Articles & case studies

"Gonna' throw some data stewards at it!"

I'm not exactly sure what that means, but that was a response I received regarding a $3B company's MDM plan.  While data stewards are not the end all/be all solution to a data management plan, I applaud that the organization has recognized data troubles that they currently face.  It's a big initial step in thinking about the value that data is bringing to their organization.  It's a recognition of how poor data standards has led to costly headaches as they modernize their application and data landscape.   It is also the start of a cultural shift that I hope continues to evolve.

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How does one start that cultural shift around data without having to live through that pain element?

There isn't an easy answer to the question, but there are organizations of all sizes and stripes don't have defined data governance and data management functions.   They let the applications do what they do, the people use them how they use them, and the data end up how it ends up.  

If your organization is lacking that cultural importance around data and recognizing its value as an asset, here are a few ideas that may spark conversations and potential a culture shift. If your company is thinking about implementing a new business application in the next 1 to 3 years, it's a golden opportunity for instituting data governance operations.

Inform your company that data is the most cited reason for implementation delay, cost overrun, and project pain.  Data has a high potential to increase implementation costs by millions. This is backed by Gartner, Forrester, or anyone that has lived through a major implementation.

Next , I would talk through how the firm can mitigate that risk and ease future pain by starting to implement data quality and data standards today.  The clean-up work will need to be done regardless.  By having that head start, you can potentially light a spark that builds out the policies, mechanisms, and attitudes about the value of data across the organization.  

Not only will you mitigate risks and lower costs of the implementation, you will improve current business operations dramatically.  I read a report by McKinsey that identified that organizations spend 30% of time doing extra work because of data issues and data management inefficiencies.

Additionally, ask how the organization going to prevent data from getting as bad as it today post go-live.  Depending on the type of data, it will degrade between 4 and 30% each year.

In 5 years, best case scenario the data will be ~80% as clean as it needs to be without clear management in place. That data degradation will have a similar costly impact as the bad data that exists today and will start to negate the savings and process improvements that the new application is suppose to yield.

If your company is bumping along on their current systems with no plans to change course, guess what?  It also a golden time to spark the conversation.

Start to identify and talk through how much data quality and inefficiencies that the team has to fight through on a daily basis. Identify additional value and insights that the organization can gain if it was properly managed.   That 30% stat from McKinsey is valid here. Start to be that data champion and start small on one aspect of the data landscape.  Supplier, customer, or address data might be easy lift with high impact.

On one project, we were told by the client that cleansing up and de-duplicating their supplier data would save them approximately 30% on their raw material costs.  Holy Buckets! This was for Fortune 500 organization, so for a few months of work, we'd conservatively be able to save this organization millions of dollars each year.

Regarding the organization at the beginning of the piece that are throwing some data stewards at their data, we'll see how it plays out over the next months.   They're open to learning more about data management and data governance and that open mind is incredible and without a doubt will lead to great success over the next years.

On the For Love of Team podcast with Winston Faircloth, Premier International (now Definian) CEO Craig Wood provides a forthright account of Premier International's (now Definian) history, employee culture, overarching value system, and approach when handling unforeseen circumstances. The listener gets a unique lens into the tools used by company leadership that have contributed to the organization’s growth and award-winning culture, such as the tenets of The Definian Way, radical candor, gratitude, and self-awareness.

Aligning with Premier International's (now Definian) foundation and guiding principles, Craig celebrates Premier International's (now Definian) founders for creating the company with such an intentional ethical groundwork that has solidified the precedent for today’s simultaneously employee-first and client-first culture.

Click on the image below to listen to the full podcast interview with Premier International (now Definian) CEO Craig Wood.

One of the world’s largest medical centers aimed to consolidate their ERP systems across hospital branches onto a single, integrated data platform. The purpose was to improve patient care and to be equipped to handle higher patient volume by achieving the following: modernization and optimization of business operations, standardization of new acquisition onboarding, and the enhancement of analytical insight capability. They selected Oracle ERP Cloud as their new technological platform and engaged Definian to support the data conversion efforts. As one of the first healthcare systems to adopt the full Oracle ERP Cloud solution, the client faced many unique challenges; however, Definian’s methodology and Applaud® technology minimized the risk associated with data migration and paved the way for a successful implementation.

Freeing the Hospital to Focus on Validation

The client was initially responsible for loading data into Oracle Cloud, but did not have knowledge of how to execute Oracle loads nor how to perform analysis of the accompanying load logs. Recognizing Definian’s experience in loading data to Oracle Cloud for other large organizations, the client asked Definian to perform data loads in addition to the other data conversion responsibilities. This lifted significant cost from the client, allowing them to focus on data validation and testing in the Oracle Cloud environment.

High Data Volume

Conversion requirements stated that a large volume of historical data needed to be migrated for auditing purposes. Definian worked with the client to outline strategies to best address the large data volumes. From a conversion standpoint, we grouped and aggregated historical data by the month or the year using our Applaud® software, thereby decreasing data volume and easing validation efforts. For production loads, Definian worked with the client to create a schedule that ensured most of their data would be loaded prior to Cutover, allowing more time for urgent tasks closer to go-live. Definian also optimized the load processing times by tweaking Oracle’s standard settings, which improved load efficiency by up to 500%.

