Supply chains face a struggle between the opposing demands of speed and quality. Acting quickly sometimes means sacrificing accuracy, completeness, or depth while seeking perfection can result in costly delays and missed deadlines.
Thus, “good enough” characterizes many of the hundreds of operational decisions impacting supply chains every day. Poorly supported decisions have negative consequences for nearly all manufacturers and their suppliers, retailers, and other participants in the supply chain ecosystem.
Conditions like these are simply unsustainable in a world characterized by economic uncertainty and ongoing disruption due to the pandemic.
Even market share leaders with highly developed data and analytics practices have their challenges. Data-driven transformation is more of a journey than a destination, meaning the most advanced organizations face shortages of skilled workers and managers who recognize the value of analytics over intuition.
Thus, solutions that overcome these challenges are in high demand. The Alteryx Analytics Cloud sits at the intersection of better supply chain decisions and broader company objectives to empower all workers to embrace data-driven decision-making. In other words, Analytics for All.
Simplifying the work of analytics
Against this backdrop is the evolving role of the Chief Data or Analytics Officer. Trends point to data leaders focusing less on infrastructure and technology and more on adoption and the organizational changes necessary to impact business outcomes. To accomplish this at scale, it’s necessary to remove barriers to the productive use of data.
Between data sources and business outcomes lies a series of steps in a process that typically requires highly skilled data and analytics workers. Few to no purpose-built visual software tools reflecting this process are available, leaving most organizations to deal with some combination of suboptimal spreadsheets, manual coding, and a chasm between the business and IT too large to accommodate the speed and specificity required of quality decisions.
The Alteryx Analytics Automation Platform abstracts complexity while automating tasks that benefit from independent execution. Thus, less time is spent on non-value-added tasks, and more effort is applied to supporting data-driven transformation goals such as faster, better-informed decisions.
Alteryx Analytics Cloud products include Machine Learning, Designer Cloud, and Auto Insights. Each supports numerous use cases using visual methods that remove hurdles to decision speed and improvement.
Many use cases can leverage assets developed by existing Alteryx Designer and Server customers to speed time to value. For example:
Data workers of all stripes, from business analysts to data scientists, can automate every step of the analytics process, including data preparation and blending, reporting, predictive analytics, and data science. Access to any data source is possible — big or small, operational applications or data warehouses, in the cloud or on-premises, internal or third parties.
Common Use Cases: Numerous; Demand Forecasting for Safety Stock Optimization, Inventory and Assortment Planning, Predictive Maintenance
Typically paired with multiple Designer users, Server allows analytic project assets to be shared, automated, secured, and governed. It’s an essential element for those who recognize the benefits of applying Designer to many use cases across an organization.
Common Use Cases: Designer Workflows as Analytic Applications for Everyone (e.g., select a machine to determine service or maintenance status), IT/Data Governance, Upskilling and Training
Supervised machine learning (ML) offers a path to predicting outcomes for various potential use cases critical to an adaptive supply chain. Yet model development and deployment can be a complex process requiring highly skilled and experienced data scientists. Whether or not your organization has such resources, Alteryx Automated Machine Learning empowers workers of varied backgrounds through a visual and guided approach that emphasizes accuracy, understanding, and trust.
Rather than time-consuming manual investigation and transformation of data for machine learning, native integration with Alteryx Designer speeds training-data preparation.
Common Use Cases: Demand Forecast Prediction, Capacity Planning, Prototyping Machine Learning Projects, Upskilling and Training
Some analytics use cases are only as good as the quality of data available in the data warehouse. Thus, many organizations have begun migrating on-premises data warehouses to the cloud, where they can be scaled up and down as conditions change while augmented with new data in ways not realistic in the past.
Data engineering teams tasked with building, automating, and evolving connections between sources and the warehouse can leverage Designer Cloud to speed up the profiling, preparation, and data pipelines for analytics and machine learning. Designer Cloud provides an interactive, visual user experience that uses machine learning to guide the exploration and transformation of any dataset.
Common use cases: On-Premise-to-Cloud Data Warehouse Migration, Data Governance
The last mile for many analytics are the visualizations or reports delivered to those in the business tasked with making a decision. Rather than requiring someone to interpret these outputs, Alteryx Auto Insights automates the process of finding insights, so business users can take action sooner. Like Machine Learning, Auto Insights integrates with Designer when helpful to prepare transactional or time-series data sources.
Common use cases: Spend and Procurement, Retail Performance and Operations, Labor Productivity and Utilization
Analytics for All
While each element of the Alteryx Analytics Cloud offers distinct value, it’s when they are applied collectively relative to an organization’s priorities and analytics maturity that the most value is realized. For many, the value of better supply chain decisions made more quickly – by more workers – makes the Alteryx Analytics Cloud an essential part of digital transformation success.
To benchmark your organization’s analytics maturity, take the Alteryx Analytics Maturity Assessment
To identify the best use cases to pursue first, complete the Alteryx Business Use Case Discovery Guide