Monthly Archives: August 2014

How the Mobile Brain Alters Customer Relationships

August 27, 2014

Big data collection and analytic technology is of increasing importance in a world that is now more digitally-oriented than interpersonally connected. There are at present 1.75 billion smartphones in the world – nearly one-quarter of the global population uses a smartphone.

And due to the accessibility, context and immediacy that consumers are afforded in an interconnected mobile world, consumer behaviors have already started to change. 77% of users now use their phone to research products or services, and 64% have connected with a business. Consumers have higher expectations of mobile interactions because apps like Google Now proactively present relevant, contextual content. Even business models have been transformed by the immediacy demanded in a mobile world – Uber is a prime example.

What does this mean for businesses employing data-driven marketing techniques to improve communications and customer experience?

It means marketers have to step up their game in real-time interaction management and mobile analytics. Organizations that harness the mobile transformation are tapping into its pervasiveness and the growing network of connected sensors all around us in order to better understand and even predict what customers need next. This kind of data-driven marketing is the new basis of competitive advantage, and as consumers interact over a growing number of devices, integration of those cross-channel experiences is paramount. It’s not just mobile for mobile’s sake – it’s the mobile augmentation of the overall customer experience.

One company driving new insights from mobile data is, a Teradata customer. The world’s second-largest automotive classifieds website, recognized the need to capture, integrate, and drive insights from the more than one terabyte of information that its 11 million monthly users generated. That gave them a better understanding of how customers were behaving in order to present the right message, at the right time, in the right format.

One of these key insights came when used geospatial data to marry mobile location with web behavior. “We’re beginning to provide interesting metrics about how many people are searching within 1 mile of their dealership – which basically could mean we’ve got people on their lot looking up basic information about vehicles looking at,” noted Kevin Wyderka, Director of Business Intelligence & Data Warehousing. This ultimately led to a better mobile customer experience and a selling point to advertisers.

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If you’re interested in this topic and want to learn more, then we’re in the same boat. I’ve partnered with Bob Garcia at Urban Airship, a leading mobile technology company, and submitted a session for SXSW Interactive 2015 in Austin, TX where we hope to get enough votes to be able to really bring this topic to life next March.

Will you help me get Teradata on the event agenda?

Click here to vote and help get us there to talk about some really game-changing stuff in the digital marketing spectrum. Thanks!

00-11-lummuscropMichael Lummus leads digital marketing solutions at Teradata. A thought leader on the convergence of digital & traditional marketing, he frequently speaks at industry events held by the Direct Marketing Association, Gartner, Automotive News & others. Michael has had roles as Senior Product Manager at Acxiom, Director of Marketing at Michael Smith & Associates, & founded Sonus Marketing, a marketing agency & provider of ad buying technology.

Real-Time SAP® Analytics: a look back and ahead

August 18, 2014

On April 8, I hosted a webinar and my guest was Neil Raden, an independent data warehouse analyst. The topic of the webinar was: “Accessing of SAP ERP data for business analytics purposes” – which was built upon Neil’s findings in his recent white paper about the complexities of the integration of SAP data into the enterprise data warehouse. The attendance and participation in the webinar clearly showed that there is a lot of interest and expertise in this space. As I think back about the questions we received, both Neil and I were surprised by the number of questions that were related to “real-time analytics on SAP.”

Something has drastically changed in the SAP community!

Note: The topic of real time analytics is not new! I won’t forget Neil’s reaction when the questions came up. It was like he was in a time warp back to the early 2000’s when he first wrote about that topic. Interestingly, Neil’s work is still very relevant today.

This made me wonder why this is so prominent in the SAP space now? What has changed in the SAP community? What has changed in the needs of the business?

My hypothesis is that when Neil originally wrote his paper (in 2003) R/3 was SAP (or SAP was R/3 whatever order you prefer) and integration with other applications or databases was not something that SAP had on the radar yet. This began to change when SAP BW became more popular and gained even more traction with the release of SAP’s suite of tools and modules (CRM, SRM, BPC, MDM, etc.) — although these solutions still clearly had the true SAP ‘Made in Germany’ DNA. Then came SAP’s planning tool APO, Netweaver XI (later PI) and, the 2007 acquisition of Business Objects (including BODS) which all accelerated SAP’s application integration techniques.

