Stop Poor Data from Throwing your ERP Transformation Off-Course

Data disparity has reached concerning levels with evolving technology and lack of training, time, and investment in users. Whether you are preparing for an ERP application upgrade or a complete ERP transformation, it is just as essential to ensure your existing legacy data’s validity as it is to choose the right solution for your enterprise needs. Missing and inaccurate data can prevent your organization from leveraging your chosen solution’s capabilities, and bad data could perpetuate challenges and increase costs associated with the current application. Many companies simply do not have the resources or expertise to ensure data quality.

Data Quality: The Key to Building a Modern and Competitive Enterprise

Data issues are the primary reason business initiatives fail to deliver value. Poor data quality is one of the top 3 risk factors of any enterprise project. The data effort’s allegorical project cost can be 20 – 40% of an ERP implementation’s attributed to, which can be broken down into data quality issues, data conversion effort, and data integration.

If you compare an organization’s enterprise applications to a home, then data quality is akin to dirty floors and counters or items that have been placed in areas where they do not belong. It is crucial to meet your data challenges head-on; ignoring the problem today will undoubtedly cost your organization time and money at a future date. Just as a home should be cleaned regularly, data cleansing also needs to be consistently addressed. A data assessment or health check can get your organization on the road to reliable and quality data.
 

 

Learn Why Data Quality is Paramount Through Our Customer Case Studies

Many of your industry peers have taken steps to address data quality issues. Let’s dive into a few case studies and see what we can learn from their journeys:

1. A company that provides industrial products and building materials implemented a new ERP to replace discrete legacy systems at multiple sites. When business users were asked to validate data before the conversion, they did not know precisely what to validate. The data was already live in their legacy systems and had been signed off on. What was the problem with their current data? Conversion and user testing were successful, as was the project cutover. The project was considered a success; however, the same end-users found that the master data had similar challenges as the legacy system after go-live. They wrongly assumed that the IT team had cleansed the data, and the IT team believed that the business users gave them clean data to load in their new solution. Some of the challenges encountered included duplicate customer header records and sites labeled with slightly different names and addresses. More specifically, there were intentionally duplicated sites to split sales rep commissions caused by a system limitation. Had the data been consolidated before loading it into the new ERP application, the solution’s capabilities could have been leveraged to avoid invalid addresses, displaced address fields, and free form notes.
2. A company known for its building technologies sought to evaluate its Oracle EBS data to check if any issues exist that would be a challenge for implementing Oracle Cloud Planning. They also wanted to get a head start mapping their existing data elements to the format required for Oracle Cloud Planning’s File-Based Data Import (FBDI) templates but did not have the expertise and resources to address this internally.
3. A uniform rental company using Oracle EBS PIM and Financial Modules wanted to implement Oracle Inventory as a replacement for its existing (non-Oracle) inventory applications. They are not aware of any current challenges with the PIM design but reached out to our team for a second opinion as part of their global design efforts.

In these case study examples, performing an independent, objective health check of enterprise data would reduce risk and save money for these companies. A health check would further prioritize the challenges that needed to be addressed and estimate the cost and effort necessary for resolving them. Inspirage’s Enterprise Data Readiness Assessment (EDRA) framework is a comprehensive assessment developed to quantify an organization’s maturity as it relates to managing enterprise data. These assessments are recommended before solution migrations but can also add significant value during a steady state.

Avoid Common Pitfalls in ERP Transformations and Implementations

If you are considering an Enterprise Data Readiness Assessment, there are a handful of points to consider before you embark. First, Inspirage EDRA works with a sample set of data. Because there may be additional undetected issues outside the sample data set, Inspirage Data as a Service (DaaS) is recommended to build on the assessment and drive data quality as a project track. Next, Inspirage EDRA assesses the data and detects issues but does not include the resolution of the problems. Inspirage DaaS prompts the correction of data issues. To accurately plan project migrations, business involvement and input is needed to address data issues.

Once your organization is ready to begin an Enterprise Data Readiness Assessment, here is what to expect:

1. Key users and process owners are interviewed initially with a questionnaire template, followed by questions about customer-specific business processes and data maintenance flows. Examples of past business data challenges are gathered.
2. IT teams are interviewed to understand the current data architecture, including flows and integrations. Sample data from source systems in the scope are collected. Users are probed for known IT issues.
3. Sample data sets are studied to assess data quality. This can be different for each use case but typically includes profiling against standard metrics to:
   • Identify missing, redundant, or inconsistent data elements or garbage characters.
   • Compare data across systems to pinpoint fallouts in the integration.
   • Perform specific data set validations.
   • Review initial mapping of source data to target system data conversion templates. Or interface tables to look for missing elements and perform a duplicate detection exercise for the master data (if needed, a third-party tool may be utilized for online address validation).
4. Business leadership and data owners are consulted to understand the existing data governance process, discuss challenges and goals, identify the systems of record for different data sets, and recommend a data governance framework to meet challenges and goals.

Inspirage has the answers to your questions

We can all agree that for business decisions to be timely and effective, they must be based on discoverable, usable, and current data. At Inspirage, we know all too well the importance of accurate, consistent, and standardized data. Whether you are considering an application upgrade or a total ERP cloud transformation, we have you covered. Contact us today and let Inspirage’s Enterprise Data Readiness Assessment (EDRA) framework identify your data’s strengths and weaknesses. Our team will take it one step forward and put a roadmap in place to ensure you are optimizing your ERP solution’s capabilities and delivering quality business-ready data that is current, meaningful, and trusted.