Master Data Management

Supplier and customer addresses from the client’s legacy systems were inconsistently formatted and contained user-input errors. Definian’s address standardization process normalized and validated addressed while providing audit trails, ensuring transparency every step of the way.

All master data (Customers, Suppliers, Items, and more) was loaded into Production at least three weeks prior to their corresponding transactional data (Sales Orders, Purchase Orders, Invoices, and more). During this transition period, all changes in the legacy systems also needed to be made in Oracle ERP Cloud. Using Applaud®, Definian developed conversion programs that accounted for both newly created and modified master data to ensure all transactional data would be aligned with existing data in the Oracle Cloud Production environment.

Project Risks and Complexities

Due to the COVID-19 pandemic, we conducted the Cutover data conversions virtually. Definian consultants continued to maintain regular communication with the client and we addressed all data-related issues as they arose.

The client determined that they needed to convert Purchase Order (PO) Receipts, despite recommendations from vendors to avoid this conversion due to validation complexity. Definian took on the challenge and minimized load errors by using Definian’s Oracle Cloud Critical to Quality (CTQ) pre-load validation checks, reporting validation issues before loads took place. Definian also optimized the PO Receipts conversion process by utilizing inheritance riles to pull values from the corresponding Purchase Order, which minimized the risk for mismatching POs/receipts and significantly decreased the volume of load errors.

As a research hospital, the client uses the Oracle Cloud Grants module to manage the finances of research grants and awards. The client’s awards data requirements necessitated significant manual updates/intervention, so they would not be handled with programmatic conversion like other data objects. We instead leveraged our technical support team to develop webservices that efficiently updated award records and ensured that the awards data met the client’s initially specified requirements.

Key Activities

• Identified and documented requirements for converting data to Oracle ERP Cloud.
• Identified, prevented, and resolved problems before they became project issues.
• Facilitated discussions between the business stakeholders, the functional team, and the load team to coordinate requirements and drive data issues to completion before each test cycle and Go Live.
• Quickly adapted to changing data conversion requirements and proactively identified and addressed downstream implications, keeping the project on schedule.
• Harmonized, cleansed, and restructured Supplier data through Definian’s deduplication process; only clean, unique records were converted to Oracle. Standardized and cleansed Customer and Supplier Addresses; additionally provided clear reporting to business stakeholders.
• Definian’s Oracle Cloud Critical to Quality (CTQ) pre-load validation checks identified load errors prior to executing Oracle data loads. This early-stage resolution enabled efficient data loads to fit into the tight Cutover window.
• Utilized robust data profiling and error reporting to assist business stakeholders with data cleansing, data enhancement and data enrichment prior to Go-Live.
• Fully automated all data transformation activities, removing error-prone manual steps from all processes; ensured consistent and predictable output.
• Tracked records throughout the data transformation process to assist with post-project audits.
• Loaded over 18 million data records into Oracle Cloud while meeting cutover deadlines and maintaining high data quality.
• Provided project management services to ensure data migration was completed on-time and within budget.
• Generated reports through Applaud® to aid in validation of finances and to ensure accounting tied out.
• Provided detailed tasks in project plan to ensure every step in cutover was accounted for.
• Developed webservices to efficiently update large volume of awards and projects that otherwise would have required manual updates by the client.

A Project in Jeopardy

UAT is typically considered a dress rehearsal for Go-Live and should result in minimal change requests. But this was not your typical UAT. During the final weeks of the project a major gap in critical-to-customer data was discovered that jeopardized this steel mill’s entire Microsoft Dynamics 365 implementation.

User Acceptance

As the name suggests, a successful UAT depends on the end users accepting the results of the conversion test cycle. To guarantee a successful go-live, each subsequent test cycle includes more end users and experts than the one that preceded it. For this final round of testing, the expert resource on steel certifications discovered that many Customer Specifications were missing and could not be entered manually. This surprise finding altered the course of our Dynamics 365 implementation, and all resources resolved to find a solution.

Customer Specifications

In a nutshell, Customer Specifications (specs) include the chemical, physical, and mechanical properties that customers need displayed on the steel certification when they receive the product. Customer specifications are applied to materials that will eventually find their way into products where failure would be disastrous. For example, if a steel bar does not meet straightness requirements, then hydraulic cylinder applications (as with those on heavy construction equipment) would fail and endanger workers. We have faith in the structural integrity of skyscrapers and the reliability of cars and heavy equipment because manufacturers strive to meet strict industry standards (like ASTM) and additional customer specifications for critical applications.

Commitment to Customers

By meeting customer specifications, the steel mill demonstrates their commitment to customer needs and delivers on a promise to provide the highest quality steel needed for each application. When UAT began, we were already migrating 5,000 such specifications. Weeks after the UAT loads, our client, one of the largest steel manufacturers in the US, informed us that there was something odd with the data.

