1. Raw data in all its enormity is of little use to the business. How do you recommend that this be streamlined into an effective tool?

The key to the effective use of raw data is to first have your goals outlined clearly, and from those goals, determine your objectives - the methods you plan to use to achieve those goals - and the assessment tools to measure the success of these methods and any areas of improvement. Raw data is best used as an assessment tool and can be applied to front-end, formative and summative evaluation. But again, the key is for the business goals and customer service goals to drive the evaluation tools, which are ultimately the ways data is collected and which data to collect.
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2. How can this data be managed effectively to give customer services teams the insight they need to do their jobs better?

While it may be interesting to customer service teams to find out the specific raw data, what will really help them in their jobs are the conclusions one draws from analyzing that data. I suggest having an employee who analyzes the data and writes summary reports. For example, call center managers don't need to know how long each customer waits to speak to a representative. However, they do need to know what the average wait time is and the target wait time, and the range of times when wait times exceed the target time so they know to increase their staffing during those hours.
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3. How can this data be managed to stream across all business silos? Do you think it should be?

I think it should be. Again, it's a matter of sharing summary reports and writing up conclusions that explain how the information collected impacts the various silos. When businesses are too segmented and isolated in their operations they tend to reproduce a lot of the same work because they don't communicate with each other about what they are working on, which is a waste of time, money and resources. Plus they tend to forget the overarching goals of the company and focus on their departmental goals, which can sometimes come into conflict. The values of a business need to be the guiding force of every department in a business, not just in how they interact with their customers but in how they work together and treat one another.
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4. How can so much data be managed? What do you think are the primary considerations when determining the value of this data?

Goes back to question 1 and whether the data reveals the success of the business and customer service goals, and can help direct how to move forward.
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5. What plan of action do you follow when it comes to this data?

I feel I answered part of this in question 1 again. But one thing I didn't mention is that a company should try to predict to the best of its ability all the types of info they may need to collect and to use industry-specific database software that can produce reports based on those different data fields. Often the company that produced the software spent years trying to predict the kind of data that would be beneficial to collect and related reports. When I use such software, I fill out all fields offered unless I am certain that the information is irrelevant to my needs. However, if there is any chance it could be relative eventually, I include the information because you never know when it may come in handy to have that data and its much easier to just do the extra work up front than to try to recreate old data, and in some cases it is impossible. As much as as you can automate would also be helpful so you do not have to rely on manpower and deal with an unnecessary amount of human error.
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6. Any thoughts or additional pointers?

If the business can afford to have a full time staff member analyzing the data, I would recommend this, since an insider would have a better understanding of the business culture what the business really needs to succeed. This person should attend meetings with all the different business silos to ensure he or she has the bigger picture of the business in mind while analyzing the data. However, if you can't hire your own data analyst, there are consultants who are familiar with your industry and database software, who can recommend reports that would be beneficial to your particular business and explain how to interpret those reports.

Also, in reading the reports, trends are typically more important than individual data, and when you see a change in data trends, focus on the point of change and what may have caused it. If you can isolate the cause of the change, you can then capitalize on the cause (if it was good) or fix it if it has been problematic.
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