I recently came across a trade-press article with the headline “Mining the Cloud.” The cynic in me immediately issued a silent scoff: How is that different from “crawling the Web”? Are we just mapping old wine to shinier new bottles? Or is there something different here?
But, seeing as how I too like to proliferate discussions of mining this or that information type, I was willing to cut the reporter some slack. The article was from Redmond Developer, and concerns “Project Dallas” under Microsoft’s Azure cloud initiative. Essentially, “Project Dallas” (still in beta) supports discovery, manipulation, visualization, and analysis of data retrieved from multiple public, commercial, and private data sources via the Azure cloud. “Dallas” allows enterprises to provide users (via REST, Excel PowerPivot, and/or Visual Basic applications) with online access to aggregated feeds via Azure, which essentially operates as an online information marketplace. Also, “Dallas” allows customers to have Azure host their data for them, or simply continue to host it on their own premises while the cloud service connects securely to it.
Since 2007, Forrester analysts Ken Vollmer, Noel Yuhanna and I have collaborated to publish an annual review of the application, process, and data integration technology landscape. The goal of this important recurring research is to help application development, business process, data management, and enterprise architecture professionals navigate the often complex and confusing myriad of choices available to solve their organization’s integration challenges.
This year’s report focuses on ten distinct integration technologies including ESB, CIS (Comprehensive integration solutions), B2B service providers, Privacy industry exchanges, B2B gateway software, and Integration appliances on the application and process integration side, as well as ETL, CDC (change data capture), and EII (enterprise information integration) on the data integration side. In addition, we continue to look at Information-as-a-Service (IaaS) as an architectural approach to supporting data integration requirements.
A key take away from this research is our recognition that application, process and data integration can no longer remain isolated siloed competencies within an organization. Our recommendation is that organizations look to consolidate their integration strategies and resources into a shared services organization that can leverage all the strengths of these different techniques.
We hope you enjoy, and look forward to hearing your feedback.
The Second Case Study on Customer Service Social Media: How To and The Results...
If you have been following this blog, you might remember that I posted this a while back. But with the new year here, I thought it might be good to repeat some of the case studies while adding new ones... just incase you missed them or incase you wanted a refresher as you start down the path of providing a solution to your company social media needs!
This is the second case studies in the series on Customer Service Social Media Best Practices! You might be wondering what I meant by "ownership." In organizational change management language... there are three stages of project success - awareness, buy-in and ownership. Here ownership doesn't me "owning" like it's mine - not yours. It means taking 100% responsibility for leading and faciliating solid, genuine, collaborative relationships with the whole company to further the whole company's succcess. Here's more details on how Lenovo accomplished their social media goals!
Why Did Lenovo Consider Social Media?
When Lenovo acquired the IBM PC computing division, they realized customers were talking about their products on 3rd party forums like notebookreview.com and thinkpads.com. They felt left out of these important customer conversations. To remedy that, they took ownership and lead the customer social media interactions.
There’s no doubt about it. The BPM suite market has fundamentally changed, now that IBM announced plans to buy Lombardi, and Progress Software sealed the deal on Savvion yesterday. Two little vendors . . . and you would think, given all the reaction, that something really big happened. But in many ways, that’s the case.
Ok, why are these two deals so important? Lots of reasons, including:
Price-performance is everything in data warehousing (DW), and it’s become the leading battleground for competitive differentiation.
As I noted in a blog post last month, the price of a fully configured DW appliance solution has dropped by an order of magnitude over the past 2-3 years, and it’s likely to continue declining. In 2010, many DW vendors will lower the price of their basic appliance products to less than $20,000 per usable terabyte (TB), which constitutes the new industry threshold pioneered by Oracle, Netezza, and other leading DW vendors.
But that’s just a metric of price, not price-performance. Ideally, each DW appliance vendor should be able to provide you with a metric that tells you exactly how much performance “bang” you’re getting for all those bucks. In a perfect world, all vendors would use the same price-performance metric and you would be able to compare their solutions side by side.
But, as I noted a year ago in another blog post, truly comparable cross-vendor DW benchmarks have never existed and are unlikely to emerge in today’s intensively competitive arena. No two DW vendors provide performance numbers that are based on the same configurations, workloads, and benchmark metrics. And considering how sensitive these performance claims are to so many variables in the vendors’ solutions and in customers’ production environments, it can be quite difficult to verify every vendor performance claim in your specific environment.
