Check out this Mobile Health Marketplace article, featuring UCSF’s LogicNets-based app (developed by Dr. Robert J. Rushakoff) as one of the mobile health tools for diabetes highlighted at last year’s “Diabetes Management: Devices and Data Driven mHealth Tools” conference.
We were delighted to learn today from Lisa Beatty, HR Services NA Portfolio Manager at Ingersoll Rand, that her team has been awarded the Ingersoll Rand President’s Award for Operational Excellence for the deployment of their LogicNets-based application “MyAnswers”. With the use of the LogicNets expert system platform, valuable expertise is now available online, providing greatly improved self-service access to benefit information for all Ingersoll Rand employees nationwide, 24 hours a day, seven days a week. The success of the project means the group is considering expanding their scope to other regions this year.
We started working last year with Tulane Law School’s Elizabeth Townsend Gard and her husband Ron Gard on the Durationator — an online tool making it easier to research copyright status. Read all about it in Tulane’s New Wave news article.
We’re very pleased to announce that our decision engine platform has been selected as the core technology to power an automated synoptic reporting and diagnostic protocol system for PALGA, a Dutch-based foundation that services a nationwide network of over 50 pathology laboratories throughout the Netherlands. The contract was awarded in conjunction with ICT Automatisering (ICT), our new Dutch integration partner and a leading global provider of high-quality technology solutions.
You can read the full press release here.
We wish we’d come across this post when it was first published, but better late than never. The article – The Real Docs Need is Decision Support - by Mark Baker on his Every Page Is Page One blog describes how decision support provides a means of structuring the optimal delivery of knowledge – a point of view which is, obviously, very close to our own hearts.
The additional idea we’d like to add is that the key value underlying decision support technology is the quantitative management of the relationships between the information describing symptoms, causes, and supporting resolution resources. This means that Decision Support not only allows you to structure and automate diagnostic pathways that could be followed in applications available to agents and/or users, but it also allows for automated learning and evolution. As a result you allow users to answer questions applicable to a variety of different potential resolution pathways and have the system learn from the users’ repeated experience. For example: a user identifies his/her product’s internal networking as the problem area and the decision support system starts to ask relevant questions. As questions are answered, the user sees the most relevant probable causes and their respective probabilities. The user can keep answering questions until the probability is 100% or skip straight to an end-point and perform the recommended resolution steps to see if that doesn’t solve the issue. Once resolved, the system would factor in the final resolution pathway for future use and the organization would accumulate detailed statistics on the diagnostic results and the user experience.
So, Decision Support is much more than having an expert document his ideas at an initial point in time and structure a single recommended pathway. Rather it goes beyond to provide a self-maintaining knowledge repository that optimizes itself and reacts to changing approaches over time.
We’re amazed that some of our customers have initially balked at the idea of providing automated diagnostics to their end-users via LogicNets for fear that it would “impact” paid services opportunities. In other words, providing better, more timely service would result in lowering revenues. We understand the reluctance to threaten a pre-existing revenue source. However, we’ve always been able to demonstrate that providing web-based self-service, in fact, 1) generates many more new, fast turn-around revenue opportunities than the status quo of off-contract service calls or pay-as-you-go tech support and 2) actually increases traditional add-on revenues.
First, high quality self-service systems are themselves excellent new revenue sources, with customers and partners more often than not willing to pay a subscription fee. Second, they provide such tight control and insight into a customer’s exact situation that they enable both new and traditional add-on services to be presented dynamically at the moment they are most relevant and therefore most likely to be purchased. Finally, they satisfy the customer’s need to see for themselves that paid support is the best alternative by integrating the ultimate directive to engage the company with a preliminary set of alternative do-it-yourself steps. When properly implemented, automated self-service makes the customer feel that they have been given the chance and necessary information to find a cost-effective fix and that they are acting reasonably by ultimately engaging Support after the system has proven that bringing in the cavalry is necessary.
The real game-changer about automated self-service with a system like LogicNets is that you gain unprecedented insight into the customer’s actions and situation and you can precisely control when and how to present the appropriate information in response. In the traditional scenario when break-fix services cost extra, users obviously try to solve issues on their own. Relying on Search as the tool to find information either on the web or in your knowledge-bases, users work manually and in an ad-hoc way to troubleshoot problems. Yet the company has no idea that they are doing this or what approach they are taking… and odds are that the customer is flailing. Typically, the company’s chance to assess the situation and influence only comes after the customer has failed at their initial attempts, concluded that your support materials are worthless, and has now called you as a last resort. At this point they are completely fed up and now have to suffer the indignity of describing to your agent the whole experience they just went through. With automated self service, the customer has followed a standardized and proven process for identifying relevant symptoms, determining causes, and eliminating irrelevant factors. If the company needs to be pulled in, the user is satisfied that they have done everything they can. But even better, all their activities to date have been recorded so that the company’s agent can pick up at the next level without having to ask those annoying redundant questions of the case history. The result is always a happier customer and, it seems to us, more net opportunities to generate revenues as payment for proven proportional value.