Improving Enterprise Master Data Management Capabilities – A strategic differentiator

Most software systems in an organization have list of data that are shared and consumed by several of the applications that make up the system. For example, a typical ERP application will have a customer master, material master, vendor master and account masters. This master data is critical asset of an organization and need to manage its lifecycle well. If you have a bad data, then organizations end up making bad decisions faster.

Some of the issues organizations faces are:

- Manual data processes which leads to duplication of efforts.

- Local data management processes, standards and rules are inconsistent leading to poor client satisfaction

- Lag in decision making due to data integrity issues

- High data maintenance costs due to inadequate support to identify the sources of truth and duplicates

- Lack of standardized master data, industry best practices – debilitating organizations from deriving maximum benefit out of the system

- Regulatory compliance and audit challenges due to poor data quality


An organization’s MDM maturity level can be arrived by understanding and benchmarking its overall Enterprise Master Data management landscape with the activities identified across each maturity level as indicated below:

Level	Activities
Level 0 (Initial)	No strategic Objective, data strategy
	System specific scope
	No sharing of master data
	Roles & Responsibility inconsistently defined
	Limited integration
Level 1 (Partially Managed)	Tactical MDM implementation with limited scope
	Limited entities defined
	Key processes defined
	Limited sharing between key applications
Level 2 (Defined)	Strategic Objectives and data Strategy defined
	Data standards are agreed to and shared within organization
	All key entities and limited Data stewardship capabilities
	Service levels defined for monitoring
Level 3 (Quantitatively Managed)	Enterprise wide scope to cover all business critical master  data
	Enterprise solution for single source of truth
	KPI’s established to align business goals
	Real time master data harmonization
	Enterprise data Stewardship
Level 4 (Optimizing)	MDM integrated with BI, SOA and BPM
	Evaluation of data governance policies for continuous improvement
	Periodic independent audit to ensure compliance
	Data Stewardships are evaluated

It has been said that MDM is a journey; to take that journey from tactical to strategic level; organizations need to take a stock using the above maturity matrix, set future goals and measure progress towards target to achieve highest level of maturity and continuous improvement.

Cloud- Based Asset Management

The software as a service (SaaS) model as a part of the Web 2.0 revolution is considered very attractive, viable and cost effective solution for delivery of business applications for small and medium sized business. In last couple of years, I have come across many RFPs and enquiries even from large companies who wanted to evaluate and adopt cloud based model for Enterprise asset management. Today quite a few large companies have already adopted cloud for their business critical applications including EAM

The enterprise space is undergoing transformative reinvention with radical shift in new offerings and proliferation of cloud based enterprise class applications. The proliferation of “nimble” solutions, which are relatively easier to implement, boast of a faster time to market and significant reduction in TCO, have really caught the attention of business and IT alike in enterprise accounts and cloud clearly offers most of these benefits.

Having seen the trend and benefits, let’s look at the challenges from asset management perspective.

• Data security. Customers (especially asset intensive organizations like utilities, oil and gas etc) want to use cloud solution but still they want data to be on- premise due to security, country specific regulatory requirements etc.

• The quantity and complexity of interfaces that an EAM system would need to connect to including asset instrumentation, and the requirements that the reports and analysis that result be very specific to the individual company and its individual industry.

• Performance and availability over WAN in distributed and remote environments with asset management users having limited time and exposure to software solutions.

For many industries where asset data sensitivity in not that critical, cloud based asset management is the best choice. Even with existing massive investments in infrastructure, software licenses, organizations are looking to switch to cloud option completely managed by service providers.

Also asset intensive organizations are looking for hybrid cloud model like surround cloud application for service management, field force management, approval workflows etc leaving in-premise EAM application to mainly power users.

So in coming days, more and more businesses would look for opportunities to migrate existing enterprise applications to cloud based asset management software