Piecewise Uncovering of New Information

This had become a recurring theme – a gradual, piecewise uncovering of new information revealing how their heavily customized legacy AS/400 (mainframe) system operates. The client’s homegrown system afforded countless operational benefits over several decades of use but created challenges for today’s implementation. The downside with non-standard systems like this is that data management is incredibly difficult. Executing a successful conversion required Definian’s project management methodology and the technical capability, data profiling, and rapid application development available through Applaud® software.

Enhanced Conversion Program Delivered

The total count of converted Customer Specifications jumped from 5,000 to over 25,000 just weeks before go-live. Given the short timeframe and quick turnaround, our herculean efforts to expand conversion scope were met with praise from both our client and our partners. A combination of end user due-diligence, expert project management, technical consulting, and the Applaud software streamlined development of the Customer Specification conversion program enhancements. We celebrated this victory and continued loads to Dynamics 365 for testing and validation. Little did we know that an even more daunting task awaited us.

Recreating Custom Backend Code

We were told, yet again, that certain specs were missing. This time, even after extensive data spelunking, no information about the specs could be retrieved in the presumed Customer Product Master table or any other master data tables in the mainframe database. We were at an impasse – how could customer specs exist while no information about them is present in the database? The client revealed that they implemented backend COBOL logic in the AS/400 mainframe that dynamically creates specs directly from sales orders. To close this gap Definian was asked to mimic the backend logic and create item-level specs from transactional data. Since this master data did not exist in the mainframe, we needed to dynamically create it through conversion code.

Rising to the Challenge

The challenge of dynamically creating master data from transactions did not discourage us. Because of Definian’s commitment to client success, this challenge could not faze us. It is exactly moments like this where we rise to the occasion and leverage the power of Applaud to make the impossible a reality. Definian’s experience in complex situations like this empowered us to gather the necessary requirements and turn around a new Customer Specs load file in a single weeks' time. The final record count had skyrocketed to roughly 62,000 – an 1100% increase from the UAT record count.

Reflecting on Our Success

This is one of the many stories from this Microsoft Dynamics 365 implementation where Applaud enabled us to make complex conversion changes quickly and keep the project timeline on track. In ambitious projects like this, requirements are expected to evolve over time. But when complex changes are requested late into an implementation, it introduces risk into the conversion process. I credit our success on this implementation to Applaud and its unique ability to rise to even the most complex technical challenges and minimize data migration risk.

A Proudly Home-Grown Solution

Our steel manufacturer client proudly designed their own Supply Chain software solution decades ago. Everything involving requisitioning, manufacturing, and sales was handled in a custom solution they built on mainframe servers. Occasionally, I would stumble upon decades-old comments between lines of COBOL code and be reminded that this is a home-grown, one-of-a-kind system.  For example, a happy anniversary message to my colleague's mom and dad 20 years ago was among the many lines of code I reviewed. These happy notes aside, this legacy database posed serious challenges to the transformation project because of how different it was from the target system, Microsoft Dynamics 365.

The Challenge of Missing Data

We suffered from a total absence of certain master data in the legacy system. Missing data in the system posed challenges to the project and called into question the feasibility of data migration.  To explain how this business could operate without master data, they intentionally built their software solution around transactions. This design allowed steel product to be defined dynamically by customer orders.  Additional specifications for finished products were derived from steel industry standards (ASTM) and physical, chemical, and mechanical properties.  The programmers of this custom mainframe manufacturing software recognized that they could carry out business without maintaining a Product Master!  Creatively, the legacy solution used attributes on work orders and sales orders to define the finished product.

Likewise, there was no master data for Formula, Routes, and Operations – these functional areas document the raw material and the processing steps needed to manufacture finished product for customer orders. The cold drawing, stress relieving, turning, grinding, and other cold finishing steps were driven by the deeply knowledgeable foremen on the plant floor and scheduled accordingly.  Effectively, there was no 'single source of truth' for several data objects that were needed in Dynamics 365.

Developing a Product Master from Transactional Data

Before we could go live in Dynamics 365, we first needed to create a Product Master.  Our conversion program considered 2 years’ worth of sales orders, work orders, and purchase orders. Dozens of fields across these tables were used to derive physical and chemical attributes of the product. After extensive research and data profiling, we grouped transactions on matching attribute fields and could confidently define a Product Master for each distinct combination or attributes.  95,000 sales orders, work orders, and purchase orders boiled down to 5,000 distinct products successfully converted to Dynamics 365.

Developing Formulas and Routes from Transactional Data

To standardize manufacturing processes, we were also tasked with creating master Formula and Route data for Dynamics 365.  Surprisingly, most of the metalworking instructions we needed for conversion were non-existent in the system.  We found that only a few weeks' worth of scheduling data was retained at any given time.  To overcome this gap, the business restored 2 years' worth of scheduling data from tape backups, and we used these historical backups to extrapolate the Formula, Route, and Operations.  In addition to historical scheduling data, we worked with manufacturing experts to understand undocumented complexities in their manufacturing process. For example, certain steps needed to be structured inline (like when steel passed directly from a turning machine to a grinding machine) and others needed to be discretely broken out for capacity planning.  Also, certain operations were structured as alternates to give the buisness greater flexibility in the manufacturing process.  As a result, the business now has a source of truth for the plant floor that does not rely on tribal knowledge.

