Putting Data to Work Using Self-Service Integrated Analytics

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I’ve been creating business intelligence (BI) solutions and platforms at Intel for 16 years – and I’m as excited about our most recent BI analytics project as I’ve been about any project we’ve ever done. We have created an Integrated Analytics Hub (IAH) that is connecting disparate data sets and providing self-service BI to Intel’s sales and marketing organizations – ultimately transforming how Intel’s business operates. You can read our recent white paper to learn the details of the solution architecture – in this blog, I want to share some success stories that illustrate the amazing business value provided by the IAH.

Gauging Digital Marketing Impact

Intel engages in a wide variety of digital marketing activities. Some are paid digital ads. Others are through social media, both with and without video. Some are through search engines. We collect data about all these campaign activities, but the data we collect comes in different forms due to varying sources, types, and protocols. Our Integrated Digital Marketing Analytics (IDMA) solution, built on the IAH platform, provides the sales and marketing organizations with a holistic view of digital marketing activities. Through visualizations and dashboards, analysts can compare campaign performance and tactics against benchmarks. Using this data, analysts can determine that certain creative ads work better than others. The sales and marketing organizations can then use this knowledge to shift spending to the most effective channels. The end result is cost savings: we estimate that using the IDMA solution saves Intel at least USD 170,000 per quarter.

Identifying Customers Ready for the Next Step

Part of our overall strategy for the IAH is to establish a data catalog that connects all our data sets. For example, the data catalog includes data from the marketing automation system and our customer relationship management (CRM) system. Analysts in the sales and marketing organizations can use self-service BI tools and apply data transformations to the available data. Recently, one of the business analysts in the marketing group decided to correlate the data associated with specific customer accounts against information about when and how those customers communicated with Intel. Based on the resulting reports, the analyst identified a customer that appeared ready to move to the next step in the sales pipeline – but that customer wasn’t covered by a sales rep. The analyst alerted the appropriate sales personnel, and the result was a half-million dollar design win on an account that could otherwise have easily slipped through the cracks.

Accelerating the Democratization of Data

As with all IT shops, we constantly face the challenge of doing more with less. Our mantra rarely varies from “reduce cost, increase velocity.” To this end, we have fully adopted self-service BI analytics as a critical strategy. We want to get IT out of the business of manually building dashboards and reports, and put that power into the hands of the users. IT can then focus our resources on making data available so it can be easily connected and mined for value by anyone, including both business groups and IT.

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The BI technology stack that we’re using in the IAH exposes the content in multiple formats (including relational views, multidimensional cubes, in-memory models, and raw data files), and is agnostic to front-end tools – analysts can use their favorite analytics tools to explore the data. Being tool-agnostic is important, because the ecosystem of analytics tools is rapidly evolving, and our IAH shouldn’t stand in the way of adopting the latest and greatest tools.

The response of the business is, in a word, amazing. Our active self-service business user population has grown 5x, from 289 active users in 2013 to over 1,500 active users in 2014. Query executions numbered about 200,000 queries in 2013. At end of 2014, that number had multiplied 18 times, to 3.6 million queries. The trend continues, with the system now handling millions of queries per month in 2015.

The IAH has fully enabled the democratization of data, and is transforming sales and marketing into a data-driven business. So much so that currently three out of every four (more than 70%) of the business analysts in Intel’s sales and marketing organizations are self-serving themselves to BI data – far higher than the industry average cited in various online white papers. 84.4% of all of our analytics queries by our sales and marketing users are via self-service. In other words, we have successfully achieved democratization of data and have fully instituted self-service BI – compared to an industry average adoption rate of only about 22%, according to a study by Logi Analytics. It’s truly exciting to see this sort of growth.

What’s Next for BI at Intel?

Intel is successfully responding to the deluge of data – democratizing it while enabling analysts to use their favorite tools to make better business decisions. As described in our white paper, “How Intel IT’s Integrated Analytics Platform Helps Sales and Marketing,” the reason for our success rests on two key pillars: making data readily available and easily understood.

Now that we have the IAH in place, we’re working to automate the process, such as creating real-time alerts and predictive algorithms to identify the best engagement channel or content or other aspects that seem to be most important to predict design wins.

Now that I’ve shared our story, I’d be very interested in hearing what other BI architects are doing to democratize data, build self-service BI portals, and drive adoption across the enterprise. Feel free to share your comments with me and join the conversation at the IT Peer Network.