For organizations struggling to execute advanced use cases in Salesforce Revenue Cloud, more often than not, the issue lies not in the platform functionality but in the data you’ve put into it. Before you look to other solutions, take a closer look at your data.
For many organizations, perceived functionality issues in Salesforce Revenue Cloud are data deficiencies in disguise. Organizations that fail to properly prepare their data set before migration or maintain it once the system deploys will find that they cannot execute complex use cases or optimally scale initiatives.
Our Salesforce Studio experts explore what goes into an effective Salesforce Revenue Cloud data strategy and how organizations can prepare and maintain their data to get the most out of this market-leading business service platform.
1. Understanding data complexity and criticality in Salesforce Revenue Cloud
It’s important to acknowledge that Salesforce Revenue Cloud fundamentally differs from other products within the Salesforce ecosystem. While all data should be clean, timely, and relevant, data used to develop finance-based assets, such as quotes, contracts, or invoices, requires more complex data models and a higher level of criticality. At the same time, Revenue Cloud connects customer data within the CRM to financial systems – which means it must support the needs of both the front and back offices.
Errors or omissions in the data set in Revenue Cloud could have a massive downstream impact on pricing or billing. To mitigate the risk, organizations must have a higher level of due diligence and awareness about migrating data into Salesforce Revenue Cloud and a plan to govern and maintain it once it’s there.
2. Breaking free of the traditional project mindset
One of the most common missteps companies make during their Salesforce Revenue Cloud migration is to treat it as a one-time project. The data in Revenue Cloud is part of a living ecosystem. It will change and evolve, so it needs to be updated and maintained. There needs to be transparent and accountable ownership for data maintenance and governance.
Organizations must understand that Salesforce Revenue Cloud or any tool of its kind requires an ongoing investment of time and resources to continue to perform optimally. Without that investment, the value the platform delivers to the business will erode over time as the quality and completeness of data wanes.
A data set, no matter how clean at the time of migration, cannot stay that way without a robust maintenance and governance strategy.
3. Assembling a master data management team
Data deficiencies can take many forms:
- Invoices that can’t be paid or posted
- Regional or industry data requirements that are not in compliance
- Inaccurate quotes.
In many cases, the data needed to solve an issue one team is experiencing will be held by another. And therein lies the problem: people in finance need to be made aware of sales processes; people in sales need to understand the needs of finance. Often those teams play a role in the success of the other but are unaware of the other’s needs.
Because of these siloes, data is a team sport. While every team needs different information to perform their task, they must ensure that the entire data set is clean, timely, and accessible.
It is essential to assemble a data management team representing the entire end-to-end process across the data supply chain. Each group should share their needs and challenges and then work together to document processes, determine hand-off points and ensure data is updated and maintained correctly. With that framework, it will be possible for the organization to identify data points of failure and how to prevent them.
Data is a team sport.
4. Defining the enterprise data architecture
Salesforce is not an island – it is part of an ecosystem. Organizations must look at their data across their application landscape as part of an end-to-end process, not in a silo, and answer questions such as:
- Where does your data come from?
- What are your anchor technologies?
- How does it move through your system?
- Where does it live?
- How is it used?
Organizations need to think beyond a single Salesforce application regarding data and the underlying systems and processes that ensure data remains relevant.
We sometimes refer to this concept as a data lineage initiative which is when we map the data’s point of origin and how it is used throughout the business. We review data analytics, insights, reporting, and compliance as part of this process. Knowing the purpose of the data and where it is in the lifecycle allows you to pick the correct data for the proper purpose. With this thorough understanding of the data lifecycle, organizations can identify data gaps, wherein a piece of data gets captured in one process but is not carried through to subsequent parts of the lifecycle.
It’s essential to recognize that back-office processes like billing and revenue reporting depend entirely on data created in the front office. For that reason, data design must consider the needs of sales, operations, and finance when creating data. The resulting process to create the data in Salesforce must also be structured to consider how back-office teams will use the data. This is different than how some other functions, like marketing or customer service, manage this issue since, in those cases, data is primarily used by one team at a time with a clear handoff to the next stage of the process.
Still using spreadsheets in addition to Salesforce? Then you have a data gap.
5. Adopting strong data governance and management
Once the organization understands its data’s lineage and documents its end-to-end processes, achieving a position of enterprise-wide trusted data is possible. Maintaining that position, however, requires strong data governance.
Data governance is the organization’s practice of controlling how data is used, stored, and maintained. It includes things like standards and retention policies and identifying personally identifiable information (PII) that is associated with specific compliance requirements, such as General Data Protection Regulation (GDPR) in the EU or the California Consumer Privacy Act (CCPA).
Another key part of data governance is ensuring that the organization is set up to execute the data. That means making sure the data is consistent, complete, and accurate. Someone needs to look at the data’s physical values and ensure they meet business requirements.
And who, exactly, is that someone? As with so many cross-functional business initiatives, it is often neglected when responsibility is shared. To have an effective data strategy, one person must serve as the champion of that function.
If an organization does not have a chief data officer, which is often the case in small organizations, it may fall into the purview of the CIO or CFO. Regardless of who oversees this asset, they must understand its importance to all business functions.
When responsibility is shared, it is often shirked. To have an effective data strategy, one person must serve as the champion of that function.
|What about tech?
By now, you might be wondering: But what about tech? Shouldn’t the technology platform stand out in each of the above steps?
Quite honestly, no. While technology is often framed as a silver bullet solution that will deliver data quality, data management, and data governance – many stalled projects and failed deployments have proven that it won’t. Organizations must first align people and processes – then think about technology.
That said, it’s important to remember that organizations must closely connect the technology strategy to business objectives and the data strategy to help achieve its vision.
|The value of enterprise-wide data transformation
So your organization has achieved a consistent state of enterprise-wide trusted data – what does your business get in return?
Globant: Our approach to data in Salesforce Revenue Cloud
Unlike other Salesforce partners and service implementors, Globant has a dedicated team specializing in Lead-to-Revenue (LTR) operations. This group knows how to use data across the revenue lifecycle and how this information must be captured and stored in Salesforce Revenue Cloud.
Our cross-functional team includes LTR leaders, Salesforce domain experts, data specialists, and industry professionals that approach Salesforce Revenue Cloud engagements from an enterprise-first perspective, ensuring alignment between how value is sold, delivered, monetized, and accounted for.
As a parallel discipline, Globant works with organizations to align the operational needs of the future with data design. In building that solution, our team partners with clients to clean and migrate their data and adopt appropriate governance and management processes to help unlock the full potential of the Salesforce platform.
- Data diagnostic
- Data migration strategy
- Salesforce data architecture creation
- Data sourcing
- Development, execution, and operation
As companies execute and scale increasingly advanced use cases in Salesforce Revenue Cloud, access to clean, timely, relevant data will become the most critical success factor. This requires companies to not only correctly prepare their data set before migration but meticulously maintain it once the system is deployed.
If your company is struggling with defining its Salesforce data strategy, Globant can help. Our highly specialized data experts and Salesforce specialists work with organizations to help them find their so-called “secret sauce” – a unique and customized approach to data migration, governance, and management to unlock the full potential of the Salesforce platform.
For more information, please contact us to connect with a Salesforce team lead.