A Brilliant Legacy System Unraveled

Reflecting on the experience, I recognize that the legacy database and software was the result of over 20 years of ongoing development by loyal, lifelong employees.   The clever and unconventional software this group created contributed to the cold finishing for millions of pounds of steel.  Very likely, I have driven in a car, or been in a skyscraper, or flew in an airplane made with steel that at some time was a data point in this AS/400 mainframe server. I am humbled to have been called to help this business maintain their leadership position in the global supply chain.  Together we unraveled this steel mill’s  one-of-a-kind solution and migrated it onto a system that will carry the business forward for the next 20 years

Client:  $17B Privately Held Diversified Automotive Company

After implementing Workday HR solution, our client encountered difficulties in effectively tracking the usage of Workday reports and managing inbound/outbound HR-related datasets. Consequently, there was little insight into user adoption, poor visibility into potential data misuse, and a continued lack of data oversight. To address these issues, our team embarked on a mission to streamline their data management processes and enhance data governance.

Assess and Improve Data Governance Operations:  Definian's Data Governance-in-a-Box approach assessed current data governance processes, operational model, and requirements.  The assessment created a roadmap to quickly meet the immediate needs and set the groundwork to more easily incorporate future requirements.

Integrated Workday, Collibra, and Purview Metadata: Leveraging Definian's MetaMesh technology, we designed and integrated the metadata across Workday, Collibra, and Purview. This enabled the unified management of Tableau reports, Workday reports, diverse datasets, and other data products across the enterprise.  Driving clarity and trust within our Client's data

Workflow Design and Implementation: Our team designed and implemented robust workflows aimed at governing the report certification process. These workflows were pivotal in ensuring that data shared both internally and externally adhered to stringent data-sharing agreements.

One of the largest technical hurdles that we worked to overcome was how Workday limited the extraction of metadata necessary to meet our Client’s requirements.  To overcome those constraints, we strategically extended the functionality of native Workday reporting. This extension enabled MetaMesh  to extract the essential metadata required for effective tracking and governance of their reports and datasets.

Through integrating Collibra, Workday, and Purview, designing governance workflows, and innovatively extending the capabilities of Workday reporting, we were able to build clarity and trust around the HR reporting functions for our Client. Our solution not only facilitated efficient tracking but also bolstered their data governance framework, ensuring adherence to regulations and optimizing data utilization.

This initiative signifies our commitment to crafting tailored solutions that overcome system limitations and propel organizations towards effective data governance and management. At every step, we remain dedicated to empowering businesses to harness the full potential of their data assets.

Cloud implementations continue rising in popularity and are projected to make on-premise database-driven business solutions obsolete. This trend has been accelerated by the current pandemic and its global impact. Before COVID-19, experts projected the worldwide public cloud services market would jump by 17% this year [2020], reaching $266.4 million. At no other point in history has there been such a need for the instant availability of IT resources and remote collaboration. In response to this global pandemic, over twice as many IT leaders are planning to accelerate their cloud adoption plans than those that are planning to put them on hold. No matter what you or your organization chooses, it is important to not make this decision lightly.

While moving to the cloud has its obvious benefits and can be a very cost-efficient solution, it can also spiral out of control without careful planning and a data-driven approach. Cloud computing reduces or eliminates the need to purchase equipment and build-out and operate data centers. This presents significant savings on hardware, facilities, utilities, and other expenses required for on-premise computing. As an additional incentive, some cloud computing programs and applications, ranging from ERP and CRM solutions, use a subscription-based model. This allows businesses to scale up or down according to their needs and budget. It also eliminates the need for major upfront capital expenditures.

In stark contrast to the benefits and promised cost reductions when moving to the cloud are the risks and costs associated with a delayed, over budget, or unsuccessful implementation. According to Garter, “83% of all data migration projects either fail outright or cause significant cost overruns and/or implementation delays”. In this case, getting your data loaded into the cloud is only half the picture; the data also needs to be correct, both literally and for the intended business purpose. You can find more about how data migration can fail and the downstream consequences of that failure.

One of the most significant risks in any implementation is data. Data migration often gets underestimated because most think of it as “moving data from point A to point B”, but it is much more complicated. Gartner has recognized the risk inherent to data migration. “Analysis of data migration projects over the years has shown that they meet with mixed results. While mission-critical to the success of the business initiatives they are meant to facilitate, lack of planning structure and attention to risks causes many data migration efforts to fail.” Poorly understood/documented legacy data, dirty data, and constant requirement changes are only some of the reasons migrations often fail.

Lack of preparation is often the leading cause of delayed and over budget projects. No matter the target system, the first part of any successful migration/implementation is a data assessment. Definian’s Enterprise Data Modernization is a short, focused effort that helps organizations prepare for their upcoming initiatives. The list below can be used as a template of questions that must be asked and answered as part of a data assessment effort.

