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    Augmented Analytics Q/A

    We hosted a webinar explaining the ins and outs of augmented analytics, including how JAGGAER is helping users along the path. We received dozens of audience questions, so the webinar hosts, Mike Roberts and Amenallah Reghimi, have provided answers to some of our favorites.

     

    To get all the details on augmented analytics, watch the webinar recording.

     

    1. What are augmented analytics?

    a. Amenallah: Augmented Analytics transform how our customers explore, analyze and act on the automated insights generated by JAGGAER One. Augmented analytics, by contrast, is built on the principle of self-service by business users. The intelligence is already pre-programmed (embedded) and continuously learns as the data changes. Augmented analytics solutions are built out of the knowledge of domain experts (for example, JAGGAER customers and software development teams) who understand the business (and regulatory etc.) frameworks and who anticipate future changes – in order to get away from heavy reliance on IT.

    2. Why do augmented analytics matter?

    a. Amenallah: Augmented Analytics facilitates the access to the insights and helps the users to better understand the data and be more proactive. Now that insight is actionable because it connects directly to an action you can take to solve your business problem. These actionable insights are extremely helpful because they serve as a guiding light for what you should prioritize in your business. The best thing about augmented analytics is that it sees what you see but also sees what you don’t see.

    3. Is there a minimum volume of data an organization needs to have in order to use augmented analytics efficiently?

    a. Mike: Typically for AI and machine learning, we talk about it in the context of big data. But it’s really a matter of quality over quantity. A lot of these approaches are just about looking at the data you have, identifying outliers and accounting for them, which really doesn’t need that much data. Some use cases for predictive analytics and AI for spend analysis will be dependent on having more data, but there isn’t a specific threshold. Instead it’s that the more data you have, and the more accurate it is, the better off you are.

    4. How does the system ensure the quality of the underlying data?

    a. Amenallah: There are several ways of this. One is making sure that the data entered in the system is structured and clean, this is done in two ways. First is by making sure that there is a guided approach when asking users to enter data into the platform, and second is when getting data from the outside making sure that we have ways to classify and structure that data. We can do this via machine learning, intelligent classification systems, workflow systems for validation and other avenues. By ensuring that the data is clean, relevant, structured, and can be classified we can be certain that the data is of good quality.

    5. What are the impact results using analytics in our procurement process?

    a. Mike: One major benefit is being able to more accurately forecast your spending. With predictive analytics, it becomes easier to see trends, both past and future, of where your money will be going. That makes it easier to set budgets and manage your categories.

    b. Amenallah: Another advantage is democratizing information. Mike opened the webinar with some slides about data visualization, which makes your metrics easier to understand at a glance and share with stakeholders. But I also talked about conversational analytics and the chat bot, which lets anyone on your team ask for information in plain language and get results instantly. Team members can get their own information quickly without having to go through a business information team. That’s perfect for different roles who want a different data experience.

    6. How can the predictive analytics tool deal with sudden trend changes, like the current COVID crisis?

    a. Mike: The situation we’re in right now is completely unprecedented, so ultimately, it’s extremely difficult to make predictions. As we said, a lot of the predictive analytics tool relies on your previous data, so it’s difficult to use in a completely new scenario. But that’s part of why we allow you to manually adjust some of the parameters. As we showed during the webinar, you can add adjust prices and demands for certain goods if you think they might increase or decrease. The predictive analytics tool can then take those factors into account when it calculates predictions.

    7. Does the way an organization uses the platform today dictate the ability to use these analytics? Do you have to have specific JAGGAER modules already in place before implementing advanced analytics?

    a. Amenallah: We have built pre-designed dashboards that can enable a customer to be able to use this out of the box, they can then build on top of that platform and customize this for their needs. The interface is a very simple but effective ‘plug and play approach’. It is important to note however that we are not an analytics solution provider, we are a procurement solution provider. So, the answer is that yes, the analytics are tied to JAGGAER modules and the JAGGAER platform, but these analytics are incredibly powerful and user-friendly to set up.

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