ECM strategy evolves from focus on acquisition to actualization

Find out why companies are turning to advanced search, analytics and other techniques to get more value from data stored in enterprise content management (ECM) systems.

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Enterprise content management guideFind out why companies are turning to advanced search, analytics and other data management techniques to get more value from data stored in enterprise content management (ECM) systems.


Table of Contents

Enterprise content management overview: Understanding ECM systems
Five ECM technology trends that can affect your ECM strategy
Disjointed eDiscovery practices exposing companies to legal risk, rising costs
ECM strategy evolves from focus on acquisition to actualization
Expert advice for enterprise content management technology purchases


Core enterprise content management (ECM) functionality is no longer cutting-edge technology for most corporate IT departments. Companies know how, where, and for how long to store documents in a central repository. Their problem is leveraging the exponentially increasing amount of data they're storing -- data that's often underutilized and provides little value to the organization.

Driving this trend is partly that the ingestion of data is becoming easier and easier. But as the volume of data in ECM systems increases, IT departments' efforts must also increase. This often does not allow for proper planning of taxonomies and data maps. The result is frequently a large collection of data that corporations know contains immediate value, yet they have no idea how to access it. In the worst-case scenario, a company is left with valuable content in one or more "catch-all" buckets and lacks the resources to give it structure.

Actualization of content remains the focus of organizations and one of the greatest expenditures in their ECM implementations. That's why business intelligence (BI) and content delivery are the segments of the ECM discipline that are evolving the fastest. Consequently, they are the segments of ECM with the fewest best practices and least consensus on use.

Another challenge is managing -- and finding value from -- nonstandard data types. In most companies, day-to-day documents are covered, and knowledge workers know very well how to find and use them. These documents usually fall into the ECM category of collaboration, record or general workflow. However, it's the content that is more periodic and unstructured, such as social media, that today is underutilized and poses the greatest risk. For example, corporations in litigation could be missing out on that one paragraph that wins a case; advertising companies could be missing out on hidden demographics; and companies currently in audit could be filling gaps in a punctured paper trail.

Getting to the true 'actualization' of content
To help better leverage stored data, many companies first turned to search. The creation of search and indexing was one of the brilliant evolutions in technology. Search is a powerful tool, allowing organizations a single access point into a dataset without prior understanding of the data's filing structure. It turned "catch-all" buckets of content into dynamically created on-the-fly folders. The downside of search is that it generally assumes the individuals doing the searches know the correct terms or criteria to find the documents they require. That's one reason why search is no longer enough. This is evident when watching the most popular consumer search technologies continually trying to re-invent themselves and become an even smarter tool. So the problem remains: There is intelligence within content that companies know exists, but they don't know the structure or the keywords to get to it.

Success requires a heavy reliance on knowledge workers being involved in the ECM technology decisions.

 

The next evolution was to create new types of search that could be applied to all that data, such as concept search, parallel search, federated search, and visual search. These technologies increase the searchers reach into the depths of content -- and they have provided a big step forward. Today, advanced search technologies have matured and are utilized heavily in enterprise-level BI platforms. Search has now been adopted by enough companies that best practices are fairly well known. However, enterprise search will always suffer from the reliance on an individual's a priori knowledge of what must already exist in a dataset. To get even closer to the vision of better utilizing stored enterprise data, data mining and analytics are the natural next step.

Data mining and analytics packages are the most cutting-edge group of ECM technology. For the sake of most conversations, data mining and analytics fall roughly under the same definition. As far as this article is concerned, they are the technologies that get at what search cannot. They incorporate pattern recognition, clustering and classification engines. The challenge with this area is its relative immaturity for most enterprise-wide usage. While the buzz around data actualization is often about techniques such as word clouds, visual data maps and unstructured content storage, most of this is, in fact, just buzz right now. Best practices in these areas are still being established. While there can be practical implementations of all these technologies, most companies should pursue them only as part of a larger ECM project.

Some tried-and-true practices remain. When implementing search or analytics isn't an option, records managers often default to taxonomies to gain access to information and retention schedules to manage them. This is a well-established area, highly successful for those regularly consumed and critical documents. While there will always be the pool of documents that just do not fit a taxonomy, a good taxonomy can still facilitate daily operations of any organization. But with the evolution of social content, records managers have their hands full bringing order to this type of content. If fact, many organizations are creating social media policies to remove it from the ECM equation.

So what should an organization do to better actualize content? First, know that utilizing content is a very broad and evolving topic that demands the focus of organizations. Success requires a heavy reliance on knowledge workers being involved in the ECM technology decisions. Next, organizations need to plan ECM strategies to align with the rapidly evolving technology world. Three years from now, advanced search will be old news, integrated BI and ECM will be the norm, and analytic bots will be the future. Finally, as with any project, companies must have a full understanding of their requirements, expectations and ultimate goals.


Chris Riley, ECM expertAbout the author: Chris Riley is a recognized industry expert in document recognition, enterprise content management (ECM) and analytics technologies. Currently, Riley is senior ECM & document capture architect at ShareSquared, Inc.; he lives and breathes technology and has built his career on helping companies buy, use and optimize advanced technologies for their business. Riley has 12-plus years of experience in this arena; during that time, he has owned three software companies and received several technology and business awards. He has degrees in business administration, computer science and mathematics, and holds certifications from the ECM trade organization AIIM as an "Enterprise Content Management Practitioner (ECMp)" and "Information, Organization and Access Practitioner (IOAp)." Riley also is a sought-after speaker and educator throughout the content gathering and delivery space. He can be reached at Chris.Riley@sharesquared.com.


Table of Contents

Enterprise content management overview: Understanding ECM systems
Five ECM technology trends that can affect your ECM strategy
Disjointed eDiscovery practices exposing companies to legal risk, rising costs
ECM strategy evolves from focus on acquisition to actualization
Expert advice for enterprise content management technology purchases


 

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