Identify

• Analyze the relevant data across your application landscape
• Generate detailed data statistics and facts for every data element in every relevant legacy table/file
• Report invalid data scenarios
• Summarize unique data patterns in key data elements
• Identify additional data-related anomalies

Assess

• Understand redundant data within an individual application and across multiple disparate applications
• Review and quantify missing, erroneous, and inconsistent data
• Gather metrics summarizing identified data errors
• Compare legacy data against data governance standards

Prepare

• Review detailed findings with the project team and issue recommendations
• Define a data quality strategy that outlines cleansing recommendations for each distinct error/warning
• Providence guidance regarding historical data
• Brief project leadership regarding potential project risks

The only way to plan effectively and create accurate business requirements is to base them on data facts and not assumptions. These facts come from a through data assessment effort. Research from IDG found that 41% of IT directors delayed or abandoned some of their 2019 IT modernization initiatives, often due to competing priorities or lack of a clear strategy.  A current client, implementing Oracle, was able to meet their originally planned System Integration Testing (SIT) cycle deadlines and conversion metrics, despite not leaving enough time between the initial 3 test cycles to address the complex, dirty, and heavily customized legacy data. The project suffered the heavy additional cost of overtime work for several months. The additional cost would have been unnecessary if a data assessment was performed before the creation of the project timeline because the complexity of the legacy data would have been uncovered and the milestones adjusted accordingly. Other implementation efforts are not so lucky; for example Target Canada. Starting with and committing to a data-driven methodology alongside industry experts, your organization is on the right path to successful cloud implementations and systems for years to come.

If you want to ensure your cloud implementation is a success, have questions, or just want to discuss cloud migration, feel free to contact us.

Tableau Catalog is a feature within Tableau that provides a comprehensive and unified view of your organization's data assets. It helps users discover and understand the data available to them, promoting better data governance and collaboration. Here are some key aspects of Tableau Catalog:

1. Metadata Management: Tableau Catalog allows you to capture metadata about your data sources, such as data definitions, lineage, and usage information. This metadata is crucial for understanding the context and reliability of the data.
2. Data Discovery: Users can easily search and discover relevant data sources within the organization. This promotes self-service analytics and reduces the time spent on searching for the right data.
3. Impact Analysis: Tableau Catalog provides impact analysis capabilities, allowing users to understand how changes to a particular data source may affect downstream reports, dashboards, or analyses.
4. Data Lineage: Understanding the lineage of data is essential for ensuring data quality and making informed decisions. Tableau Catalog visually represents the flow of data from its source to its usage, helping users trace the origin of the data.
5. Usage Metrics: It provides insights into how frequently data sources are used, which can help organizations optimize their data infrastructure based on actual usage patterns.
6. Collaboration: Users can add comments and annotations to data sources, fostering collaboration and knowledge-sharing among team members.
7. Security and Governance: Tableau Catalog supports data governance by allowing administrators to define and enforce data security policies. This ensures that sensitive data is accessed only by authorized users.
8. Integration with Tableau Server and Tableau Online: Tableau Catalog is integrated with Tableau Server and Tableau Online, providing a seamless experience for users working within the Tableau ecosystem.

Tableau Catalog integrates features like lineage and impact analysis, data discovery, data quality warnings, and search into Tableau applications (Figure 1).

Tableau Catalog supports data lineage including databases, tables, flows, workbooks, sheets and owners (Figure 2).

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Tableau Catalog also supports data certification. After executing the certification process by data owners, a data source gets a green check mark on its icon. Certified data sources rank higher in search results and are added to recommended data sources (Figure 3).

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Users can also set Quality Warning messages on data assets such as data sources, databases, flows, and tables. Quality Warnings include Deprecated, Stale Data, Under Maintenance, and Sensitive data (Figure 4).

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Overall, Tableau Catalog combined with Tableau Prep Conductor forms part of Tableau Data Management, which is fit-for-purpose for Tableau customers.

An ounce of prevention is worth a pound of cure. This is true in terms of Grandma logic and in the world of data management. Organizations spend millions implementing new ERP and business application solutions but frequently neglect the foresight to plan out master data management after the transformation occurs.

Implementation partners are the best in the world at implementing new solution, whether it be Oracle Cloud, SAP, Workday, D365, or another solution. Implementation partners/consultants know their stuff. I've worked with tons of them. They're whip smart and driven to make the solution work. However, the focus is making the solution work for you and not how to improve and sustain your data's value and cleanliness.

I'm going to spend a minute with you today to outlining how to start a conversation on data quality and data management in a way that can help prevent it from backsliding and costing a fortune to fix in a few years and invigorating the organization's data governance.

A good way to start that conversation is too talk through how data quality is going to maintained on an ongoing basis and that if it is not measured, it will degrade.

• Work with the stakeholders to rough out key data areas that cause significant impact and the impact of that data if it degrades
• Create a rudimentary scorecard by outlining out the acceptable level for each issue
• Collaborate with the team to identify who owns these metrics and if there are mechanisms in place that capture to them

Once the basics of the process and the seed is planted about measuring data quality and how it affects the organization, start to dive deep into the types of data quality issues that affect the business.

