We came across a humorous post at a Harvard Business Review blog the other day about silly business language. All the acronyms, consultant-speak, jargony slang and high-tech spin are making basic business communication nearly impossible:
you get phrases like, “You should meet this guy with the SIO. He’s sort of this kind of social entrepreneur thinking outside of the box in the sustainability space and working on these ideas around sort of web-based social media, and he’s in a round two capital raise in the VP space with the people at SVNP.” This would all be funny if it weren’t true. People just don’t make sense anymore.
A similar story about LinkedIn’s most overused resume words of the year also reminded us of the often careless and sometimes abusive relationships businesspeople seem to have with the English language.
Synergy, paradigm, silo, value-add, net-net, win-win, leverage, most unique, align – these various clichés have all driven me crazy at some point over the years. But, like a lot of people in technology, I’m probably guilty of overusing “solution,” “stack,” “partner,” and a few others. Within BI, “big data” looks to be shooting across the buzzword hype cycle with record speed. When these words are thrown around so loosely, they lose their essential meaning. For example, we’ve tried to break down the meaning of big data.
All of this reminds me that “semantic confusion” in BI remains a serious problem and appears to be getting worse. Consider the great BI (business intelligence) vs. BA (business analytics) debate. The conventional wisdom seems to be that BI is backward-looking, a technology or process that helps organizations understand what happened, while BA is forward-looking and predictive.
Maybe that’s why IBM has positioned its Watson play around analytics. In our view, however, the fundamental difference between BI and BA is basically how the data is processed and presented to the user – what I would characterize as features of the tool or platform.
A greater challenge is the confusion that results when organizations have multiple definitions of key terms like “customers” or “sales.” This is a huge problem at both ends of the BI spectrum – for developers trying to build easy-to-use applications and for analysts and executives trying to make decisions. And it’s a particular problem at large enterprises with complex organizational charts and fragmented IT systems (dare I say siloed?).
Defining core metrics consistently across the organization as part of a common business language is the keystone of effective BI. As we point out here:
Standardizing your business language also enables transparency, accountability, and concurrence. And the process of establishing a common business language helps promote best practices in collaboration and fact‐based decision making.
For workers in any field to collaborate productively, they must be able to communicate clearly. In BI, the need for collaboration between users and BI teams is especially great at the moment, which means there is a premium on communicating clearly. Developers and business users must simply learn to speak each other’s language if they are to bridge the BI Delivery Gap and if investments in data warehousing and BI are to deliver optimal returns. We think continuous engagement is the right model for developers to think about growing and strengthening their relationship with BI users, who, like or not, truly are calling the shots these days.
So that’s why we say let’s lose the lingo, jettison the jargon, and excise the acronyms. Clearer communication can lead to better BI.
Aberdeen released a report that highlights the increasingly difficult time problem in business intelligence and the way that Agile development and interactive, business-driven BI address the issue. In short, business executives and analysts have to make decisions faster. The solution from a BI perspective is really two-pronged – using Agile BI to develop new tools faster and ensuring the tools themselves empower users through high degrees of self-service and interactivity.
Aberdeen’s analysis is based on previous research into development methodologies. The findings showed that 103 out of 237 respondents said their organizations are still using traditional methodologies exclusively. No wonder, in the words of the report’s author, that:
Organizations are struggling to get the right information to the right people at the right time.
The cause is largely due to:
Vast inflow of fresh data and increasingly demanding community of business managers.
So the high-level diagnosis seems on track. But the issues and problems multiply as “decision-making windows” shrink – a phenomenon experienced by 64% of business managers surveyed. Of course, we all know this intuitively; quicker business cycles, intense cost and competitive pressures, and fast-moving, technology-fueled markets mean we need to make decisions faster, which means BI teams must deliver more data faster to support those decisions.
And there is plenty more data go around; Aberdeen’s research says IT has seen 40% increases in data volumes, which bogs down development.
The speed with which “best-in-class” (and the speediest) BI organizations can move really caught our eye. According to Aberdeen, they can “add a column to report in an average of 4.3 hours and create entirely new dashboards in 3.8 days.” There is no way to deliver BI this fast without using Agile BI methodologies to ensure strong interaction and excellent communication between developers and business users. Faster development cycles are just a reality of today’s business.
Further, Aberdeen highlights visual or interactive BI tools as critical to keeping up with the increasing time pressures. How? By enabling greater self-service and more interactive or “drill-down” capabilities.
Self-service BI encapsulates the concept that business managers will be fully empowered to analyze data and discover new business insights without direct help from corporate IT.
This sounds like business-driven BI at its best. We often describe this to our clients as the ability to “ask questions of the data,” a functionality that is built directly into the core of Balanced Insight Consensus.
