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Oracle Sales ops transforms Business Analytics with Oracle Analytics Cloud

Divya Malik
Marketing Director

Oracle Analytics Cloud is consistently recognized as a visionary in the Analytics and BI Platforms space by Gartner, Forrester, and other industry watchers. To help us better understand the secret to that success, we talked with Francis Defilippis, Oracle’s manager of business analytics and reporting services to learn how his sales operations organization turned to Oracle Analytics Cloud about three years ago, and the results have exceeded expectations. 

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Here’s the transcript of the conversation that I had with Francis.

Divya: Francis, thanks for taking the time to speak with us today. Please tell us a little bit about yourself.
Defilippis: I’ve been with Oracle for nine years in a number of positions within sales operations, most recently serving as manager of business analytics. Like most business analysts, I’m a data geek and love to extract meaningful insights from mountains of information. That’s why this job fits me so well because our charter is to analyze data from our sales organizations and deliver accurate, relevant insights to executives in a timely way. 

Divya:  How have you executed that charter in the past?
Defilippis: Before Oracle Analytics, our primary tools were Excel spreadsheets and PowerPoint presentations. We used the spreadsheets to organize and analyze information and then presented that information to decision-makers with PowerPoint. It was a manual workflow with a lot of steps and many opportunities for errors to creep into the process.
In recent years, our executives have been requesting more and more reports and we responded by creating more and more custom spreadsheets. As a result, our spreadsheets grew in number and complexity to the point where they were difficult to maintain and use. As one example, we needed two full-time employees to generate just four reports using an array of spreadsheets. It was highly inefficient and we weren’t meeting the needs of our stakeholders.

Divya: Talk about the specific problems you encountered with the spreadsheet approach.
Defilippis: Well-designed spreadsheets can be powerful tools for business intelligence, but they have limitations. It’s hard to share data between spreadsheets, so information tends to be siloed and often duplicated, the exact opposite of what business analysts need to do their jobs effectively. Spreadsheets don’t scale well. As you populate a spreadsheet with more and more data, it eventually becomes too unwieldy and must be split up, adding to the complexity and inefficiency of our process. 
Data accuracy was another issue because of the large volume of manual data entry, a time-consuming and error-prone activity. 
But the biggest problem was the lack of centralized data. With all these spreadsheets flying around, it was hard to tell which one was the most up to date. The same information could exist in several spreadsheets, leading to synchronization problems. The bottom line was that we had no single source of truth, no one place where we could be sure the data was up to date and accurate. 

Divya: What was the impact of these problems on your ability to do your job?
Defilippis: The number one negative consequence of all that complexity was that executives didn’t trust the insights we were delivering. Even a small mistake would cast doubt in their minds on the entire analysis. Also, time is always a factor in decision-making, and because of the inefficiencies of the system, we struggled to extract the necessary insights at the pace that executives needed them. 
As our internal customers started to complain, leadership realized that it was time to act. About three years ago, they set an ambitious goal to completely transform our process for ingesting, storing, analyzing, and reporting so that both we and our stakeholders could have a high level of confidence in our insights.  

Divya: An IDC study in 2019 found that analysts spent 81% of their time managing data and only 19% on analyzing and providing insight on that data. Was that true of your organization before Oracle Analytics?
Defilippis: Absolutely. We’re trained to analyze data, not to manage it. Our analysts were spending most of their time doing things such as coding, leaving little time to actually analyze the data. 
We wanted to flip the script. One of our goals was to allow analysts to spend far more time on analysis and leave data management to others. 

Divya:  When you first evaluated Oracle Analytics, what did you see that excited you?
Defilippis: The overall feature set is pretty impressive. Oracle Analytics offers everything from self-service visualization and inline data preparation to enterprise reporting and advanced analytics. We could see right away that this platform had the potential to transform the way we deliver insights to our customers. 