Think cross platform data flows and how/where data can go south as it moves across the landscape. After the data conversations has started, there is a lot more that the team can do, but the important part is that everyone is starting to recognize the value and impact data has.

This small mindset shift will pay off dividends in terms of efficiency and insights as the data governance and master data management culture begins to take shape.
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If you have questions about data management, data quality, or data migration, click the chat bubble below. I'd like to learn about them and work with you to figure out solutions.

Implementing Oracle Cloud ERP together with Ivalua can improve your organization’s supplier on-boarding management, sourcing and RFx, contract redlining, and provide an intuitive marketplace for procurement. However, that functionality comes with a significant amount of complexity and dependencies that we experienced while executing the complex data migration process for both Oracle Cloud and Ivalua at one of the nation’s premier hospital systems.

If you plan on implementing Oracle Cloud ERP and Ivalua, the following best practices will help guide your journey:

1. Recognize that not all cloud infrastructures are the same

Like Oracle Cloud, Ivalua also rests on a cloud infrastructure. However, Ivalua’s cloud model is different from Oracle. Ivalua is highly configurable, and more closely resembles a typical on-prem structure, with the capability to customize data migration load templates that are client-specific.

For example, this hospital system converted legacy contracts to Ivalua, which were then migrated to Oracle Cloud via a BPA (Blanket Purchase Agreements) interface. One of the hospital’s unique business requirements was that contract priority be converted to Ivalua. Even though Ivalua does not have such a field out of the box, we were able to quickly create a new custom field, add it to the Ivalua load template, and integrate it into an existing Oracle Cloud field.

2. Adapt your load approach for each system

As an all-encompassing ERP, Oracle Cloud enforces data integrity validation and structural crosschecks that will prevent invalid data from loading, which consequently requires longer loading times. In contrast, Ivalua’s focus on specific modules enables faster data loads.

For this hospital’s implementation, during the second System Integration Testing (SIT2) cycle, a new Ivalua scope requirement unexpectedly came up which required the team to purge previously loaded data and reload contracts according to the new requirements. The entire contracts purge and re-load process was able to be completed within 48 hours (the load itself took less than 1 hour).

3. Understand Inter-dependencies

When implementing Ivalua alongside Oracle Cloud, consider the common conversion elements between the two data transformations. For example, when converting procurement elements into Ivalua, it is critical to maintain a focus on Suppliers, Items, and Manufacturers that are also being converted to Oracle Cloud. A consistent scope and deduplication strategy should be implemented in Ivalua and Oracle Cloud, and common keys will need to be referenced in both systems. One final area worth exploring could be using your existing Oracle Cloud to Ivalua integration to replace some of the Ivalua migration work.

To help us handle these complex interdependencies, we used a data conversion tool – Applaud – to maintain a shared data repository across these data sets. This made it possible to report against the entire data landscape and keep key values synchronized between Oracle Cloud and Ivalua. Applaud also accelerated deduplication of supplier data in both Oracle Cloud and Ivalua, resulting in optimized business outcomes after go-live, related to a single view of suppliers, total spend, corresponding volume discounts, etc. Finally, we were able to rely on existing integrations between Oracle Cloud and Ivalua to replace several supplier conversions, saving the hospital tens of thousands of dollars in the process.

4. Establish a program-level plan encompassing both Oracle Cloud and Ivalua

It is important to view things at a program level, not just at the individual Oracle Cloud and Ivalua project levels. For example, on this hospital’s implementation, supplier data was initially being reviewed, loaded, and validated by separate teams for Oracle Cloud and Ivalua, which caused inharmonious data to be loaded to the two systems. By moving to a common team performing a common sign-off, data quality was vastly improved, and the amount of rework was reduced.

Additionally, Oracle Cloud load failures can have a major impact on Ivalua data conversion. Even a handful of suppliers falling out from the Oracle Cloud loads have the potential to significantly impact downstream Ivalua loads. For example, during the SIT2 cycle, one of the suppliers that fell out from the Oracle Cloud loads corresponded to dozens of contracts and thousands of contract lines. Without performing a delta load of this supplier to Oracle Cloud and Ivalua, thousands of item prices would be missing from Ivalua.

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The steps outlined above give you a framework to understand the Ivalua and Oracle Cloud systems relative to one another and accordingly plan your conversion effort. Having a common team with a common data migration solution to work on both Oracle Cloud and Ivalua gives you visibility into all the inter-dependencies mentioned above and potential breakdowns.  

‍IT Transformations that involve multiple technologies can be daunting, but the payoff is that your organization will have a best in class solution that addresses your unique needs. I wish you luck on your implementation and if you have any questions about data conversions for Oracle Cloud and Ivalua, please contact me at luke.sherer@definian.com.

We are at the beginning of our Cloud journey for a globally recognized research hospital. This institution has thousands of beds and conducts 2,500 ongoing research projects. When Definian was brought onto the project, our goal was to help establish a high-level process flow for the Oracle Project Portfolio Management and Grants. The insights we gained over the last several months will fuel this institution’s ERP transformation as it continues to grow and acquire additional institutions.

