{"id":2900,"date":"2022-05-10T15:17:23","date_gmt":"2022-05-10T19:17:23","guid":{"rendered":"https:\/\/muutaa.com\/?p=2900"},"modified":"2022-05-11T22:38:03","modified_gmt":"2022-05-12T02:38:03","slug":"expect-the-unexpected-identifying-outliers-in-your-supply-chain","status":"publish","type":"post","link":"https:\/\/muutaa.com\/fr\/expect-the-unexpected-identifying-outliers-in-your-supply-chain\/","title":{"rendered":"Expect the Unexpected: Identifying Outliers in Your Supply Chain"},"content":{"rendered":"

By Barry Holleman<\/p>\n

As a healthcare supply chain professional, you want to support your organization\u2019s strategic imperatives by becoming more agile, precise, and proactive<\/a>. You understand the impact your department can have on improving cost, quality, and satisfaction, but too many visibility gaps stand in your way. You know outliers exist within your vast ecosystem that drive expenses up, but your team lacks the time and resources to find and resolve them before it\u2019s too late, when the invoices are due.<\/p>\n

Sound familiar? When it comes to the supplies and medications your clinicians and patients use, it\u2019s important to know what\u2019s going right, but\u00a0imperative <\/em>to know what\u2019s going wrong. We frequently hear about the challenges of\u00a0 identifying and correcting for outliers in our conversations with supply chain leaders, and for good reason. Outliers \u2013 or exceptions to what is expected and forecasted<\/a> \u2013 can cause all sorts of induced errors in the system and can be quite costly.<\/p>\n

In complex systems, with disparate data sources it is hard to find outliers with basic statistical modeling tools such as spreadsheets. These are not only labor-intensive, slow, and limited in scope, they are also prone to errors in data entry and scaling. Such errors can lead to unseen outliers in some places and exaggerated outliers in others.<\/p>\n

Time is of the essence, so you need timely insight. What good does it do to find out from an invoice that a $30,000 device was ordered for one surgeon, while the rest of the surgical team uses a $10,000 device for the same procedure with great outcomes? Likewise, shouldn\u2019t you have a way of knowing before <\/em>you order if the price is significantly increasing, or if a stockout is likely because of current or impending spikes in demand? And, if there are issues in product delivery, you might not be able to ensure the same continuity in care if you can\u2019t spot the problem in time.<\/p>\n

Tech-Enabled Decision Support for Healthcare Supply Chains<\/strong><\/p>\n

Unless your team is overflowing with time and resources (which would make you quite an exception in your own right), you can\u2019t identify outliers accurately with human-led calculations and observations alone. You need artificial intelligence and machine learning to amplify human intelligence. In other words, you still make the decisions, but smart technology unlocks the information you need to make the right choices at the right times, every time.<\/p>\n

Fortunately, the technology is here and readily available. You won\u2019t find it in an ERP or other information system because today\u2019s IT systems lack the capabilities to show outliers proactively, especially on rapidly changing data points like price variances. The holistic, timely view you need requires specialized software capable of integrating and scrutinizing all relevant data sources (clinical and financial<\/a>), performing checks and balances, and providing alerts and alarms in an analytical dashboard that make it easy for you to make\u00a0 short-term corrections and impact future decisions for the thousands of products and players in your supply chain.<\/p>\n

l'application DemandAMP+<\/a> provides all that functionality and more. Developed exclusively for healthcare supply chains and available as a secure, cloud-based IA en tant que service<\/a> solution, DemandAMP+ provides the visibility you need to see and address outlier concerns over the next week, month, and year. This intelligent automation fuels better decisions with an easy to understand traffic light dashboard that indicates the severity of the outlier (red, yellow, and green \u2013 with red indicating urgent action is needed). As a result, you can:<\/p>\n