Divya:You chose Oracle Analytics Cloud over the server-based version. What was your reasoning? 
Defilippis: First of all, Oracle makes it really easy to evaluate these two alternatives because the feature set is exactly the same in each one. That meant that we could focus strictly on the operational aspects of the respective offerings.There were several reasons why we went with Oracle Analytics Cloud. For one thing, using a cloud service minimizes the drain on our department’s human resources. We don’t have to worry about infrastructure issues such as upgrading servers or configuring firewalls—the hosting group at Oracle handles all those administrative tasks. Now our analysts can spend much more of their time probing mountains of data looking for actionable insights. 
In addition, migrating our users from Oracle Business Intelligence Enterprise Edition to Oracle Analytics Cloud is much more straightforward in the cloud. It scales quickly and easily compared to the server-based version, which requires lengthy procurement and installation cycles when you need to add capacity. 

Divya:  Give us an example of how Oracle Analytics Cloud adds value to your operations.
Defilippis: The self-service analytics feature of Oracle Analytics Cloud has transformed the way we turn data into insight. In the past, analysts spent a lot of time writing code to manipulate data. With self-service analytics, those operations are just drag and drop—no coding required. This feature alone has increased productivity by an order of magnitude. In addition, Oracle Analytics Cloud has an enterprise-grade dashboard with pixel perfect reporting, so analysts can trust what they see on the screen.

Divya:  What about integration? How does Oracle Analytics Cloud work with other applications?
Defilippis: This is where the power of a true platform comes in. We integrated Oracle Analytics Cloud with Oracle Autonomous Database to create an end-to-end analytics process. The autonomous database aggregates data from all over the organization. That information feeds the work our analysts do using Oracle Analytics Cloud. 

Divya: Can you say something about the Oracle Autonomous Database? Why did you choose that product over other database offerings?                                                                                                                                Defilippis: We chose Oracle Autonomous Database because it requires virtually no maintenance. The reason is machine learning, which allows the database to automate time-consuming administrative tasks traditionally performed by database administrators, for example, database optimization. 

Divya: How has Oracle Analytics Cloud transformed the way you fulfill your mission?

Defilippis: It's like night and day. Instead of a massive collection of individual spreadsheets, we now have a single source of truth that is reliable and up to date. It’s hard to overstate the importance of having everything in one place. Now our analysts can be confident they are working with the latest information and that boosts confidence for us and our customers. The increase in productivity is astounding. 

Our team is fairly small, with only one technical resource for more than 20 superuser analysts. Having a tool like Oracle Analytics Cloud has allowed us to support our data science and analyst community in a whole new way. Centralizing all our pipeline and customer utilization data in one place is truly transforming how we run our business.

Divya: Do you have any specific anecdotes or metrics you can share?

Defilippis: We had a high visibility report that was a nightmare to put together, extracting the information from multiple spreadsheets and creating a PowerPoint presentation. It literally consumed two analysts for an entire week—80 hours of staff time. Thanks to centralized data and the visualization capabilities of Oracle Analytics, we now spend just 5 hours creating that report, freeing up 75 hours of valuable analyst time for additional data analysis work. 

Divya: How are your internal customers feeling about you now?

Defilippis: We are winning back their confidence with more accurate and timely reporting. By automating data management and eliminating manual tasks, our reporting errors have dropped by 90%. Thanks to Oracle Analytics Cloud, I can now provide timely data and insights directly to Oracle’s sales management team, which enables them to make decisions quickly.


Divya:: What advice do you have for someone in your position who is considering Oracle Analytics Cloud?

Defilippis: I would point to my own experience. Oracle Analytics Cloud has completely transformed the way we deliver business analytics.  I can now provide timely information and insight directly to my sales management team, which enables them to make decisions quickly. Our business analysts are more productive and morale is higher because they’re doing the work they’re trained to do instead of jockeying Excel and PowerPoint. We can scale our capacity in minutes when requirements change. 


My message would be, if you want those capabilities for your organization, you can’t go wrong with Oracle Analytics Cloud.

Watch this webinar to hear Francis discuss Oracle’s business transformation with Oracle Analytics 


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