Wanted to run the following two questions and my answers by the community:
Q. What is the average age of reporting applications at large enterprises?
A. Reporting apps typically involve source data integration, data models, metrics, reports, dashboards, and queries. I'd rate the longevity of these in descending order (data sources being most stable and queries changing all the time).
Q. What is the percentage of reporting applications that are homegrown versus custom built?
A. These are by no means solid data points but rather my off-the-cuff – albeit educated - guesses:
The majority (let's say >50%) of reports are still being built in Excel and Access.
Very few (let's say <10%) are done in non-BI-specific environments (programming languages).
The other 40% I'd split 50/50 between:
off-the-shelf reports and dashboards built into ERP or BI apps,
and custom-coded in BI tools
Needless to say, this differs greatly by industry and business domain. Thoughts?
As one of the industry-renowned data visualization experts Edward Tufte once said, “The world is complex, dynamic, multidimensional; the paper is static, flat. How are we to represent the rich visual world of experience and measurement on mere flatland?” Indeed, there’s just too much information out there for all categories of knowledge workers to visualize it effectively. More often than not, traditional reports using tabs, rows, and columns do not paint the whole picture or, even worse, lead an analyst to a wrong conclusion. Firms need to use data visualization because information workers:
Cannot see a pattern without data visualization. Simply seeing numbers on a grid often does not convey the whole story — and in the worst case, it can even lead to a wrong conclusion. This is best demonstrated by Anscombe’s quartet where four seemingly similar groups of x/y coordinates reveal very different patterns when represented in a graph.
Cannot fit all of the necessary data points onto a single screen. Even with the smallest reasonably readable font, single-line spacing, and no grid, one cannot realistically fit more than a few thousand data points on a single page or screen using numerical information only. When using advanced data visualization techniques, one can fit tens of thousands (an order-of-magnitude difference) of data points onto a single screen. In his book The Visual Display of Quantitative Information, Edward Tufte gives an example of more than 21,000 data points effectively displayed on a US map that fits onto a single screen.
I just finished reading Corporate Culture: The Ultimate Strategic Asset by Eric Flamholtz and Yvonne Randle. The book is based on the premise that company culture is a critically important yet often uncredited driver of success and failure, even correlating to financial performance. And, like other aspects of modern corporations, culture requires active management. Companies with great cultures don't get there by accident. The book is a worthwhile read for those with an interest in general management and the implications of culture for mid-sized to large companies.*
The book defines corporate culture as the "values, beliefs, and norms that influence the thoughts and actions (behavior) of people in organizations." The connection between cultural attributes and actions made me think about applying the concepts of culture directly to digital intelligence. Why is culture important in the context of digital intelligence? Because simply hiring people or implementing technology isn't enough to achieve digital intelligence proficiency. I see proof of this on a daily basis as I work with clients who struggle with digital intelligence despite substantial investments in the best technologies and most talented teams. These organizations have many of the individual pieces but cannot put the puzzle together. Culture is the connective tissue that binds technology, people, and action together.
To take the idea a bit further, let's look at the five key components of corporate culture according to the book and their digital intelligence implications:
Forrester's global Marketing Technology Adoption survey investigates:
What technologies do marketers currently use, and what do they plan to use?
How much do marketers budget for technology acquisition and operations?
What are the users' top goals for and pain points from marketing technology?
You can use the survey results to:
Provide justification for a business case in your 2013 technology road map.
Compare your spend levels and technology use to those of other marketing professionals.
Spot trends and see best practices to incorporate into your technology strategy.
The survey will close on Friday, August 3, and the completed research report will publish in early September. Once the research publishes, I will also present the findings in a Forrester Webinar and in advisory sessions to interested clients.