In my first official post(*), I would like to talk about what I think is an important concept and that is part of my blog name: KAIZEN.Kaizen is a Japanese term and comes from the concatenation of “Kai” (= Change) and “Zen” (= Good). The two together refers to “continuous improvement”. Kaizen is more than a word; it is a philosophy that focuses of continuous improvement through all aspects of life. Doh!
But how does it relates to Web Analytics? As Paul Hostein explained in one of his recent posts, you can address your website optimization process in a Kaizen-way: simply make improvements to your website on a continuous basis. But you can see further than that. How can the Kaizen method help anyone being successful in his Web Analytics project? Well, when applied to the workplace, Kaizen activities aimed at improving all functions of a business. And as far as I know Web Analytics is a function of a business.
Sounds a bit too theoretical? Well, let me talk first about Toyota, where Kaizen is not only a key company value but one of the key factors that contributes to Toyota success story. There was a very interesting article in the New Yorker about that topic earlier this year. The author explains that Toyota defines innovation as an incremental process, in which the goal is not make huge, sudden leaps but, rather, to make things better on a daily basis. Basically Kaizen promotes slow and steady improvements. This fundamental aspect runs counter to the way that most companies think about innovation or change. To quote James Surowiecki, most corporations hope that the right concept will turn things around overnight. There you go. This, I think, often applies to Web Analytics –especially in large enterprises. People expect to turn things around in one go.
You can read lot of things about all the possibilities beyond Web Analytics, its added value, the improved ROI and all the rest. And there are plenty of people out there – especially vendors who will tell you how easy it is and why you should get all their super-features. Then you find yourself embarked in a huge project (usually comes with high costs), trying to deploy complex technology and practices. In the end (if you get there), you will likely find yourself sitting on a mountain of data and no one to figure out what to do with these. Truth will hit you like a train: Web Analytics is NOT easy. Just ask Eric T. Peterson, he will tell you :-) . More seriously, large scale improvements - while attractive - are more difficult to achieve.
Going for an iterative and incremental approach will make your life easier. First, your goals will be more achievable. Your project will be easier to manage, risks will be lower, costs will be more reasonable (so easier to get money from your boss) and you will deliver results faster. At each step, your experience and skills will grow – allowing you to move to the next level of difficulty progressively.Maturity is important – no need to provide state-of-the-art analytics if your key users & stakeholders are not prepared nor do have the knowledge and skills to use it. Start with the basics. It will be easier for your audience to understand, it will most likely create interest and raise more questions. From there, move on to more advanced practices. If you make your business users happy, they will ask for more. In the end, it will be much more motivating for everyone.
This is a principle I have applied so far in my Web Analytics journey and it has quite paid off. I have learned a lot. My company has learned a lot. We are learning and developing. There is still a long way to go but each month we are progressing, doing more, getting more benefits from our Web Analytics expertise. We continuously improve.
That is what keeps me motivated, asking for more. Kaizen approach may seem mundane but its application requires commitment, patience and perseverance. All these qualities are key elements for successful Web Analytics (or any project).
Related reading
- "The Open Secret of Success" - New Yorker article by James Surowiecki
- "Kaizen" definition on Wikipedia
- "Web Analytics - the Kaizen Way" - Post by Paul Hostein
(*) I already wrote a post on that topic last year as guest poster on Lars Johansson’s blog.