Self-service is all the rage in the world of business intelligence (BI), but it’s no fad. In fact, it’s the only way to make BI more pervasive, delivering insights into every decision—important or mundane—that drives your business. It’s the key to empowering users with actionable insights while removing many mundane BI development and maintenance tasks from IT’s crushing workload.
In mid- 2009, I published a Forrester report describing key benefits, use cases, and approaches for implementing self-service BI, under the broad heading of “mighty mashup.” Forrester customers have responded very favorably to the discussion, asking for advice on whether, when, and how they should adopt this approach. Going forward, Forrester will deepen our discussion of self-service as a best practice to be incorporated into enterprise BI Solution Center (BISC) teachings.
The First Case Study in the Series About "How to Deploy Customer Service Social Media!"
If you have been following this blog, you might remember that I posted this a while back. But with the new year here, I thought it might be good to repeat some of the case studies while adding new ones... just in case you missed them or in case you wanted a refresher as you start down the path of providing a solution to your company social media needs!
When I published the ROI of customer service social media, everyone had asked me - who is doing social media and what are they doing. To help those who haven't started down the social media path, I put together the 5 Best Practices of customer service social media. That doc is chocked full of ideas you can use today. And to provide more details on how companies have accomplished their goals for social media, I also decided to publish a bunch of case studies! ACT! is the first of many! I hope it helps you to get a better idea of how valuable social media is and its bottom-line affects!
Who is Sage and What Did They Want to Accomplish With Social Media?
Business processes can be incredibly hard to fathom. The more complex they are, the more difficult it is to find the magic blend of tasks, roles, flows, and other factors that distinguish a well-tuned process from a miserable flop. Even the people who’ve been part of the process for years may have little clue. It’s not just that they refuse to look beyond their job-specific perspectives, for fear of jeopardizing their careers. It’s often an issue of them being too close to the problem to see it clearly, even if they try very hard.
Process analytics is all about identifying what works and doesn’t work. It’s a key focus for us here at Forrester, and I’m collaborating with one of our leading business process management (BPM) analysts, Clay Richardson, on research into this important topic. The first order of business for us is to identify the full range of enabling infrastructure and tools for tracking, exploring, and analyzing a wide range of workflows. It’s clear that this must include, at the very least, business activity monitoring (BAM) tools, which roll up key process metrics into visual business intelligence (BI)-style dashboards for operational process managers. Likewise, historical process metrics should be available to the business analysts who design and optimize workflows. And each user should have access to whatever current key performance indicators are relevant to the roles they perform within one or more processes.
Social networks have always been with us, of course, but now they’ve gained concrete reality in the online fabric of modern life.
Social network analysis has, in a real sense, been with us almost as long as we’ve been doing predictive analytics. Customer churn analysis is the killer app for predictive analytics, and it is inherently social. It’s long been known that individual customers don’t always churn themselves—i.e., decide to renew and/or bolt to the competition—in isolation. As they run the continual calculus called loyalty in their heads and hearts, they’re receiving fresh feeds of opinion from their friends and families, following the leads of peers and influencers, and keeping their fingers to the cultural breeze. You could also make a strong case for social networking—i.e., individual behaviors spurred, shaped, and encouraged within communities—as a key independent variable driving cross-sell, up-sell, fraud, and other phenomena for which we’ve long built predictive models.
The other day, a Forrester client was asking me for educated guesses on how fast the average enterprise data warehouse (EDW) is likely to grow over the next several years, and as I was working through the analysis, I couldn’t avoid the conclusion that social network analysis—for predictive and other uses—will be an important growth driver (though not the entire story). I’d like to lay out my key points.
Ah, memories. I remember the late, great Eighties, early in my analyst career, when I had my first brush with what was later known as “groupware.” It was a LAN-based package, “The Coordinator,” from Action Technologies. The architecture of the software wasn’t as important as the linguistic theory on which it was built: the notion that groups cultivate intelligence by structuring their internal conversations to achieve common goals.
Essentially, the package required people to tag every e-mail they sent based on whether it constituted a discussion of possibilities, a request for clarification, or a request for action—and it tracked these threads so that everybody knew the goal-oriented status of every conversation. As you can probably guess, this was a heavy-handed way of getting people to come to agreement. Software shouldn’t dictate how people choose to interact: real-world conversation’s far too complex and convoluted for that. Most people don’t like being forced to rephrase or reconceptualize how they communicate with others. In fact, most of us users simply defaulted to sending messages that discussed open-ended possibilities, rather than engage in a fussy protocol of formal requests and offers.