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Using Analytics to Improve Business Results

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There are challenges that can be encountered in any organization when analyzing data for decision-making.  Applying the optimal solution to each analytical challenge can improve business outcomes

Leaders in many corporations have struggled with effectively leveraging analytics to improve their business and bottom line.  Often, in those same organizations the concepts of data warehousing and analytics have been maligned.  These same organizations may have information-starved managers and leaders who are dealing with inefficiencies, high customer demands, and pressures from executives to drive down costs. 

Demands for access to information are at an all-time high.  Many organizations know that they now have the challenge of getting data to their internal and external communities, to provide many of the information benefits that data capture promises, but cannot deliver.  After spending a significant amount of money on those efforts, most organizations are displeased with their inability to fulfill their demands for information.  Some of these common demands include:

  • Pressure to produce quality reporting to satisfy consumer and external requests
  • Business pressures – increasing costs of operation, decreasing pool of qualified personnel, increased competition for customers, other market pressures, etc.…
  • Operational management – leveraging information to properly plan, manage, and grow all operational aspects of the business.  This may be done without access to factual statistics unless they are manually gathered and consolidated (hiring people to pull data together).
  • Broad need for access to significant amounts of information for research purposes.  Currently many individuals are hired to gather and pull data – due to inefficiencies in data management and architecture, business research has become an exercise in finding data and hiring staff  to find that data and curate it for their own purposes (every time this is done it satisfies one need and is repeated over and over).
  • ERP/ CRM / EMR adoption statistics – It is one thing to implement a centralized application, it is quite another to know that it is being used properly.  In addition, questions remain about the potential value of the information captured having the desired impact that caused the ERP / CRM / EMR implementation.

There is an old saying “when you are a hammer, everything is a nail.”  While in the right context this is good for a laugh, it exposes some of the challenges of data management and analytics.

Drivers

To understand why the combination of information demands and pressures combined with minimal results of successful analytics efforts continually frustrate leadership with a lack of value or return on their investment, examine the root of the situation and the results.  Some of the pressures to produce data / information drive leadership to pressure for quick solutions or answers.  Executive leadership has challenges and demands that require them to respond to internal and external pressures quickly and firmly.  If the resources responsible for designing and building solutions were more aligned with the demands on these executives, they would be better positioned to come up with appropriate long term solutions that were delivered with incremental, measurable value.

Here are a few examples of current solution drivers:

  1. Needs– It is important to identify the individual requirements of high profile business leaders.  Key leaders who have specific needs typically leverage their position to highlight urgency, not for the need, but for a solution.  If the needs were truly separated from the solution, it would allow the business and IT leaders to see all needs and devise solutions that would satisfy many requirements with targeted solutions.
  2. Trust– Lack of good solution examples often has non-IT resources designing solutions, figuring that if IT cannot build solutions that satisfy all their needs, they can certainly tell IT exactly what to build themselves.  As a result, IT becomes the coding department.  The organization ignores that intelligible system design is not something one invents, but it is a skill that is acquired through years of IT experience and education.
  3. External Pressures – There are several external collaboration or reporting pressures that many organizations are forced to address.  Any organization that has an external relationship that requires data sharing must be prepared with data management standards for sharing data (and not sharing when necessary).
  4. Vendors – Vendors that pitch technology tools that will solve problems.  The desire of many hardware or software vendors is to drive sales by diminishing any problem solely to the application of tools.  Many companies will make an expensive mistake in implementing what appears to be a silver bullet.

Quicksand

As a result, organizations will continue to focus their resources on projects that have minimal impact on their business and continue to build on their frustration of realizing little real value.  The repetitive process contributes to a downward spiral, and invariably organizations turn to fighting the fires for who screams the loudest or has the most powerful voice.

Unfortunately, many organizations see this issue as a lack of technical skills and try to change the technical tools and resources without addressing the real drivers with sound business and technical approaches.  Many reach out to extremely large software vendors that offer the promise of solving all of their IT problems. 

Some real drivers for systems priorities and designs: 

  1. Leverage data and information to support corporate mission, goals, and strategies
  2. Fiscal responsibility of all systems, between business and IT.  Do more with less – intelligibly designed systems will reduce hardware and software costs significantly
  3. Increase value and drive down costs through judicious use of technologies, effectively educated resources, and properly staffed teams
  4. Manage corporate operations effectively and with attention to all areas of data management

Proven Approach to Improvement

Effective organizations define a proven approach and direction that WILL lead to success in the short term and long term.  The reason most organizations forego a long term strategy is their immediate demands cause them to address the urgent issues, not the most important challenges.  They fail to recognize the need to take a proven approach and leverage success in the short term and long term.  Doing so requires a change in their approach and a willingness to leverage expertise that goes against a “fix it now” culture that has been ingrained in many organizations. 

Some key areas to address include:

  • Implementing a combined business and IT oversight of all IT efforts.  IT must report formal status on all projects and not miss dates, especially without good explanations.  Is this possible?  Absolutely, with adequate analysis and planning, it is an expectation every executive should have of their IT leaders.
  • Having a plan – a roadmap for the future.  The organizations that claim to have this usually have a diagram of tools, technologies, and infrastructure.  However, this plan is a strategy for data and its alignment with business needs and analysis in a planned, comprehensive manner.  An implemented data strategy will allow infrastructure costs to be reduced and managed against business requirements.
  • Having a data management program – Data should be an important IT asset, yet hardware is the primary focus for most organizations.
  • Implementing Data Governance – having business oversight of the processes and data helps ensure that the organization understands the value of data and information and the connections found across the enterprise for data and its usage. Data Governance is the cornerstone of an effective initiative to manage data and information effectively.

 Conclusion

Most organizations would deny they need to reinvent the way IT and the business operate.  However, most business challenges continue to mount while costs/budgets skyrocket and business leaders become more frustrated with the lack of value they perceive in the information they have available.  There is a better way, and successful organizations have found it. 

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Bruce D. Johnson

Bruce D. Johnson is an experienced IT consultant focused on data / application architecture, and IT management, mostly relating to Data Warehousing. His work spans the industries of healthcare, finance, travel, transportation, and retailing. Bruce has successfully engaged business leadership in understanding the value of enterprise data management and establishing the backing and funding to build enterprise data architecture programs for large organizations. He has taught classes to business and IT resources and speaks at conferences on a variety of data management, data architecture, and data warehousing topics.

© Since 1997 to the present – Enterprise Warehousing Solutions, Inc. (EWSolutions). All Rights Reserved

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