How are you Managing Your Information Assets?

Dan Carotenuto's picture
 By | July 09, 2013
in Data Quality, Information Capital, information management, strategy
July 09, 2013
A recent global research study by Information Builders and IDG Research Services uncovered some disturbing trends in information management:   “Companies are aware of the transformative power of using enterprise information management and analytics to align strategy and resources, but are failing to fully execute on its potential.”  More specifically, “less than 60 percent of respondents placed significant importance on extending data access to operational employees, only 50 percent indicated customers as a significant priority, and less than one-third of companies felt sharing key information with external partners and suppliers was necessary.”  
Why are organizations not fully executing on the potential of information management?  Is it that associated technologies are still not mature enough?  Advancements in integration technologies have continually improved our ability to consume, move and manipulate more data in more forms (structured, semi-structured and unstructured) than ever before.  For example, the ongoing maturity of big data technologies has removed several technological obstacles including the high volume, velocity and variety of data.  Cost obstacles have been mitigated since solutions like Hadoop run on commodity hardware.  And the advent of big data analytics technologies has resulted in new business insights.  If it is indeed a technology challenge, the issue might lie in organizations having to integrate multiple disparate products from multiple vendors or even from a single vendor—a common trait among vendors in the marketplace.
Failing to execute on information management potential might also lie in the approach organizations are taking towards managing their data.  We have heard many times over about viewing “data as an asset,” especially when discussing data governance.  I am wondering if the continuous repetition of this concept has diluted its meaning.  As a remedy I suggest we not only view data as an asset but also truly manage it as an asset.  
Effective Information management demands treating data as assets and managing them as such.  Information assets fall under the intangible assets umbrella on the balance sheet and in the asset management domain and, thus, require a systematic process of operating, maintaining, upgrading and disposing of them cost-effectively.  Production-based asset management principles can be applied to data and information the same way they are applied to facilities and equipment.  For example, information assets should be managed to provide the greatest return on investment, highest possible net benefits, shortest investment payback periods and their effective management should yield maximum use by stakeholders, systems and processes.  
iWay 7, recently announced by Information Builders at their annual user conference, is an example of an Information Asset Management Platform that enables organizations to optimize performance by exploiting the full potential of their information assets.  It’s three suites comprised of data and application integration technologies, data quality and master data management capabilities can ensure the accessibility, reliability, timeliness and meaningfulness of critical data.  Using asset management terms, it facilitates an organization’s ability to operate, monitor, maintain, upgrade and dispose of their information assets.  Let's take a closer look at its three suites:  Integration, Data Quality and Master Data.

Integration Suite:  A unified toolset that ensures rapid access to timely, accurate data across all systems, processes and stakeholders.  Designed to satisfy enterprise-scale, as well as project-oriented and departmental-level integration requirements, it delivers comprehensive integration capabilities that unify diverse and disparate environments and support operational and analytical data and application integration requirements to optimize business processes and real-time decision making.  It provides the operational, monitoring and maintenance processes of information asset management. 

Data Quality Suite:  A comprehensive toolset designed to profile, cleanse, and enrich data to drive better planning and decision making by ensuring the consistency, accuracy, and completeness of enterprise information.  It provides the monitoring, maintenance, upgrading and disposal processes of information asset management in the context of data quality management down to the atomic data level.  Monitoring in this case means profiling the data via manual or automated methods as well as monitoring the performance of data quality rules and incorporating human intervention when required for manual remediation purposes.  Maintenance, upgrading and disposal processes equate to cleansing and enrichment data quality processes.  

Master Data Suite:  A toolset that ensures consistency, uniformity, and accuracy across all critical data assets. It is a scalable multi-domain master data management environment allows organizations to enable effective data governance by rapidly creating and efficiently maintaining a single view of their core entities.  It provides monitoring, maintenance and disposal processes of information asset management for master data assets.  Monitoring in this case translates to the scoring of matched and merged records and is rendered in the form of performance metrics.  Maintenance, upgrading and disposal in the context of MDM means maintaining master data historical instances (optional for some, but a regulatory requirement in healthcare), creating and/or updating the golden record and updating and/or disposing of applicable source data (for operational systems) and destination sources (e.g., Business Intelligence data warehouses and data marts) in the appropriate implementation style(s) (i.e., centralized, registry, coexistence, consolidation).

There are many capabilities that organizations need to be aware of to effectively manage their information assets and are outside the scope of this discussion.  However, there are several in iWay 7 that stand out when considering a holistic and comprehensive IAM solution:
Data quality firewall:  I am continually surprised at the more than interested reaction I get when I discuss iWay’s data quality firewall concepts.  I am not sure if it is due to the uniqueness of the concept or simply the lack of functionality in the marketplace.  iWay 7 provides a real-time data quality firewall that leverages fully customizable business rules to proactively stop bad information from entering systems.  It executes data quality cleansing and enrichment operations in-process (as messages enter the organization) as opposed to post-process batch-based data quality operations.  
Active versus passive governance and Operational and Analytical MDM:  This is about the ability to create and maintain golden—or master—records as data enters the enterprise (real-time) as opposed to after the fact on sets of records.  Many master data management (MDM) initiatives start as an Analytical MDM (AMDM) imperative where the goal is to improve (master) the data for business measurement and analysis (manifested in Business Intelligence reports and analytics).  As an organization’s MDM process matures it will evolve to include more real-time or Operational MDM (OMDM).  One must be cognizant of what is required by the organization short and long term and the IAM tools at their disposal.  iWay 7’s integrated toolset facilitates the ability to implement AMDM and OMDM as well as active versus passive governance. 
360 Viewer:  There appears to be a dearth in the industry for business user tools that facilitate collaboration on master data and their historical instances.  iWay 7’s 360 Viewer offers a complete, web-based and role-based view of golden records mastered across all functional domains.  It provides information asset stakeholders, participants and contributors—business managers and administrators as well as data stewards, data supervisors, and system administrators—with visibility into mastered data assets along with their historical instances.  Most importantly, it expedites the remediation process by facilitating collaboration across subject matter experts, data contributors and data owners.  
Data Steward Portal:  Part of the Data Quality Suite this is a web-based foundation for data governance that allows business users and data stewards to manage configurable process-based remediation workflows to correct and resolve data quality issues quickly and efficiently.  Notifications can be sent to mobile devices when human intervention is required. With ease of access for business users, data quality issues can be monitored, managed, resolved, and tracked in real time, with an end-to-end audit trail of all changes. The workflow orchestrator for remediation processes can be customized, and optionally allows remediation edits to be reincorporated back to the source or destination. 
Integration, mastering and data quality operations exposed as services:  Many of the aforementioned IAM capabilities are available as services that are implemented within the iWay 7 IAMP toolset.  Although tightly integrated the availability of these operations as web services adds to the flexibility an organization has in implementing and customizing a comprehensive an holistic information asset management solution within their environment.  
In this blog I reviewed some execution challenge trends in information management and I explored the idea of treating data as an asset and managing it using traditional asset management approaches.  In future blogs on the topic of Information Asset Management, I will explore how to build the business case for IAM projects, how to derive the value of information assets and how to identify the return on investment for IAM projects.  
IDG Survey Finds Organizations Failing to Maximize Information Capital, June 6, 2013,
Information Builders Launches iWay 7 Information Asset Management Platform, June 4, 2013