With Netweaver XI/PI and Business Objects Data Services, it became possible to integrate SAP R/3 in real time, making use of advanced messaging techniques like Idoc’s, RFC’s, and BAPI’s. These techniques all work very well for transaction system integration (EAI); however, these techniques do not have what it takes to provide real-time data feeds to the integrated data warehouse. At best a hybrid approach is possible. Back in 2000 my team worked on such a hybrid project at Hunter Douglas (Luxaflex). They combined classical ABAP-driven batch loads for managerial reports with real time capabilities (BAPI calls) for their more operational reporting needs. That was state-of-art in those days!

Finally, in 2010 SAP acquired Sybase and added a best of breed Data Replication software tool to the portfolio. With this integration technique, changed data is captured directly from the database taking the loads off of the R/3 application servers. This offers huge advantages, so it makes sense that this is now the recommended technique for loading data into the SAP HANA appliance.

“What has changed is that SAP has put the need for real-time data integration with R/3 on the (road) map!”

The main feature of our upcoming release of Teradata Analytics for SAP Solutions version 2.2 is a new data replication technique. Almost designed to prove my case, 10 years ago I was in the middle of working on a project for a large multinational company. One of my lead engineers, Arno Luijten, came to me with a proposal to try out a data replication tool to address the latencies introduced by the extraction of large volumes of changed data from SAP. We didn’t get very far at the time, because the technology and the business expectations were not ready for it. Fast forward to 2014 and we’re re-engaged with this same customer …. Luckily this time the business needs and the technology capabilities are ready to deliver!

In the coming months my team and I would like to take you on our SAP analytics journey.

In my next posts we will dive into the definition (and relativity) of real-time analytics and discuss the technical complexities of dealing with SAP including the pool and cluster tables. So, I hope I got you hooked for the rest of the series!

No one cares about data governance, and neither should you

August 6, 2014

It’s probably the most common question I get when I visit companies struggling to get data governance off the ground: “How do I get the business to care about Data Governance?” The answer is simple. You can’t. Don’t even try. What do people care about? They care about the work that is already piled up in front of them. They care about the goals and objectives used to measure their success.

One of the first things I do when working with clients on this topic is to review the material they’ve been using to “sell” data governance within their organization. It almost always goes something like this:

• Slide 1 – “This is the definition of data governance…”
• Slide 2 – “Data governance is really great and is really important…”
• Slide 3 – “All the smart companies are doing data governance…”
• Slide 4 – “Here are the pieces and parts of data governance according to some expert…”
• Slide 5 – “Here’s some possible business value we could obtain if we implement data governance…”
• Slide 6 – “We think you should assign data stewards from your areas to this effort…”
• Slide 7 – “Here’s how we propose to get started…”
• Etc.

If you were an executive with hundreds of millions of dollars’ worth of projects lined up, and you were responsible for the success of those projects, would the preceding presentation get your attention? Probably not.

Here’s another way to structure a data governance pitch that works much better:

• Slide 1 – “Here are the major in-flight and planned business initiatives at this company…”
• Slide 2 – “Here are the kinds of data and analytics these initiatives will need…”
• Slide 3 – “Here are some of the data issues that might hobble the success of these business initiatives if we don’t do something about them…”
• Slide 4 – “Oh, look! It seems that a lot of these initiatives need the same or very similar data!”
• Slide 5 – “We’d like to ensure that the data is ready for these initiatives, at just the right time and in just the right condition…”
• Slide 6 – “This thing called ‘data governance’ will be a big part of ensuring the readiness of that data… here’s how…”
• Slide 7 – “Here’s how we propose to get started…”

Do you see the difference? It may seem subtle, but the difference in results is dramatic. The first approach sells “data governance”. Even though it mentions potential “business value” on slide 5, it’s the wrong kind of value. It’s new value that will compete with, rather than support, major business initiatives. That is, it’s just more work to do.

The second approach simply offers to help major initiatives in a specific way. For example, perhaps one major initiative is to implement an inventory replenishment application. The “pitch” would explain how business and IT need to work together to deal with known inventory inaccuracies that would hinder the project if not addressed. And, by explaining how other projects will have similar hurdles with the same data or other data, you can make a case for establishing a more permanent assignment from the business (a data steward) for each data domain that will need attention, but not before it’s needed. Then, you can talk about what a data governance structure looks like and all the ins and outs of how it will function, but only to the extent that it supports the business initiatives by making sure the data is ready. This approach works because everyone cares about the business initiatives, but no one cares about data governance, and neither should you.

Guest Blogger Kevin Lewis is responsible for Teradata’s Strategy and Governance practice. Prior to joining Teradata in 2007, he was responsible for initiating and leading enterprise data management at Publix Super Markets. Since joining Teradata, he has advised dozens of clients in all major industries.