If you plan on implementing Oracle Cloud PPM and Grants you will have to face the questions I pose in the 4 critical areas listed below:

1. What is the financial design of Projects and Grants?

The Projects Portfolio Management (PPM) module organizes activities as projects and provides a framework to organize finances. Depending on the financial requirements, there are various ways to set up projects. For example, billable projects require a project contract, which identifies billing methods and procedures. For any institution receiving external grant funding, they will likely have to implement the Grants module. This module can be seen as an extension of Projects, where Awards are created to organize and control Grant-related finances in a unified platform. Note that a contract is automatically created when an award is created, but updates may need to be made manually or through a web-service.

Each design decision has implications for downstream conversions, business users, and even other modules. However, these decisions are rarely finalized in the early days of a project. For this hospital, we sketched out multiple approaches, loaded data for a few options as a proof-of-concept, and iteratively zeroed in on the right solution. This iterative approach enabled the Client to see their data structured in different ways early in the project and saved the implementation team time by figuring out the right design outside an official integration test.

2. How are personnel configured?

A project must be assigned a project manager, and an award must be assigned a principal investigator (PI). Before employees can be assigned to these roles, they must fulfill certain configuration requirements, which might require several rounds of testing. This setup is especially difficult if you are not using Oracle Cloud as your HCM solution since the interface itself may need to be updated. Project Managers must be assigned a job and department and have an active assignment, whereas PI’s must be loaded as a PI in Awards Personnel and be configured as resources.

These are all separate configurations and the complex interplay between them needs to be thought through and vetted. Even after the vetting, the maintenance of these configurations can be difficult to maintain. One technique we’ve developed that has been critical in the success of the project is an automated process that checks for the missing and mismatched configurations for the personnel within Oracle Cloud prior to every conversion cycle.

3. How should budgets and costs be designed?

Depending on business requirements, there are several ways that budgets and costs can be organized. If the projects are budgetary controlled, the total cost for a project must be less than the total budget for the project – if the legacy system did not enforce these controls, then you should expect load errors and data cleanup. Another consideration that is critical to auditors and compliance officers is how historical cost data will be handled. If business requires historical data, you may want to summarize/aggregate costs by month or year to address the high volume and streamline the loading and review process.

This summarization is exactly what we did to ensure that our Client meets audit requirements. Our conversion approach is to aggregate historical costs by expenditure type, month, and year so that this data can be easily reviewed in Oracle Cloud for auditing purposes. Then as part of this process, we validate that total costs on the project does not exceed the total budget. This approach prevents data discrepancies and avoids data fallout during the load process.

4. Can the data be loaded and processed within the cutover window?

The cutover window is a necessary part of go-live where the legacy system is completely shut down, data is migrated to the target system, and the new system is turned on. During cutover, business cannot be conducted as usual and, for healthcare, there is clinical impact. All data migration activities must fit into this window so that business functions are not impeded. Note that loading and processing times can be different depending on the configuration of your Oracle Cloud pod, so it is critical to monitor performance in preparation for cutover.

For this project, we found that even after aggregating cost data by month and expenditure type, over 1.5 million Project Cost records would still need to be converted to Oracle Cloud. We learned from test cycles that it will take 24 hours to load this volume of data. This posed a serious risk to go-live and left little time for running conversions, loading upstream objects, post-load processing, and validating data during the cutover window. To reduce risk, we worked with the hospital on a plan that migrates the vast majority of the data weeks prior to go-live and shortens the cut-over window.

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Whether you represent a research hospital, a university, a non-profit, or any other enterprise that relies on Project and Grants management, these same questions will be relevant to you as you begin your Cloud journey.

For a hospital like this, projects range from grant funded research in everything from cancer to coronavirus, internally funded initiatives, and even construction. By upgrading from their aging Lawson solution to Oracle Cloud, the institution will be able to track projects from inception to close and have access to comprehensive reporting. This will make meeting budgetary, statutory, and regulatory requirements easier, and the institution will become a better steward of donor and sponsor money.

This implementation also positions the hospital for continued growth. The questions detailed above are an important part of the discovery and requirements gathering process for implementing Oracle Cloud PPM and Grants for each acquisition and are part of our best practices approach.

I wish you luck on your implementation and if you have any questions about data conversions for Oracle Cloud Project and Grants modules, please contact me at dennis.gray@definian.com.

A few months ago, while working on an ERP implementation for a large hospital, one of the directors on the supply chain team was abruptly pulled away. A key supplier admitted that one of their contractors was manufacturing in a facility not registered with the FDA and surgical gowns they manufactured may not be sterile. Considering this emergency, I was ready to postpone the meeting. But the team quickly agreed that we needed to complete this requirement gathering session. We needed to move forward and make progress on this project. After all, this supply chain disruption was exactly the type of challenge that our new solution would be able to handle more swiftly and accurately than their aging system could.