The bottom line is that IT and the business must collaborate more effectively and frequently if they are to prosper mutually in our fast new world of tighter decision-making cycles. And IT is no longer the gatekeeper, a point we made here. Or, as the report’s author says:
IT must move to a more supportive role – providing analytical tools, education and support, and a rich set of high-quality data – to enable business users to be more self-sufficient … [this] approach to business intelligence takes responsibility for the discovery of relationships in the data away from IT organizations and places it where it can be used to best advantage – with the managers who truly understand the business.
It’s that time of year again, when pundits across the technology landscape begin to make their predictions and resolutions for the new year. Some of our favorite BI observers have chimed in about how they hope 2012 will bring peace on earth and goodwill to men — not to mention better BI delivery!
We certainly share the view of Boris Evelson of Forester, who expects organizations will “learn to live with multiple BI tools” and further movement of BI “into the hands of end users.” We’re all for increasing the user-centricity and business focus of BI – as we point out here and here. read more…
Last week, I posted about the implications of “big data” on the future of BI, and why we’re skeptical about many of the bold promises of business benefits without adequate coverage of the hurdles involved. We’ve also spent time with TDWI’s Big Data Analytics research results (registration required), which offered a refreshingly pragmatic tone in all the recent noise about “big data.”
Big Data & the Future of BI
2011 may be remembered as the year of “big data” in technology circles. Certainly, that’s true in business intelligence and analytics (broadly defined). IBM’s Watson was part of the story, as was the report from McKinsey Global Institute that came out a few months ago.
Titled “Big Data: the Next Frontier for Innovation, Competition and Productivity,” the report was full of fun facts (30 billion pieces of content are shared on Facebook every month and all the world’s music could be stored on a $600 disk drive) and bold claims. read more…
Managers and technologists familiar with the Agile software development methodology are familiar with the concept “continuous integration,” which refers to:
continuous processes of applying quality control — small pieces of effort, applied frequently. Continuous integration aims to improve the quality of software, and to reduce the time taken to deliver it, by replacing the traditional practice of applying quality control after completing all development.
As powerful as the notion of continuous integration is (especially from a technical standpoint), we think continuous engagement may be even more so. read more…
If you missed our most recent BI Knowledge Exchange Webinar, you missed out on five proven ways to cut BI overhead and ensure value delivery from your projects. Savings of up to 40% are especially useful this time of year, as 2012 BI project budgets are being shaped.
Check out the video here and supporting article here.
User Adoption Is Not Separate from Development
“User adoption” refers to the willingness of end users to embrace a software system once it has gone live. Software and BI development teams tend to focus on meeting raw requirements as listed, and therefore user adoption has always been something of an afterthought. At most, one team member may be responsible for ensuring the application presentation layer is usable and acceptable to users. And generally speaking, other steps that drive user adoption, like training, documentation and communication, are thought of as activities that take place after the hard work of development is mostly done.
Consumer empowerment and the “Apple-ization” of IT have made this traditional view unsustainable. Usability has become too important. We’ve shared our thoughts before on the “why” and “how” and of usability. Basically, our point of view is this: forget fancy graphics, beautiful colors and slick interfaces; for developers and BI teams, usability is a strategy to ensure BI apps are adopted across the organization. It also helps eliminate rework. BI apps with major usability issues are difficult to fix after the fact – like trying to build a ranch house on top of a foundation designed for a two-story Colonial. read more…
Moneyball & BI: The Debate Continues
Melinda Sue Gordon/Columbia Pictures
Now that the hype around the latest Brad Pitt movie has died down a bit, we wanted to revisit our previous post, which outlined what BI teams can learn from the Moneyball approach to baseball management – like the importance of clear semantics, prioritization and consistency in metrics. We are impressed by the movie’s solid box office and mostly positive reviews. It shows how “the data guys have won,” as this story put it, and what happens when executives have the skills, knowledge and freedom to make “creative use of data.”
Among baseball pundits, the movie has generated considerable debate about what led to the success of the Oakland A’s in the mid-2000s. A strong case can be made that it wasn’t so much about superior player evaluation and asking the right questions of data, but rather just about having the right personnel – specifically a few great young pitchers. Or maybe it was just that the A’s innovated by going against standard industry practice; they decided to zig when everyone else was still zagging.
This is not the right debate to have. And it’s similar to the fallacy that BI success is “all about the technology.” read more…
If it’s budgeting time at your organization, it’s time to consider five proven ways to cut BI overhead and ensure value delivery from your projects:
- Build it right the first time.
- Make business users the owners of BI apps.
- Start with core requirements and re-use components.
- Automate everything.
- Use what you have and don’t move sideways.
While some of these tips may seem self-evident, it’s important to remember that not following them often leads to most of the common BI delivery issues and challenges. To find out how to apply the tips, check out the full article here.
And don’t miss our BI Knowledge Exchange Webinar on this topic November 3rd.
