Technology has powered the evolution of finance departments by enabling them to become proactive and partner with the business on critical decisions. In the past, forecasting and analyses were spreadsheet-driven, highly manual processes that consumed resources and time. Talented finance professionals deserved better, and so did the companies that employed them. That was before the Snowflake Data Cloud arrived on the scene and disrupted the status quo of financial operations and began modernizing the workflows that finance professionals depend on. This ongoing evolution led by the Data Cloud’s unique capabilities has enabled finance teams of every size, industry, and scale to utilize dynamic models with real-time feeds of operational data that support the execution of strategic planning, forecast precision, and the ability to take action on the latest insights.
As cloud adoption continues to become ubiquitous, so too does the massive volume of data that is generated from all types of sources, making data collection, harmonization, and activation critical elements of modern organizations and teams. Finance departments are at the forefront of this transformation and need reliable and timely information that directly influences their organization’s margins to capitalize on every growth opportunity. One clear example of this need, which is uniquely acute in the cloud computing era, is the need to arm finance teams with proactive and analytical methods that help them understand their cloud costs and the right level of agility to act quickly on new insights. The practice of waiting for the month-end invoice is becoming obsolete. Instead, finance departments require the ability to pivot and change direction as they receive new data and fresh information.
Finance departments need to understand cost drivers holistically, starting with enriching their data so that their organizations can see the full picture across multiple departments. Another area we see a strong need for across finance is automation. If your team is repeatedly performing an analysis/process, or returning to an identical issue, again and again, consider investing in capabilities to better address these challenges head-on.
The Snowflake Financial Planning and Analysis (FP&A) team has itself taken this journey and uses the Snowflake Data Cloud to accurately attribute and understand cloud costs, identify and react to trends, and predict future spend with more precision. Based on our own journey, we are able to share several lessons and repeatable processes that can provide a blueprint to help your organization’s finance department take a similar route.
1. Map cloud spend to your organization’s cost of goods sold (COGS)
To effectively manage and forecast cloud spend, teams need a holistic picture of their data that is presented in a structure that resembles how the business operates and functions. For instance, similar to forecasting revenue for a consumption-based business, analyzing and forecasting COGS at Snowflake is a complex problem. Every customer uses Snowflake in a unique way, and because of this, every customer has a different profile based on an ever-evolving and growing list of factors. From a strategic and operational perspective, organizations should aim to understand how variables such as the specific region/cloud, features used, unique workloads usage patterns, and more may impact short- and long-term margins.
By using the Data Cloud, our Finance department was able to get a single data set that blends together data from across the company (for example, product, sales, vendor) into one source that provides accurate cost data down to a granular level .
2. Automate cost management
The cloud can frequently act as a catalyst for rapid growth. Whether your organization is expanding across the globe, or adding employees and customers rapidly innovating core products and services in multiple directions, there is a need to get away from manual processes and invest in automation. At Snowflake, as we went through our own rapid growth, we realized early on that the only way to properly scale was through automation and tooling that reduced manual work and allowed Snowflake to not lose sight of the granular details of the business.
Snowflake’s journey leveraging cost automation is applicable to almost any team and company looking to level up its expertise in cost management of cloud spend. First, you need an easy way to track historicals and examine the current state. Dashboards are a great visualization tool that can be assembled and shared quickly across the business to efficiently provide context. Snowsight dashboards—and coming soon to private preview Streamlit—are Snowflake native tools that can be used to check overall trends and share knowledge across the business.
Often, as a company scales, smaller events of waste begin to go undetected and larger events are only noticed once they become a considerable issue. By investing in anomaly detection by applying advanced modeling to their data, organizations can pick up on small instances of waste and automatically trigger a communication with the appropriate stakeholders.
Finally, as organizations scale, efficient management, calculated purchasing, and intentional coverage of pricing instruments result in material savings (or unplanned cost). Automating every phase—past, present, and future—of cloud spend is critical to not get lost in the noise of scale and operational complexity.
3. Enable attribution of spend
Attributing spend, which is essentially the ability to track the individual cost of a good or service to the end user, is equally as important through an internal, operational lens as it is to the external performance of an organization. Regardless of the scale of your operation, or the resourcing needed to develop your product, the value and outcomes driven by assigning ownership to internal cloud spend remains foundational.
Snowflake has two main sources of internal cloud spend cost: cloud service providers (CSP), which is almost entirely related to our engineering team’s usage, and Snowflake’s cloud spend for the remaining business units within the company.
When it comes to CSP spend, the goal is to attribute development spend to individual teams and cost centers programmatically—via systems and tagging from engineering prioritization and investment—and aim to assign allotments to individual teams by the end of the next year. This provides autonomy for different engineering teams, while improving short and long-term visibility for the Finance team and company leadership as to where investment in their team is going.
For Snowflake spend, the Finance team happens to be one of the largest users of the Data Cloud at Snowflake. With Snowflake’s own heavy use of the Data Cloud, the Finance team also tracks the usage costs for internal teams, which is particularly relevant in the context of Snowflake’s multi-tenant product. By having a robust and accurate customer-level costing of usage, it’s recommended to cost the usage just as if it were any other customer.
However, attributing the usage at the customer level isn’t granular enough to generate real insights on cloud spend. As such, the Snowflake team created a data model framework that uses metering data to attribute usage down to a specific team, or even user. This allows teams to understand how they use Snowflake today and plan for and optimize that cost in the future. Similar to how Snowflake attributes usage to sources or customers in our own environments, it is essential that organizations on this journey do the same in order to drive accountability and ensure that internal cloud spend grows in an intentional and efficient manner.
4. Enablement of stakeholders and business
Lastly, it is critical to provide visibility and enablement to the broader organization. As more organizations become established in the cloud, the topic of proper cloud spend management affects everyone, both directly and indirectly. Below are examples, outside of core engineering teams, that use products from the function of our management of cloud spend:
For many financial teams, managing cloud spend is a relatively new challenge and a recurring pain point—but it doesn’t have to be. It can be solved by understanding the cost drivers, automating cost management, effectively managing spend, and enabling key stakeholders to leverage the data they need to take action. Being able to optimize cloud spend drives efficiency at scale, and helps users ensure they are using the cloud in an intentional and efficient manner.
Learn more about using Snowflake for financial departments here.
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