Rachel asserts that “accounting is really an exercise about setting our priorities and ensuring that we are acting on and accounting for those priorities. ” Thus, Rachel recommends that organizations be more transparent about their accounting (and distribution of resources), so that they can make their organizational values “crystal clear”.
Yes, I thought. The more data, the better we can see where an organization is focusing its resources. Then, we can draw conclusions about whether the organization is doing what it says it values.
Then, I tripped over The Washington Post’s mindblowing –actually genius– graphic by Laura Stanton, breaking down the $819 Billion Dollar Stimulus Bill into ‘buckets’. A second graphic shows how the money will be spent over time. (Here’s a little screen grab to tempt you to get over to the whole thing!)
What’s the difference between “819 Billion Dollars” and actually being able to understand what the Stimulus Package is made of? It’s right there, in Stanton’s graphic. Just by looking at the graphic, you get it. Quickly. Comprehensively. Accurately. Powerfully. And now you can talk about the Stimulus Package knowledgeably.
There’s something else that Stanton’s graphic shows us, and that’s the difference between transparency and understanding .
Being transparent with your data is ONLY the first step towards demonstrating what your your organization really values.
In addition to being transparent (i.e., forthcoming and complete), data also need to be presented. Organizations need to share their quantitative and qualitative data in ways that are actually informative. Data need to be organized, categorized, graphed, compared, depicted, parsed, etc. so that people can understand what’s there. Then, people can come to their own conclusions about the organizations’ authenticity.
In the example of the Stimulus Bill, not even the most avid political bloggers tracking tax cuts vs. infrastructure investment could give you a picture as clear as the one provided by Laura Stanton, based on the data assembled by Karen Yorish, at The Washington Post.
Too often, information is just ‘posted’, as though we stakeholders are actually going (to be able?) to figure out ourselves what the data mean. Even when data are presented in conventional, common forms, like on balance sheets according to GAAP, we need trained professionals to analyze them. Meanwhile, everyone else’s eyes glaze over.
Of course whoever is presenting the data gets to make choices about how the data are presented. These choices are rarely value-neutral; they can hide information, reveal information, and encourage conclusions in one direction or another. Still, even a presentation that frames the data in a potentially biased way is a huge step better than a raw data dump.
Authentic organizations don’t expect their stakeholders to sweat over their ‘transparent’ data, as though their stakeholders were MBA students taking a finance exam. Increasingly there are formats, templates and best practices that can guide organizations that choose to go beyond being transparent. Organizations that want to be understood, and be held accountable for being authentic, have some models to follow.
The folks over at CorporateEye post regularly about best practices in corporate communications. David Armano at L+E (Logic+Emotions) has a truly outstanding array of visual displays of processes, concepts and qualities. (See graphic at right.)
To be authentic, organizations must recognize that being transparent is not enough.
Organizations must go further and communicate information about ‘who they are’ and ‘what they do’ in ways that permit invite stakeholders to understand them.
Then, stakeholders can hold organizations accountable for being authentic.