{"id":68419,"date":"2024-01-26T14:49:40","date_gmt":"2024-01-26T13:49:40","guid":{"rendered":""},"modified":"2024-01-26T15:12:40","modified_gmt":"2024-01-26T14:12:40","slug":"optimising-business-operations-through-ai-powered-solutions","status":"publish","type":"post","link":"https:\/\/cm-edgetun.pages.dev\/en-gb\/industry\/blog\/cross-industry\/2024\/01\/26\/optimising-business-operations-through-ai-powered-solutions\/","title":{"rendered":"Optimising business operations through AI-powered solutions\u00a0"},"content":{"rendered":"\n

As powerful new AI solutions increasingly catch the attention of business decision-makers, Gartner has recognised Causal AI as a rising star<\/a>. Unlike traditional machine learning, which mainly predicts, Causal AI enables you to tackle previously unattainable \u201cwhat-if\u201d questions, creating new links between decision-making and ROI. <\/p>\n\n\n\n

\"causaLens<\/figure>\n\n\n\n

causaLens is at the forefront of Causal AI innovation, providing solutions through the Microsoft marketplace that help organisations move beyond existing predictive models.  <\/p>\n\n\n\n

In this third of our four-blog series, we’ll explore how causaLens has productised Causal AI to reimagine problem-solving across supply chains, customer journeys, manufacturing processes and more.<\/p>\n\n\n\n

AI that answers your business questions <\/h3>\n\n\n\n

\u201cIf I increase the price of my product by 5%, how will that affect my customer retention rate and revenue?\u201d <\/em> <\/p>\n\n\n\n

Standard machine learning struggles to provide answers to certain business questions, due to its tendency to forecast outcomes. The power of Causal AI models, which are fully transparent and explainable, is that they capture underlying causal relationships in data, not mere data correlations. This enables them to respond confidently to hypotheticals and provide actionable recommendations to optimise your business KPIs.  <\/p>\n\n\n\n

While recent years have seen growing academic interest in this emerging technology, causaLens is the only company to have productised it through the decisionOS platform. <\/p>\n\n\n\n

Find decisionOS on the marketplace<\/a><\/div>\n\n\n\n

Workflows built to answer \u201cwhat-ifs\u201d <\/h3>\n\n\n\n

decisionOS lets you build and deploy decision workflows leveraging Causal AI \u2013 going from raw data to a production-ready decision-making application seamlessly. Data scientists can use decisionOS to access the latest Causal AI algorithms and build best in class Causal AI models. Business users can access “decisionApps” deployed within decisionOS to surface actionable recommendations for their use-cases and improve decision-making.  <\/p>\n\n\n\n

Using decisionOS, your team is empowered to build models that go beyond correlations and understand cause and effect relationships that can predict accurately, but, more importantly, assess the impact of interventions and counterfactuals. <\/p>\n\n\n\n

decisionOS tracks decisions from data, to recommendation, to ultimate outcome and reports that back in the KPIs which your enterprise cares about That way, you can track success by the value-generating decisions you make, rather than technical metrics like model accuracy. <\/p>\n\n\n\n

Buy better outcomes <\/h3>\n\n\n\n

According to Forrester, marketplaces for SaaS sourcing help alleviate issues such as SaaS sprawl, excessive cost and security risks \u201cwhile still supporting business-led purchasing, which contributes to increased business agility, better business outcomes, and improved employee experience.\u201d <\/sup>(Source: The Forrester New Wave\u2122: SaaS Marketplaces, Q2 2020<\/a>.)<\/p>\n\n\n\n

That\u2019s true for causaLens, which has seen customer ROI across a range of use-cases:  <\/p>\n\n\n\n