The Tradeoff Analyticsâ€™ approach for making satisfying decisionsWhat makes consumers satisfied with their selections? What minimizes regrets and returns? In an investment scenario, what contributes to sustainability, to market volatility? What increases the patientâ€™s chances of sticking to a treatment, despite uncomfortable side-effects and pain? The Tradeoff Analytics tool tackles these questions and more. Decision science suggests that when making complex decisions, a thorough examination of the available options can lead to a more qualified judgment. This is exactly where the Tradeoff Analytics tool comes inâ€”it allows you to compare and explore many options against multiple criteria at the same time. This ultimately contributes to a more balanced decision with optimal payoff.
“With Tradeoff Analytics, we focus on creating net new value adds to our software versus spending time on recreating the wheel.” â€”John Shelton, CEO, SDWA VenturesClients expect to be educated and empowered: â€śdonâ€™t just tell me what to doâ€ť, but â€śeducate me, and let me choose.â€ť Tradeoff Analytics achieves this by providing reasoning and insights that enable judgment through assessment of the alternatives and the consequent results of each choice. The tool identifies alternatives that represent interesting tradeoff considerations. In other words: Tradeoff Analytics highlights areas where you may compromise a little to gain a lot. For example, in a scenario where you want to buy a phone, you can learn that if you pay just a little more for one phone, you will gain a better camera and a better battery life, which can give you greater satisfaction than the slightly lower price. The service structure is twofold:
- Tradeoff Analytics uses mathematical filtering to narrow results to the most optimal. This lets you focus on the top options without the clutter.
- It then uses various analytical and visual approaches to help you explore the tradeoffs between these options. You can add and remove objectives and see what makes it to the optimal set and why. You can prioritize according to your personal preference to emphasize certain values or objectives. Tradeoff Analytics will guide you with â€śdid you knowâ€ť kind of insights so that you will never miss out on those options that best meet your needs.
IBM Watson Tradeoff Analytics Updates since BetaWe worked with clients and partners to bring you these updates since beta:
- Categorical and date/time values – This version expands beyond our support for numerical objective values. To understand the significance of this change, consider the phones selection example that was discussed before. In this example, the brand of the phone is a categorical value. With this feature, the Tradeoff Analytics service enables editing the order (the prioritization) of the brands. The date / time data type is very useful when there is a preference for it, for example when you want to select the newest house, or want to select the nearest doctorâ€™s appointment. This feature also allows for filtering them in new UI components like in this screen:
- New Language support – The new Tradeoff Analytics version also supports nine more languages on top of English: German, Spanish, French, Italian, Korean, Portuguese (Brazil), Chinese, and Chinese Taiwan.
- More client library customization â€“ There was already feature and style customization, but now developers have control over different events that happen during the decision process. This enables them to tap in at different stages of that process and input custom behaviors.