Long-time Alteryx users know that getting started is easy, but also that the freedom to explore the most valuable use cases is less about power and more about the physical space between Alteryx and the data. This is called Data Gravity, described like this by Dr. Athina Kanioura, PepsiCo’s Chief Strategy and Transformation Officer, and previously the Global Head of Applied Intelligence at Accenture:
“As data gravity takes hold, it becomes more difficult and expensive to move data and applications around. This can create significant challenges for organizations, particularly when it comes to the performance and scalability of their analytics and machine learning workloads. To address this challenge, organizations need to find ways to process and analyze data at the edge, where it is generated and consumed, in order to reduce latency, improve performance, and enable real-time decision making.”
The good news for Alteryx customers is that data gravity can’t hold you down anymore when it comes to prioritizing the highest-value use cases — especially if you use Snowflake. This is good news to any supply chain leader struggling to adapt to uncertainty and disruption.
The In-DB Connector
Since 2017, users have been able to leverage Alteryx-Snowflake in-database processing. Through this functionality, supply chain analysts had the option to create more sophisticated predictive models that incorporate a larger and more diverse set of data, such as transactions, customer demographics, social media, and other external sources.
Now able to handle larger data sets and more complex processing, analysts could reflect never-before-seen customer behaviors and marketplace signals in forecast models. That’s essential to help supply chain leaders improve inventory planning, production scheduling, and demand forecasting decisions.
Pushdown Carries the Load
In 2021 Alteryx announced even deeper integration with Snowflake that included the ability to execute complex workflows directly in Snowflake through push-down capabilities. This gave supply chain analysts the freedom to develop predictions the right way. Alteryx can move more data preparation and blending tasks directly into the Snowflake environment, allowing for more complex data transformations and computationally intensive queries to be processed within Snowflake.
This made it easier for analysts to leverage the full power of Alteryx and Snowflake together, without the need to switch between platforms or invest in additional infrastructure. Less friction = greater adoption and value.
Making an Impact for Supply Chain Analysts
Now that you’re caught up, you can see how this leads to immense benefits for use cases of the non-predictive variety — e.g., the reporting or descriptive analytics more common and fundamental to measuring operational performance.
Among the business functions featuring the greatest volumes and varieties of data types is the supply chain. For example, supply chain analysts may need to incorporate supplier performance metrics, customer transactional data, logistics and transportation data, weather data, and sensor data, among others. These sources are neither small nor very structured.
Looking ahead, I expect that many more new Alteryx customers’ first use cases will instead be in the supply chain or other priority areas now that restrictions on use case complexity and intensity have been lifted. Letting potential value be your guide, as opposed to technical data limitations.
Cloud Opens Adoption
Move ahead further in time, to February 16, 2023, and Alteryx announced, “new self-service and enterprise-grade capabilities to its Alteryx Analytics Cloud Platform to help customers make faster and more intelligent decisions.”
Now, the Alteryx customer has a choice between the traditional Designer/Server experience behind much of the story in this post, and Cloud-only offerings that present some familiar and new capabilities to support supply chain decision improvement.
Consider that Snowflake was the Cloud launch partner for this announcement and also what makes Snowflake so appealing to customers: ease of use, separation of processor and storage in the payment model, and data sharing — all in support of becoming a more data-driven, smarter, and agile organization. That’s not an easy value promise to keep when you don’t own the last mile of analysis. Or as said in the press release by a Snowflake official:
“The Alteryx Analytics Cloud now brings the self-service data analytics interface to the browser, while Snowflake reduces the barrier to entry for more users,” said Christian Kleinerman, SVP of Product, Snowflake. “By providing in-database processing natively for data platforms, Snowflake and Alteryx help customers significantly speed up their analytics processing, while improving efficiency, security, and cost reduction.”
A version of Designer, Designer Cloud, offers many of the same capabilities but is easily provisioned to many more users than was possible before, just like any Cloud application. So, whether a customer begins the journey in supply chain or finance, continuing forward into other departments does not require a significant investment in additional resources or training, and avoids conflicts with IT or existing governance controls.
A dedicated predictions application called Machine Learning featuring built-in education is also Cloud-based and can operate on top of existing data integration workflows to speed the modeling process. Those models in turn can be plugged directly into existing and new workflows: imagine a predictive maintenance model scoring new sensor and CRM data and generating an App for workers in a factory to check the service status of shop floor machines.
Likewise, Auto Insights can interpret trends within existing workflow outputs to bring added fidelity to the insights presented by static reports and dashboards. There’s a concept called “Analytics Empathy,” which many leaders lack and leads to a reliance on gut feel over data to make decisions. Auto Insights presents a path to improving the Analytics Empathy — and decision effectiveness — of your supply chain leaders.
Lastly, Metrics Store is exactly that: an implementation of standardized yet customizable enterprise KPIs and metrics within Alteryx, accessible so that everyone is on the same page when it comes to defining and tracking performance. You can’t improve what you can’t measure.
With technical and adoption barriers removed, supply chain leaders are now free to explore the highest value use cases from the beginning of their Alteryx journeys. Just like their peers in finance, where numerous users surpassed the constraints of spreadsheets and automated various analyses related to auditing, compliance, regulation, tax, and accounting.
For more about Alteryx in Supply Chain
- Alteryx for Supply Chain Intelligence
- eBook: 8 Areas of Your Supply Chain That Can Create Growth Right Now
- IDC Report: Enabling Growth and Resilience in Supply Chains with Customer-Centric Analytics