Back in 2010 I wrote an article on Data Management for the Sage Saleslogix community site.  The site changed to Saleslogix community under the hands of Swiftpage and now the portal has moved to be a private community.  I thought it was an appropriate time to repost under our Simplesoft blog to keep the information alive for those who have referenced it or linked to it. 

Nine Practical Strategies for Data Management  

Data quality is one of the core pillars for Customer Relationship Manage­ment (CRM) success. It does not take long to realize when using a CRM tool, like Infor CRM, that the need for data quality management is paramount. The grueling pains of poor data management can range from the costs of inaccurate printing and re­turned mailings to the subtle troubles of us­ers not trusting the data like they should. The effectiveness of customer facing operations (sales, marketing, and support) depends on having clean data. Think of the implications of marketing to customers using inaccurate data and sending them a prospecting letter (maybe you have lived it). The costly mistakes speak for themselves. 

Research studies from the Data Warehous­ing Institute suggest it only takes about four and a half years for a database to become ninety-eight percent “bad” if data is not man­aged properly, and regularly. On-going T.L.C (Tender Loving Care) will keep the data constant, but changes that occur with records when customers move, marry, divorce, pass away, go out of business, etc., render them obsolete quickly. Users can become skeptical of the data and resort to deploying their own data repositories. Of course, no one plans to use a tool where the data is outdated and not trusted. So, what can an Infor CRM Administrator or Data Steward do to ensure high quality data?  

Strategies for Data Success  

First, establish the processes and tools to prevent inaccuracies.  

Tip: We have found it helpful to develop a document to define user policies and pro­cedures to establish data standards. Define the policies and procedures for managing change early before the system is deployed and communicate those policies to the end users of the system.  

Clean up existing data inaccuracies (if they exist).  

Our customers find it helpful to use a data survey checklist that helps you think about areas of review. 

Review critical data suppliers and entry points. Insist they provide accurate and current data. 

Especially important before importing data with G.I.G.O. (Garbage In, Garbage Out) in mind. 

Build in data accuracy by enforcing re­quired fields and pick lists. Also, use script­ing to enforce business rules whenever possible. 

Tip: Focus on the most important data first, especially for mailing and reporting. I am sure you have observed a state field with OH, Oh., OH., Ohio, OH-IO and other variations. This scenario can be easily prevented.  

Don’t be seduced by the promise of CRM data cleanup tools without a plan for pre­vention, too. There is no substitute for pre­venting errors at the source. 

Tip: You can enforce both clean up and pre­vention at the same time with QGate’s Pari­bus and PowerEntry utility.  

Select specific software tools to solve spe­cific problems rather than general tools for general problems. The Groups features is an easy-to-use built-in tool in Infor CRM. 

Tip: There are many built in tools and meth­ods to manage data so spend the time or work with your channel partner to learn them all.  

Assign a data steward (or trustee) to be responsible for each data element (Con­tacts, Accounts, pricing information, etc.). 

Typically, this role is the business process administrator; whereas the power user role manages the data and both should have strong execu­tive support. 

Establish a process through which the accuracy and quality of data in all sys­tems can be reviewed and assured on a reoccurring basis. Schedule regular tasks to review and clean up data, such as on a weekly or monthly basis. The data stew­ard/administrator should be held ac­countable for completing those tasks. 

In the case of multiple systems using the same data, identify a system of “official record”. That is, a system in which data will originate and “feed” other systems that re­quire the data (accounting and sales inte­gration come to mind). 

Identify Data Quality Issues in Infor CRM  

Infor CRM administrators can create ad­ministrative Account / Contact / Opportunity Groups for various data segmentation such as missing required fields, duplication of data, and data that needs to be reviewed because the records have not been updated or reviewed, within a specified period of time, such as a six months or a year, for example. 

Infor CRM also includes tools to mass ‘swap’ the content of fields, change values, and merge records. As a standard procedure, first complete the actions in a test environment to verify the steps and desired results. After veri­fying, perform the steps in your production sys­tem. 

Tip: Always backup a production database be­fore making mass changes and complete during non-working hours. You also may want to use the built in “user fields” to mark which records are changing, this will simplify an otherwise irrevers­ible change and provide a temporary audit.  

Cleaning Data Using Infor CRM 

There are some basic built-in tools for managing and de-duplicating data in Infor CRM, which can be supplemented with and enhanced by third-party tools, such as QGate’s Paribus and several other data management solutions. 

Nevertheless, a data management strategy, as outlined above, is required. Some of the data de-duplication tools available in Infor CRM include: 

Administrative Groups – groups can be created to help administrators identify and cleanup data issues such as missing data or duplicate data 

Check for Duplicates Wiz­ard – an automated method of finding and eliminating data duplicates 

Merging Records Manually – a simple method of merging two or more records from the Group view 

Increasing the reliability of CRM data within an organization is priceless. Avoiding costly mis­takes such as targeting a current customer as a new prospect is critical.  Now is a great time to review and clean your Infor CRM data. Remember to review and clean existing data, clean the data being entered, and prevent the current data from becoming “stale”. Managing data quality is an ever moving target and must be a part of your overall system management strategy. 

Data helps solve problems.  — Anne Wojcicki 

If you would like to discuss upgrading your system, or to see a free demonstration, please contact Simplesoft Solutions. 

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