), among other tools, for establishment and carrying out of such rules.
• Business Process Management (BPM), which is a system for routing your content-managed information into day-to-day processes, working across information siloes while maintaining data privacy as required by government regulation and business standards. The end goal of BPM is optimizing business efficiency while reducing enterprise risk. Exela’s BPM solutions make use of AI and ML, among other tools, to optimize employee experience at both the front-office and the back.
• Customer Experience Management (CEM), which sets up a process for culling your managed content to track and gain insight into customer interactions, make predictions, and optimize each part of the customer experience journey, from business generation to end-user-experience. Powered by AI and ML, among other tools, Exela’s CEM solutions help businesses to optimize customer experience, including by identifying and addressing customer needs and maximizing reach.
• Business Intelligence (BI), which refers to turning information into actionable insight leading to better decision-making and then making that insight work for you through consolidation, visualization, alerts, and search capabilities. Exela’s BI solutions include AI-powered information management and consolidation/centralization of search capabilities.

We’ll be discussing more about EIM and how best to implement EIM in future blogs so stay tuned to the Exela Blog. In the meantime, don’t miss this insightful thought leadership article from Exela’s President, Suresh Yannamani on how healthcare organizations can use EIM to prevent fraud

Businesses, irrespective of their size and domain, require access to information in order to make informed business decisions and develop successful strategies. This information is often derived from data, so we might think that more data leads to more information, so more is better. However, it is possible to have too much of a good thing. Data is only valuable if you can use it, and without proper structuring and management tools such as cognitive search tools, companies can find themselves drowning in data.

At the onset of the “digital age,” enterprises struggled to weed through bottomless pits of data, searching for information in unstructured environments. Employees would spend hours of valuable time that could have been used on more meaningful and productive tasks.

Initially, search results were determined solely by the presence and frequency of specific keywords. Search functions have, of course, improved and changed in many ways since those early days. One of the most important shifts came with the introduction of natural language processing and machine learning capabilities, which today power cognitive search tools.

So What is Cognitive Search?

When it comes to data and information, accuracy and relevance make all the difference. Even with the right keywords and key phrases, you can spend hours looking through and collecting information, and still not find what you’re looking for. With so much data on hand - and more being added by the minute - it isn't easy to extract what’s relevant.

Cognitive search is driven by artificial intelligence (AI) and aims to deliver contextual information that is highly relevant to a user’s search request. Relevancy determinations are achieved by inferring a user's intent and finding patterns and relationships within the data.

How Does Cognitive Search Work?

Natural language processing (NLP) and machine learning are used to mine, extract, and summarize data from different sources, irrespective of the formats.

NLP has some restrictions, as it focuses solely on linguistics, whereas cognitive search follows a language-independent, statistical approach to understanding human information that is fine-tuned by the use of linguistics. Simply put, cognitive search is aligned with users more naturally, providing a 360-degree view of the user journey and their past interactions to personalize the experience.

Here are some benefits of cognitive search and how it can be an asset:

Penetrate Extensive Data Sources

We’ve all heard that data is a valuable commodity in today’s world, but even the best information is no good if you can’t get to it. Cognitive search has enabled businesses to extract information buried within voluminous sources quickly, and more accurately, effectively unlocking the potential value of large, previously daunting datasets.

Improve User Experience and Engagement

Cognitive search doesn’t just make it easier for employees to find valuable information and make smarter choices. A customer-facing cognitive search function can create a more effective, streamlined, and satisfying user experience. One of the biggest turn-offs for potential customers is a website that is confusing or difficult to navigate. Including a search function that accurately directs them to content, based on their intent rather than just the keywords they used, can make a huge difference - especially in jargon-heavy industries.

Access Relevant and Accurate Information

Natural language processing doesn’t just help cognitive search tools better understand the intent of the search query - it also helps the system gauge the relevance of text content like email, blogs, reports, research work, and documents, as well as media content like meeting videos and audio recordings. This helps it do more in-depth research and come up with relevant information.

Enhanced Search Results

Machine learning algorithms help in providing better search results. It touches searches through structured and unstructured data and lends profound, meaningful, insightful search results.

Personalized Recommendations

Users’ previous histories and usage patterns can be factored into each new query, better learning their preferences and interests to recommend content that is more likely to be relevant.

Final Reflections

Using cognitive search tools enhances the user search experience, whether it's for customers or employees. With less time sifting through data, employees can spend more time on their core tasks and customers can feel satisfied that their questions were answered in a quick manner.

Learn more about what cognitive search can do for your business.