Infor has announced a new intelligent stock control add on application to its Healthcare SaaS solution. Named the Infor Inventory Intelligence for Healthcare (IIIH) it was developed by the Infor Dynamic Science Labs team. The Dynamic Science Labs has developed the solution to deliver recommendations using mathematical models for maintaining optimum stock levels based on the different needs of each stock location within a hospital.
The software provides parameter recommendations for replenishment every two months and supports any location that is defined within the Infor S3 application. Customer-based service metrics allows IIIH to recommend new Min/Max/Reorder points for each stock item per location every two months. Customers will be able to define what locations will use the data science.
First generation stock control systems focused solely on reorder level allowing the purchasing team to start the process of replenishment. That reorder level was normally set once in the life of the stock item and rarely updated. This new solution takes into account usage and transactions data to optimise stock levels. The brochure states: “Infor Inventory Intelligence for Healthcare incorporates algorithms that leverage your order and transaction history to actively and intelligently maintain the stock in your stockrooms.”
This may seem a simplistic but the formulae are likely to be complex. Despite the minimal number of parameters used, the mathematics quickly becomes complex in order to avoid making poor recommendations. This is not prescriptive analytics as the software merely makes recommendations for the hospital staff to consider. However for each stock location it does mean that the suggestions are likely to lead to improved stock control. For hospitals with limited storage space this is important. Overstocking can lead to the inability to store items properly within normal storage as bulky items take up too much room.
Mike Poling, senior vice president and general manager, Infor Healthcare commented: “Successful healthcare organizations understand that in order to increase profitability, steps need to be taken to better handle inventory management. There is no one-size-fits-all approach to inventory management, and it’s important to partner with an organization that is specialized, understands market trends and fluctuations, and is innovative enough to harness the mass amounts of data available today in intelligent ways to use it for making better, faster decisions tomorrow.”
Is IIIH real software intelligence?
Companies are striving to make their software more intelligent. This is not self-aware software but it is the first step towards a fully cognisant solution. On questioning Infor it became clear that the software is a first generation solution towards intelligent software. As additional parameters are added the mathematical algorithms become more complex and harder to validate. For example the software does not support rapid real-time replenishment. One argument here is that if there is a rapid depletion of inventory over a very short period then normal reorder levels can apply.
While the solution does not consider rebalancing of stock levels between internal locations, Infor are considering this for a future version. This is wise as several hospitals will have master stock rooms from which to replenish smaller more localised stores. As the software develops and the mathematics are proved in real life, data scientists will be able to introduce more variables and look at future requirements, rather than just historic trends.
John Carrico, director, product management, Infor Healthcare commented: “We don’t currently have procedure based forecasting in our application, however we see tremendous value in providing forecasting based on volume metrics: procedures, in-patient days, ER visits, RVU’s, etc. This type of forecasting is a near future item. “
When this next change happens IIIH will take a step towards predictive analytics embedded into the business logic of Infor S3. This will enable the software to start placing orders automatically. That is someway off at the moment.
Is the software proven
This is not just a piece of software written in a science lab and imposed upon business. Infor has been working with a partner over the last year to carry out proof of concept and Beta testing. The software will be showcased at Inforum later this year (July 10-13 in New York) by the data science team and Sanford Health.
Sanford Health, an organisation with 43 hospitals and nearly 250 clinics in nine states and three countries appear to have been the beta partner for the project. Whether the solution has been implemented across all their hospitals is not yet known but it will be interesting to hear more. Rial Stedman, Directory of Inventory management at Sanford Health is due to present alongside Dynamic Science Labs Director Leigh Martin and data scientist Dawn Rose at the event (LAWS-441C).
This is an add-on to the existing Infor S3 suite rather than an update. By making it an additional cost item it might just put off some health who were considering Infor for their hospitals. Despite this it is an easier product to determine a return on investment for the solution. It will be interesting to hear whether Sanford has considered the cost benefits of the data science based solution and actually carried out any metrics.
Benefits will both be tangible in terms of a reduced procurement spend and intangible in terms of better space planning capabilities. One hopes the former have been calculated while the latter benefits will be interesting to hear from Sanford Health direct.
Software companies are racing towards delivering software intelligence. NetSuite recently announced Intelligent Order Management at SuiteWorld and it seems that Infor are the latest to join the “Intelligent” bandwagon. It is questionable whether either of these solutions provide the software with intelligence. What they do show is that software companies are starting to embed analytics within business logic rather than having them as add on solutions providing intelligence. This is a first tentative step towards software intelligence and it needs to be taken.
What is interesting about the IIIH solution is that the data science used will be applicable across a range of vertical industries. Data Science labs normally select an industry vertical to get a solution off the ground and into the real world. Once successful they look to modify the algorithms for other verticals such as Manufacturing, Aerospace and other Infor verticals. While healthcare is the first industry that has taken advantage of these new algorithms there will be other industries who are very interested in improving their stock control using this science.