I can’t believe it has been a year since the first Atlanta Barcamp! And for you folks saying “What’s Barcamp?” You’ll just have to bear with me for a little while. Yes, i’m a branding guy now, but I have nerdy roots and Barcamp is a wonderfully nerdy event.
Right now we are in the ATDC space at Ga Tech. We’ve been fed some BBQ, sodas and beer and now the evening sessions are beginning. The format is “unconference” or more appropriately ad hoc conference. People sign up on a sheet to give presentations, and other people sign up to attend presentations. The topics vary widely. From heavy-duty coding topics, to business issues for developers and entrepreneurs, to fun things like demos with liquid nitrogen. I’m sitting in on a session on pricing for independent consultants – generally meaning programmers for hire, but I’m sure much of it will be applicable for any consultant.
Brad Gilreath of Mapicurious.com is presenting. Right now he is giving some of the nitty-gritty of a consultants life. Short and long projects, realities of working stamina, finding a balance, hiring help etc.
Oh and in case you haven’t noticed, I’m live-blogging this, meaning I’m writing on the fly while Brad talks, so the style of this post migt be a bit rough ’round the edges than my usual fare — and may get a bit techier. As I said before, indulge me.
Big point – consultants need sleep too! Even though the fear of not having a steady gig can turn you into a workaholic. How much of your day is really usable, billable?
Uh oh, he’s showing a spreadsheet – my eyes are too old and tired for that. It is a calculator for types of activities and projects. Discussing pressure applied by clients to make your work appear to be a commodity to drive prices down.
Spreadsheet buld “product factors” to trap client requirements. Clarify scope, details and particulars. Map payment cycles – build in adjustments for lengthier payment cycles – cost of sitting waiting for your money should be figured into your pricing.
The whole idea here is to have a solid tool for building estimates for projects. Understanding components and details help guide the discussion for more accurate pricing and heading off potential points of confusion before they become issues or disputes.
This approach could be used as a job auction tool. Also potential for branding the tool for particular clients. Weighted average factor pricing could be made tighter with input from accountant/economist.
It could also automatically build documentation for the statement of work.
Guideline – don’t get greedy!
Cool job Brad!
OK – now, depending on how many people signed up, I’m going to give a 1/2 hour on branding for startups.
Can’t blog and talk though 🙂
Barcamp 2 – more from Friday night
Gave my talk on branding for startups. Discussed the Three R’s of branding and some of the particular issues of note for a young company trying to get established in an Internet driven economy.
Then I went late to a talk on the Erlang programming language. It was standing room only so live-blogging wasn’t practical. Cool talk though. The big idea here: Erlang is massively scalable! The rest was over my head 🙂
Now I’m in a talk on Bayesian algorithms for filtering – two groups combined for this talk, one interested in Bayesian analysis the other in AI and cognition (with a futurist spin). Thought this would be a more philosophical discussion because of the AI, but the Bayesians have numbers on their side so the talk is getting into logic and algorithms. Spam filtering is a popular problem for applying the power of Bayesian. Basically by recognizing user behaviors and aggregating behaviors across users and then create probabilities for saving and for scrubbing any particular message. So Bayesian calculations get the probablities that score likelihood of scrub and likelihood of save. Then another algorithm has to look at the balance between the scores to determine the final save/scrub decision. The goal is to have a system that continues to learn over time to get better over time. Surprise issue – you don’t want the system to learn too fast! If it does the system can develop biases that might move you away from desirable result. Learning at the right pace allows the system to aggregate enough scores to have more relevant outcomes.
What does this have to do with branding? As I mentioned an hour or so ago, I’m indulging my nerdy roots and hanging out at Barcamp Atlanta. The technology is driving everything these days. And I believe in the long run these technologies will influence marketing and buying behaviors, just like the web has.
Moderating is discussing filtering large data sets – question now about qualifying market data as another use case. Bayesian is good at putting info into buckets. Not as good for mathematical evaluation.
Could you use Bayesian to create real estate recomendations? Start learning behavior for a home buyer? Could the home buyer train the system fast enough to make it useful infiltering a databse of 100000 homes? (questions from Alan Pinstein) The experts say yes, this is a good application for Bayesian approach.
Conversation is moving to relevance engines, but it is 10pm so time to change rooms.