Based in Denver, CO, Agile Ideation collects the thoughts and experiences of Ed Schaefer. His posts explore agile and devops related topics as he works to maximize team effectiveness and minimize waste through continuous learning, coaching and empowering teams.

The Importance of Data Management

Organizations rely on customers, suppliers, employees and service providers, but what they rely on more than anything else is data. Whether you’re talking about a fast food restaurant or a Fortune 500 company, data - sales numbers to customer information to employee payroll – is the most important aspect of any organization. As a result, good data management is vital for any corporation that wants to be able to thrive. By understanding how data interrelates, organizations are better able to use that data for decision making purposes. Technological challenges and managerial issues should be looked at as hurdles to overcome as customer expectations and employee experiences can be severely damaged as a result of poor data management, while proper organization can enhance the experience for everyone involved.

 

Poor data management leads to terrible customer experiences, unhappy employees and challenges that never should have happened in the first place. I have experienced this first hand. Every day at work I open 13 different applications so I can assist clients. If the only data needed is client data I will need to use up to seven of those systems to do so – two of which are for document retrieval, the rest account information. The system is difficult to learn, many employees do not know where to find features or that they even exist. Not only does this cause employee frustration but lengthens the amount of time it takes to help a client which increases costs and creates a poor experience as the next client waits to be connected to a representative. There are three separate applications where notes can be added, but notes are not consolidated or easily accessible. As a result a client returns a call, the note cannot be found and a new representative has to start from the beginning – once again incurring expenses and causing a poor client (and rep) experience. Multiple data vendors are used for the same data in different locations leading to confused, unhappy clients calling for clarification – thus expenses and bad experiences.

 

When examining the technical aspects and managerial issues as presented by Brown, DeHayes, Hoffer, Margin and Perkins it is clear there are many challenges that must be overcome to resolve these issues. Beginning with technical aspects, the company has an established data model, but has an overly complicated methodology that is poorly understood and explained and notation is department independent. It is absolutely unclear what method of data modeling has been used as all systems seem to have been developed at separate times by separate entities. The same data is maintained in multiple systems, but the databases do not connect. Much of this holdover is due to legacy systems that were expensive and time consuming to develop and old enough that data management was barely a concern, but the company is beginning to recognize technical shortcomings and attempting to address them.

 

Managerial issues have a bleaker outlook. Data management is volatile – systems will be unavailable at arbitrary with no explanation and many of the systems have not been updated since the days of DOS. The relationship between data is barely considered. As I previously mentioned data is not collated or consolidated across systems, notes and messages are difficult to find and inconsistencies flourish. No one is pushing for new programs because the legacy application software is so intertwined with everything else it’s nearly impossible to remove. Data is spread across systems and databases requiring long batch processes to attempt to maintain consolidated records. It seems clear that the system needs to be reexamined and though it may be impossible to start completely fresh changes need to be made to reduce inefficiencies, lower costs and attempt to replace legacy systems.

 

When data management is done right, no one should notice that anything is being done at all. Work processes and information flows should be studied and representatives using the system should be consulted so a plan can be made to increase responsiveness to customers. While clients and the majority of representatives may just find the problems an annoyance or inconvenience, when data management is kept in mind it is clear how important it is to the sustainability of a business.

Organizational Mapping and Implementation of Enterprise Resource Planning

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