We are in healthcare, and the supply chain can be a fragmented process, and now with the Pandemic quite fragile. In recent years, companies have been implementing leaner supply chains to reduce their costs. We found that our best approach to dealing with supply distributions was to create a partnership with a distributor who could provide us with a very large percentage of our day-to day-supplies. We have Central inventories in each of our hospitals; however, we use a stockless operation Monday-Friday. This means we fill supplies for our nursing units on the weekends, but during the week, the distributor is picking, packing, and shipping those supplies in a low unit of measure. Orders are placed electronically by noon daily, and start arriving by late evening. A 'back order' list is sent to us each workday in the late afternoon - too late to do anything with it.
We did work with our distributor to develop a more customized spreadsheet that detailed each item, by hospital and delivery location. Each following day we would break the file down so that we could e-mail it to each area, to get feedback from them on critical needs. This took our resources time to prepare and send the next morning. Staff getting the information didn't have much time to review and respond. In addition, we would update each PO line item with the revised 'due date', for back-ordered lines - this was a manual process. This same resource would then use a tool to send each requestor a 'delayed delivery' e-mail notice. The overall PO update and communication process took an additional 1-2 hours a day in staff resource time.
With the robot doing this work for us, the vendor sends a file to an address by a certain time. They send it in at about 3:30 PM every day. The robot now takes that file and works that file, which it has ready for us usually by 4:30 PM. Now, it still may be too late for us to work, but the first thing in the morning, we have the file, and the Bot has already sent out notifications to all the users of any backorders. First thing, when they walk in the morning, they know what their backorders are. They didn't know that until halfway through the day before. Now, they get the information first thing in the morning so they can react. Now, we are getting the information first thing and have the time to work with the manufacturers and distributors to come up with other products so that we might backfill or get a branch transfer.
Our end goal was to make sure that we had a daily tool that was 100 percent accurate and could be deployed across a broad spectrum of healthcare workers. Then, they could get information faster and more accurately with as much information to eliminate a lot of extra calls and communication. That is what we embarked on. We dissected our current process and looked at all its different triggers to see how we could turn this into an automated tool. We broke down our process and identified everything that we were doing, then UiPath helped us identify what we needed to modify. We worked that into a tool where a Bot could come along and process it every day, then deliver every afternoon. That was our end result, and it's been extremely successful. We started using the tool last December.
We combined some automation that we already had in this process into this tool to make it a whole automated process, rather than partially bringing it under. We have a vendor who delivers us a report daily of all their backorders because we use the main distributor, so they deliver us a backorder report. Therefore, we made sure that they aligned it in a way that the robot could read it. Then, we wanted to break that down in a way so each of our hospitals could see their section. So, we added some data to this tool which allowed the robot to see that record, and say, "This belongs here, and this belongs here."