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Due to the complexity of hospitals’ supply chains, clinically impactful disruptions are more common than most people expect. In addition to having multiple locations, departments, and business units to account for, hospital supply chains are further complicated by the range and types of products involved and the different requirements for handling them. For example, pharmacy products are highly regulated and therefore require accurate end-to-end tracking and management to ensure compliance. Countless products are subject to safety recalls – like the one that pulled our supply chain director away. Mismanagement of these supply chain complexities can result in situations in which doctors and nurses are unable to carry out their mission as caregivers.

According to a Cardinal Health survey from 2017, 18% of hospital employees have heard of a patient being harmed due to a supply shortage. Also, 25% knew of expired or recalled products being used to treat patients. Inefficiencies and functional gaps in aging supply chain management systems are causing patients to receive less than desirable care. The same Cardinal Health survey showed that 20% of a physician's time at work is consumed by supply chain tasks rather than caring for patients or working on research. Hospitals in America could save $24.5 billion annually or approximately $11 million per hospital each year by eliminating supply chain inefficiencies. To generate these estimates, hospitals with high performing supply chains were compared with all others, which proves that these savings are realistic and attainable without sacrificing overall hospital performance.

Every day, Supply Chain Management errors hinder doctors and nurses’ ability to effectively treat patients. With these issues occurring with such frequency even during normal operations, it is not hard to imagine the widespread Supply Chain challenges that would occur during a crisis, especially a global one. Today, amid a pandemic, hospitals must function as efficiently as possible. Doctors and nurses want to focus their attention on patient care rather than the availability of supplies, but this is not always possible.

The COVID-19 pandemic dramatically disrupted the medical supply chain. Demand for masks, antibiotics, and other supplies skyrocketed as medical staff, first responders, and average citizens all attempt to protect themselves from exposure to the virus. At the same time, the supply of these items has plummeted. China, the world’s largest supplier of masks, was forced to close factories to prevent the virus’s spread. These factory closings in China have limited the supply of antibiotic components to India, which is the world’s primary producer of antibiotics. As Indian government officials attempt to handle the pandemic in their own country, they have begun to restrict the number of antibiotics that are exported. To make up for the lack of supplies available to be imported, American companies stepped up, put their normal business operations on hold, and began making ventilators and masks using any available supplies and equipment. Medical Supply Chain Management systems must be able to adapt to these unusual circumstances to procure the appropriate amount of supplies based on the changing demand and sourcing from new or unusual vendors. While the supply shortages caused by COVID-19 have grabbed media attention recently, the reality is that supply chain management issues existed in healthcare long before the pandemic forced them into the spotlight.

Hospitals must be able to overcome challenges and respond quickly and effectively during a crisis to provide the best care for those affected. People are getting dangerously ill and dying from coronavirus. Caring for patients and saving lives must be the priority for doctors and nurses. But they cannot devote their full attention to patient care unless they first have confidence in the integrity of the supply chain, certainty about the availability of drugs, PPE and other equipment, and confidence in the accuracy of the data that manages it all. The supply chain must be managed effectively by a Supply Chain Management System to allow doctors and nurses to focus on patient care with assurance that they will have the necessary and proper supplies to do so.

We continue to move forward with the hospital ERP implementation, even amid this pandemic. Virtually, I am still working alongside my colleagues in the hospital system, testing new scenarios, and working through evolving requirements. I am lucky to be on a team like this, uniquely positioned to follow the stay at home orders while still contributing to the future of healthcare. Together, we are transforming the enterprise and putting a supply chain solution in place that will prepare the hospitals for the next challenge. This work will ensure that at the go-live date doctors and nurses will be able to trust that the supply chain is being managed effectively, reducing the risk of mishaps, and accelerating the response to health emergencies. This current pandemic proves just how significant the work we are doing is and why it is essential for us to continue working on the project. When the new Oracle Cloud implementation goes live, the hospital will find itself not only with streamlined reporting, supply and demand predictions, and supplier regulations but also with reduced operating costs.

Hospital supply chain management systems must be able to handle complexities, whether those complexities come from a global pandemic or regular daily activities. Definian migrates the data that drives these systems and ensures that they will function as efficiently and accurately as possible. With these systems in place, doctors and nurses can provide the high standard of care that we all hope for with the peace of mind that they will have the supplies needed to do so. While the recent pandemic highlighted the challenges facing healthcare supply chain management systems, these challenges existed all along. For hospitals to provide the best possible patient care, they must have an effective supply chain management system. Understanding the clinical impact of an SCM solution continues to motivate my team and I to keep working hard, especially through the COVID-19 pandemic. We know that when the project is complete it will make a real impact to alleviate stress and reduce extra work for doctors and nurses. Simultaneously patients will receive better care because of streamlined operations. Because of our efforts to migrate to Oracle Cloud, the hospital will be in a better position to manage the next supply chain disruption. Our Definian team is proud to work on a project that will have such a long-lasting, positive impact.

Austin, Rob. “Hospitals' Supply Chain Savings Opportunity Jumps to $25.4 Billion a Year.” Guidehouse, 18 Oct. 2018, guidehouse.com/insights/healthcare/2018/supply-chain-analysis?utm_source=pr&utm_campaign=sc18.

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