Google Cloud AI vs. Oracle CPQ

Google Cloud AI is a wonderful product for companies that are looking to offset AI and ML processing power to cloud APIs, and specific Machine Learning use cases to APIs as well. For companies that are looking for very specific, customized ML capabilities that require lots of fine-tuning, it may be better to do this sort of processing through open-source libraries locally, to offset the costs that your company might incur through this API usage.

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I think CPQ had worked so well for our company because of the widespread nature of our associates and tracking orders that were being placed in multiple time zones. My team specifically needed a way of analyzing these orders to track our progress in real time and sort out any supply orders before they became an issue. If you are in a centralized location with a smaller team then this may not yield much use to you.

Incentivized

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• good conversion from the voice to the text
• speed in the conversion from voice to text
• time-saving in the conversion activity
• analysis of the results of the conversion in real time

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• Leveraged automation to minimize headcount costs despite 10% year-over-year business growth, and enabled staff to focus on more strategic tasks.
• Established a flexible CPQ system that scales on demand to easily accommodate the company’s multiple global locations.
• Improved customer relations by reducing configuration time and allowing sales more time to meet with customers and close orders.

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• Some of the build in/supported AI modules that can be deployed, for example Tensorflow, do not have up-to-date documentation so what is actually implemented in the latest rev is not what is mentioned in the documentation, resulting in a lot of debugging time.
• Customization of existing modules and libraries is harder and it does need time and experience to learn.
• Google Cloud AI can do a better job in providing better support for Python and other coding languages.

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• Significant setup time, cost, and maintenance. We have to use an implementation partner
• Does not always play well with other software, even Oracle software. While this is improved and being further improved, that it was a third party acquisition means things sometimes require a little extra care
• Additional setup documentation and first walkthroughs would be helpful, especially if it was all in one place

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We are extremely satisfied with the impact that this tool has made on our organization since we have practically moved from crawling to walking in the process of generating information for our main task to investigate in the field through interviews. With the audio to text translation tool there is a difference from heaven to earth in the time of feeding our internal data.

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So far it is all good with BigMachines, looking for new features since Oracle acquisition has created a lot of expectations. We have outlined our limitations (out of box functionality) in our periodic customer successor advice meetings for a while, hope we get a resolution soon. Also, the BigMachines user license fee has increased a lot in the last three years.

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I give 8 because although it´s a tool I really enjoy working with, I think Google Cloud AI's impact is just starting, therefore I can visualize a lot/space of improvements in this tool. As an example the application of AI in international environments with different languages is a good example of that space/room to improve.

The software UI can be as complex or as simple as you need it to be (depending on the business). It does require training others on quote configuration and the order in which to build out order positions prior to configuring a quote. Once users are trained;however, it is fairly straight-forward. The UI is still more static than other new wizard/drag-and-drop models, but it get's the job done

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Other than one day two years ago and an hour or two a few times since then due to data center outages, it has been very reliable

It depends upon the day however there are so many failure points with online services, including our internet service, that this is probably closer to 9 with the latest version

Every rep has been nice and helpful whenever I call for help. One of the systems froze and wouldn't start back up and with the help of our assigned rep we got everything back up in a timely manner. This helped us not lose customers and money.

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Some specific support personal was good and fixed some problems fast using proper solutions. But when one of them went to sleep when we had critical issues and they do unreported commits to our production environment which caused issues and they were hiding it?? you can not give more than a two (maybe even that is too much). They also failed to add a feature for us which also bring the grade down.

They have pretty good training. Our business analysts have been able to go to entry and advanced level training. They have a train the trainer model. Our business analyst attended training, then trained the rest of our staff.

In fact, you only need the basic tech knowledge to do a Google search. You need to know if your organization requires it or not,. our organization required it. And that is why we acquired it and solved a need that we had been suffering from. This is part of the modernization of an organization and part of its growth as a company.

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It was a much more technical implementation than we thought. It involved much more code.

Future releases have made and will make administering the tool easier.

EDL consulting had one good developer, but when he was moved off, they were horrible to work with.

The BMI sales team does a “BOA” or a “Business Operation Assessment” which is extremely valuable, not only for them to scope an implementation and get more reach within the organization, but it is also a documentation of business process that most organizations don’t have. It highlights inefficiencies and allows for correction during implementation.

Having a dedicated team (in-house) for implementation is key

These are basic tools although useful, you can't simply ignore them or say they are not good. These tools also have their own values. But, Yes, Google is an advanced one, A king in the field of offering a wide range of tools, quality, speed, easy to use, automation, prebuild, and cost-effective make them a leader and differentiate them from others.

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Oracle engagement is ahead. They are active in the development of the tool and provide great support after implementation. They also listen to their customers and offer opportunities to feedback and provide input through activities like the customer advisory board forum.

• Artificial intelligence and automation seems 'free' and draws the organization in, without seeming to spend a lot of funds. A positive impact, but who is actually tracking the cost?
• We want our employees to use it, but many resist technology or are scared of it, so we need a way to make them feel more comfortable with the AI.
• The ROI seems positive since we are full in with Google, and the tools come along with the functionality.

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• Increased Sales Rep efficiency. Being able to create multiple quotes ACCURATELY and quickly was a game changer.
• Large implementation time. It's a little difficult to fit BMI into a SCRUM style build, with multiple working models and prototypes of all 3 simultaneously.
• A larger fee for licensing and implementation cost. ROI wouldn't be realized in the first year.