Data Readiness (Office of the CFO Series, Part 2)



“Garbage in, garbage out” – George Fuechsel

A lot of people use the term “garbage in, garbage out” without realizing that this was actually coined by George Fuechsel, an early-days IBM programmer and instructor. He said this in an effort to express to his students that a computer system is merely a place where we input information, and if that information lacks integrity then the system will perform poorly. This saying has aged extremely well and I use it often in many areas of my life, not just at work!

At Uptima, we often hear from our customers “…but I don’t know if the data is correct and I have to go check here and there to validate it.” When we are working across the revenue lifecycle, these words are like nails on a chalkboard. We understand. We have to balance books, too!

The biggest risks in data structures today

The big problem many organizations face in their data structure stems from moving quickly or overcomplicating the data model, which often results in less than ideal quality through rushed development, development that was disjointed because of a lack of testing or control, or a poor fitment of “best of breed” systems. Also, there can be several systems bolted together without any sort of Master Data Management or designation of a single source of truth, creating out-of-sync data scenarios. In an effort to control the previously mentioned issues, organizations may find themselves leveraging heavy integrations that fail under their own weight (or fail due to following the previously mentioned methodology), which only ends up in the organization reverting back to manual intervention…

And what does Finance and Accounting hate? Manual Intervention. Manual intervention is at the bottom of the hierarchy of “good integration plans” for an accounting team, because out of all of the above scenarios where data and dollars are slowed or disjointed, manual intervention introduces the chance that data is just plain WRONG, and due to the errors introduced during manual transposition, often there is no “mismatch” error to find the bad data.

Creating clean data, top to bottom

When it comes to revenue, “good enough” doesn’t cut it. We frequently work with our customers to create a healthy data model through steadfast governance and change management. We work together with our clients to form a true partnership, allowing the client to take on key decisions, while relying on us as a shepherd through the process. The result is a well defined Revenue Lifecycle, predicated upon industry, policy, and regulatory best practices, that builds a true Revenue Master, bridging the Sales and Finance masters to a common goal… Clean Data, Top to Bottom.

Creating an intelligent data model

How do we get there? By being a guiding light through a discovery process that assesses and corrects bad data through asking some of the following:

Who is best suited to define key sales and financial data? How does the sales and financial data fit into your Revenue Lifecycle? Who relies on this data, from private owners to public shareholders, and what are the regulatory risks and requirements? What do you plan to do with your sales and financial data, outside of Forecasting, Reporting, and Booking? What KPIs are dependent on this data to allow the business to glean useful insights into health and prospects? What pieces of data do you trust, and what controls do you have in place to illuminate bad or risky financials? Which parts of the sales and financial processes are ungoverned or introduce risk? Do you have any unique needs for your business in revenue recognition and recording auditable information?

With this approach, we create a data architecture that is intelligent and meets the needs of our users and stakeholders because “Revenue is king”.


Up Next in our Series, The Office of the CFO: Enabled through Salesforce

Stay tuned for Part 3 of this series, Salesforce plus the ERP: In Perfect Harmony, coming shortly!

In Part 3 of this series, we will take a closer look at top 4 ways the Sales Master and Finance Master can work together. We will focus at a high level on the Salesforce Object model and how those objects interact intelligently with the ERP depending on the types of products and contract based pricing are taken to market to best address the needs of Sales and Finance.

For more details about our 7-part series, visit our original post here:


Written by Sean Philbin, Sr. Practice Director Revenue Cloud, revenue specialist by week day, race car driver by weekend, at Uptima.