From AI-powered customer interactions to predictive insights that shape operations, artificial intelligence is reshaping the way businesses operate. Yet, these capabilities are only possible with a sustainable data strategy and a robust, enterprise-ready data platform. The quality, accessibility, and structure of data directly influence the effectiveness of any AI application.<\/p>\n
Yet, many businesses struggle to make the leap from data to AI as they deal with siloed data, a fragmented data infrastructure and manual data storage that doesn\u2019t provide a holistic view of their operations. This not only makes compliance and reporting difficult but also prevents you from getting started or even experimenting with AI applications.<\/p>\n
So how can your business overcome these challenges? We helped three leading Australian businesses overcome common data challenges and create AI-ready platforms. This blog gives you a quick overview of these success stories.<\/p>\n
A connectivity and communications technology group<\/strong><\/a>: Bridging the past and the future <\/strong><\/p>\n Wanted: A modern AI-ready enterprise analytics platform<\/strong><\/p>\n Data analysis was becoming increasingly difficult; the team relied on manual files to store data and there was no platform for diagnostic analytics. The company was upgrading its legacy ERP system by implementing Infor CloudSuite to address these challenges.<\/p>\n The Fortude transformation<\/strong><\/p>\n An AI-ready business<\/strong><\/p>\n The new platform is extensible and ready for predictive AI-based scenarios. By consolidating data into a single source of truth, the company eliminated redundancy. They also automated dashboards, replacing cumbersome manual tasks. The sales and finance teams have near real-time data. Plus, thanks to the fast implementation, critical reports were ready from day one of the CloudSuite deployment. They\u2019re now expanding AI-driven automation for further operational efficiency.<\/p>\n Customer comments<\/strong><\/p>\n \u201c<\/strong>In just three months, Fortude successfully advised on and implemented a Data Lake foundation, integrated it with our M3 multi-tenant environment, and established the business analytics required to support key decision-making processes.\u201d<\/p>\n A leading Australian furniture retailer:<\/strong><\/a> Scaling business intelligence<\/strong><\/p>\n Wanted: A sustainable data strategy<\/strong><\/p>\n Fragmented data sources created many problems. There were inefficiencies as a result of data silos and manual storage, manual reconciliation of sales data, and Power BI lacking governance controls. Getting near real-time analytics was difficult because the BI system needed a daily ETL refresh. Furthermore, there was no long-term enterprise data strategy to provide guidance.<\/p>\n The Fortude transformation<\/strong><\/p>\n An AI-ready business<\/strong><\/p>\n This has improved business agility with near-real-time capabilities, reduced IT dependency through secure self-service analytics, eliminated data silos through a single source of truth and unified reporting, and improved resilience. Plus, the data platform is scalable because of its cloud-native architecture. The company is now looking to drive AI-driven automation and expand analytics throughout its finance and supply chain functions.<\/p>\n Fortude was recognized as the winner of the Digital Transformation Award for APAC by AICPA & CIMA, 2024, and the Data Solution implemented for this company was a key case study included in the entry.<\/em><\/p>\n The brand distributor:<\/strong><\/a> Creating a data-backed strategy<\/strong><\/p>\n Wanted: A single source of truth<\/strong><\/p>\n There were many data inconsistencies as teams relied on siloed, manual data collection processes. These outdated practices didn\u2019t generate any near real-time analytics or enable self-service analytics for critical business functions. Most importantly, this was neither a sustainable nor future-ready data strategy, because it was difficult to access a holistic picture of operations and identify trends.<\/p>\n The Fortude transformation<\/strong><\/p>\n An AI-ready business<\/strong><\/p>\n The company reduced data reconciliation times, improving both operational efficiency and cross-functional team collaboration. Self-service analytics facilitated real-time data access to drive key marketing, supply chain, and decision-making functions. Overall, there\u2019s higher trust in the data collected as there\u2019s more consistency when a single source of truth is in use. The company is now expanding its analytics capabilities to other teams while automating supply chain, sales, and logistics functions with Microsoft Power Platform.<\/p>\n Customer comments<\/strong><\/p>\n \u201cThe assessment was super critical because it allowed us to take a step back and really analyze our value chain and where those key pain points were for us. What came out of it is a set of really strong recommendations…\u201d<\/p>\n At times, businesses may feel inundated with data\u2014consumer interactions, sales trends, finance and operations, and marketing performance. We must first organize the data that we have if we\u2019re to leverage AI applications. At Fortude, our work spans many businesses that are keen to get started with AI adoption but lack the critical foundation to do so i.e. a sustainable data strategy.<\/p>\n Fortude\u2019s accelerators, cloud-native architecture, and strategic assessments empower you with the essential technology kit to get AI-ready. To understand how AI-ready you are today and plan for your business\u2019s future, get in touch with us<\/a>.<\/p>\n","protected":false},"featured_media":14510,"template":"","meta":{"_acf_changed":false,"content-type":""},"industry":[14,13,11,16,12],"service":[30,74],"class_list":["post-10527","blog","type-blog","status-publish","has-post-thumbnail","hentry"],"acf":{"blog_render_type":"legacy_acf","sections":[{"section_title":"Introduction","section_content":"From AI-powered customer interactions to predictive insights that shape operations, artificial intelligence is reshaping the way businesses operate. Yet, these capabilities are only possible with a sustainable data strategy and a robust, enterprise-ready data platform. The quality, accessibility, and structure of data directly influence the effectiveness of any AI application.\r\n\r\nYet, many businesses struggle to make the leap from data to AI as they deal with siloed data, a fragmented data infrastructure and manual data storage that doesn\u2019t provide a holistic view of their operations. This not only makes compliance and reporting difficult but also prevents you from getting started or even experimenting with AI applications.\r\n\r\nSo how can your business overcome these challenges? We helped three leading Australian businesses overcome common data challenges and create AI-ready platforms. This blog gives you a quick overview of these success stories.","section_image":"","table_rows":null,"pro-tip":""},{"section_title":"Success story 1","section_content":"A connectivity and communications technology group<\/strong><\/a>: Bridging the past and the future <\/strong>\r\n\r\nWanted: A modern AI-ready enterprise analytics platform<\/strong>\r\n\r\nData analysis was becoming increasingly difficult; the team relied on manual files to store data and there was no platform for diagnostic analytics. The company was upgrading its legacy ERP system by implementing Infor CloudSuite to address these challenges.\r\n\r\nThe Fortude transformation<\/strong>\r\n\n
Success story 2<\/strong><\/h5>\n
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Success story 3<\/strong><\/h5>\n
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There\u2019s no AI transformation without data<\/strong><\/h5>\n
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