Gartner defines analytics and business intelligence platforms (ABI) as those that enable organizations to model, analyze and visualize data to support informed decision making and value creation. These platforms facilitate the preparation of data and the creation of interactive dashboards, reports and visualizations to uncover patterns, predict trends and optimize operations. By doing so, they empower users to collaborate and effectively communicate the dimensions and measures that drive their organization. The platforms may also optionally include the ability to create, modify or enrich a semantic model, including business rules. Analytics and business intelligence platforms integrate data from multiple sources, such as databases, spreadsheets, cloud services and external data feeds, to provide a unified view of data, breaking down silos and transforming raw data into meaningful insights. They also allow users to clean, transform and prepare data for analysis, in addition to creating data models that define relationships between different data entities.
The supply chain A&DI technology market spans capabilities that provide different types of analytics, focusing on predictive and prescriptive ones. Many of these offerings have been enhanced with AI and DSML capabilities to support supply chain decision making. These capabilities could either be part of a broader supply chain application/suite or a separate encompassing A&DI platform. Such a platform consists of existing and emerging technologies, including: Graph technology, Advanced analytics, AI, DSML, Model development & Digital supply chain twin (DSCT).
Retail assortment management applications (RAMAs) are a foundational component of modern category management solutions for long life cycle products. Using data & analytics and AI technology, RAMAs can curate targeted assortments to create compelling customer experiences, leading to an increase in sales conversion. Long life cycle products in retail include categories such as grocery, consumables and hard goods. The long life cycle retailers’ traditionally broad approach to assortments is not satisfying customers’ demands for more curated assortments to match their lifestyles. Local trends mean that even more granular store-specific assortments are necessary. Advanced analytics, algorithms, AI and automation will play pivotal roles in driving this transformation through better customer understanding and alignment.
Gartner defines network design as the optimization of the location and function of supply, manufacturing and distribution networks in support of an overarching company strategy and customer requirements. Supply chain network design tools support the creation of network models with the application of analytics to determine the optimal supply chain design in a structured, scalable and repeatable way. Supply chain network design tools support the determination of recommendations about the structure of the supply chain network. This includes decisions about facility locations and size, transport lanes, and modes in the end-to-end supply chain. The scale of the changes being evaluated vary from small modifications, such as changing a mode of transport or swapping transportation lanes, to large-scale changes that involve opening/closing/repurposing several facilities in the network and the associated knock on impacts. The use of supply chain network design tools to support the decision-making process enables companies to review more potential configurations for the network than a manual process allows, supporting a complete, data-driven decision making process. These decisions are usually made in strategic and tactical time frames.
Gartner defines supply chain planning (SCP) solutions as platforms that provide technological support to enable a company to manage, link, align, collaborate and share its planning data across an extended supply chain. An SCP solution supports planning, ranging from demand planning through detailed supply-side response planning, and from strategic planning to execution-level planning. It is the planning decision repository for a defined end-to-end supply chain. It is also the environment in which end-to-end-integrated supply chain decisions are managed. It establishes a single version of the truth for planning data and decisions, regardless of the underlying execution technology environment.