{"id":33074,"date":"2021-03-29T14:44:53","date_gmt":"2021-03-29T12:44:53","guid":{"rendered":"https:\/\/www.intellias.com\/?p=33074"},"modified":"2024-01-09T14:38:52","modified_gmt":"2024-01-09T13:38:52","slug":"digital-retail-consulting-to-orchestrate-data-flows-and-operations","status":"publish","type":"post","link":"https:\/\/intellias.com\/digital-retail-consulting-for-global-food-retailer\/","title":{"rendered":"Digital Retail Consulting to Orchestrate Data Flows and Operations"},"content":{"rendered":"<h2 id=\"business-challenge\">Business challenge<\/h2>\n<p>Our client, a leading player in the food delivery and catering services market that provides millions of households and offices worldwide with quality meals, was looking for a trusted technology and retail <a href=\"https:\/\/intellias.com\/digital-consulting\/\">consulting partner <\/a> to enhance their procurement accuracy and cost management.  <\/p>\n<p>The company\u2019s strong and ever-expanding global presence is backed by a network of food producers and produce suppliers as well as a growing base of customers. To handle huge data flows behind the company\u2019s operations with providers and customers, our client built a data-driven technology platform focused on managing supply chains, improving the customer experience, and optimizing business processes.  <\/p>\n<p>However, the company\u2019s constant expansion into new markets and countries added to the operational complexity and inconsistency of its internal systems, leading to numerous data mismatches and financial losses. This prompted our client to seek a partnership with a reliable technology and retail consulting company. They commissioned Intellias, an experienced provider of retail big data solutions, to perform a discovery phase and build an implementation roadmap for data reconciliation and validation software that would serve as a bridge between data services for purchase orders, goods received, and procurement invoices.<br \/>\n<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/d17ocfn2f5o4rl.cloudfront.net\/wp-content\/uploads\/2021\/03\/hellofresh_body-im.jpg\" alt=\"Digital Retail Consulting to Orchestrate Data Flows and Operations\" width=\"770\" height=\"450\" class=\"alignnone size-full wp-image-33080\" srcset=\"https:\/\/intellias.com\/wp-content\/uploads\/2021\/03\/hellofresh_body-im.jpg 770w, https:\/\/intellias.com\/wp-content\/uploads\/2021\/03\/hellofresh_body-im-300x175.jpg 300w, https:\/\/intellias.com\/wp-content\/uploads\/2021\/03\/hellofresh_body-im-768x449.jpg 768w\" sizes=\"(max-width: 770px) 100vw, 770px\" \/><\/p>\n<h2 id=\"technology-value-chain-consulting\">Technology value chain consulting<\/h2>\n<p>To provide strategic retail consulting services to our client, we started with a series of discovery sessions with the main stakeholders and the company\u2019s core business departments, including Finance, Operations, Purchase Orders, and Inventory. Our goal was to collect and validate inputs from all available sources, understand the business flows, identify constraints and showstoppers, and come up with ways to solve them.     <\/p>\n<p>Our client\u2019s global procurement system includes three key components that needed to be integrated and synchronized:<\/p>\n<ul>\n<li>A <strong>purchase orders platform<\/strong> that generates purchase orders which are then formed into offerings and sent to end users<\/li>\n<li>An <strong>inventory and stock system<\/strong> that tracks goods delivered to the company\u2019s warehouses, matches them with purchase orders, and verifies the quantity and timelines<\/li>\n<li>An <strong>Oracle Procurement Cloud module<\/strong> that processes and manages all invoices from suppliers<\/li>\n<\/ul>\n<p>As part of the retail technology consulting that our team provided, we conducted a deep analysis of our client\u2019s business processes and uncovered the reasons for data discrepancies between the client\u2019s internal systems. While in some countries the processes were fairly straightforward, in other countries a large number of subprocesses and subsystems appeared which didn\u2019t align with the procurement system as a whole. As a result, multiple errors were creeping in that caused significant monetary losses. The incorrect data also hindered efficient data-driven decision-making.    <\/p>\n<p>Following our retail consulting research, we prepared a discovery proposal where we offered our understanding of the problem statement, highlighted the key bottlenecks we found, and suggested necessary steps for the next stages of the project:<\/p>\n<ul>\n<li><strong>Data synchronization<\/strong><\/li>\n<\/ul>\n<p>Drawing on our rich <a href=\"https:\/\/intellias.com\/data-science-and-big-data\/\">big data expertise<\/a>, we came up with a list of potential methods to sync data across systems. These included back communications between the systems, monitoring dashboards, interfaces for suppliers, and a single place for specific business logic to align purchase orders and goods received. <\/p>\n<ul>\n<li><strong>Three-way matching<\/strong><\/li>\n<\/ul>\n<p>One of the most important steps our client planned to take was introducing a three-way matching technique that would allow for comparing purchase orders, goods received, and invoices to validate payment and delivery details. The strategic retail consulting approach we suggested took into account all necessary procedures for the Oracle three-way matching system to start working.   <\/p>\n<p>Based on certain rules, data is retrieved from the systems for purchase orders and goods received. That data is then validated according to rules verifying that there are no changes or errors to the approved or completed orders and that all data is available and comes in the right sequence. At this stage, the goal is to detect and handle logical, technical, process, and human errors.  <\/p>\n<p>After all datasets from both systems are compared and aligned, the data is ingested into the Oracle Procurement system with the help of transformations and lookup validations so financial specialists can run a three-way matching procedure. Future iterations of our client\u2019s solution will aim at full automation of the three-way matching process. <\/p>\n<ul>\n<li><strong>Architectural solution<\/strong><\/li>\n<\/ul>\n<p>Our key findings and insights from the whole retail technology consulting process were reflected in the architectural solution offered by the Intellias Principal Architect. The architectural solution also featured a comprehensive integration data flow diagram, additional artifacts, data mappings across different systems, definitions of technical issues within the organization, error cases, and successful scenarios of data ingestion into the Oracle Procurement system.   <\/p>\n<p>One of the greatest technological challenges faced by our team was realizing our client\u2019s decision to introduce an enterprise service bus built on Kafka for stream data processing. The streaming platform was meant to match all datasets within the entire organization. While the solution itself was very specific and complex, our Intellias Architect worked out straightforward requirements, so the architecture was understandable at the design level and provided insights on what functionality to implement and in what order.<\/p>\n<h2 id=\"business-outcome\">Business outcome for a global retail leader<\/h2>\n<p>Our vast expertise in building <a href=\"https:\/\/intellias.com\/retail\/\">retail software solutions<\/a> enabled us to provide top-quality retail consulting services to a global food delivery unicorn. Though the technology behind our client\u2019s operations has already put them in a prime position to use data for improving the customer experience and supply chains, the Intellias team\u2019s contribution will allow our client to fine-tune business processes, refine data, and save money that would otherwise be wasted due to disconnected internal systems.   <\/p>\n<p>As a result of the discovery phase run by the Intellias team, our client received a clear understanding of the solution roadmap and the next steps to take in achieving accurate procurement data and eliminating the probability of data entry errors. Our successful collaboration on this initial engagement resulted in launching several new projects for our client that Intellias is now working on.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We partnered with a global food retailer to provide retail consulting services and conduct a deep discovery phase to enhance their data platform<\/p>\n","protected":false},"author":18,"featured_media":50413,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[5],"tags":[75,79],"class_list":["post-33074","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-case-study","tag-data-analytics","tag-retail","technologies-avro","technologies-kafka-streams","technologies-kafka-streams-processor-api","technologies-kotlin","technologies-oracle-procurement","technologies-protocol-buffers"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.4 (Yoast SEO v23.2) - 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