Archive for July, 2009

Roadtrip ProductCamp Seattle 09

July 30, 2009

I committed to going to the Seattle Product Camp 09 on October 10th while I still lived in LA. I made that roadtrip a few months ago. I do not want to drive the southern Oregon stretch of I-5 at night ever again.

Having relocated to San Antonio, Texas eliminates the necessity of driving that stretch of interstate. It presents me with an opportunity to see Wyoming and Montana. I’ve driven the stretch to Denver on top of several trips to Santa Fe when I found the fast way from Austin (10.5 hrs) via Muleshoe.

The gas estimate would be 16 fills via LA and Seattle via I-5. Plug in a safety factor, so I’m up to twenty fills. So the budget is up to $800 without food or sleep. That makes the trip contingent. I won be able to firm up the trip until sometime after August 23rd baring some other wonderful surprise.

I’ll miss the Austin Product Camp, because that happens to be the day my son gets married over in East Texas.

I have two seats that could be filled along the way.

I know, it would be cheaper to fly. But, I’m not one to miss an opportunity to roadtrip.

See the map.

Roadtrip to ProductCamp Seattle 09

Roadtrip to ProductCamp Seattle 09

Notes from the Middle of the Night

July 29, 2009

I woke up at 4:00 am, so I picked up my moleskine and sketched out a stream of thumbnails starting with scope as a force, and ending with the firm as a morpheme.

Knowledge Management

I’ll omit scope as a force, and move on to some knowledge management ideas. Learning is said to be a four stage process: unconscious unknowing, conscious unknowing (fear), conscious knowing, and unconscious knowing (flow). Learning can be summarized as implicit to explicit to implicit. Back in AI class, explication moved implicit knowledge to explict knowledge. Explication was the goal. But knowledge management orients itself towards the value of knowledge.

Explicit knowledge has value, but it becomes commoditized. This makes explication a process of moving knowledge towards commoditization. The intial explication leads to another explication endlessly towards ground via subsequent explications.

Implicit knowledge has value without explication. We exchange it. We embed it. We use it unconsciously. We can even capture it without explicating it. And, in the learning process, moving the explicit back to the implicit, or forgetting, takes an effort characterized by an attention shift where we focus on other things. In academia, professors must keep moving. The hot problems change, so they shift their focus to the next hot thing. Research in requirements elicitation came to a standstill by the mid-90s. Things were forgotten, or just never made it into the textbooks.

Ultimately, the cycles of implicit to explict extends endlessly bumping into an S-curve where it fades from attention.

Knowledge cycles: explications, re-implication, implication

Knowledge cycles: explications, re-implication, implication

As a state diagram, the situation generates a surprise!

State diagram summarizing the knowledge cycles.

State diagram summarizing the knowledge cycles.

Ignoring the labels, what we have is a flip-flop. We have memory. That memory constitutes the mechanism of asymmetry in all things. The adoption of technology is asymmetric and memory based. Poisson games describes the populations adopting a technology as a series of Poisson distributions. Moore’s technology adoption lifecycle can be translated into a series of Poisson distributions. Moore asserted a normal distribution. Adoption is also characterized as a polynomial that Fourier translated into frequencies.

Adoption in different representations

Adoption in different representations

Weak Signals

Discontinuous or radical innovations occur in small populations where they reach a critical mass and move into larger populations. Adoption of such an innovation is an asymmetrical process. The adopters constitute the memory of the process. The initial adoptions constitute weak signals. They look like noise at some scale. Eventually, they no longer look like noise.

Weak Signals

Weak Signal

Packing Factor

This morning on Twitter there were a few tweets about how a lot of middle market customers were preferable to a few large customers. There was also a tweet to a YouTube presentation about determining the number of M&Ms in a jar based on the packing factor of the contents. Oddly enough, there I was hours before I got online drawing a figure about packing.

The way I stacked that second and subsequent layers of sales events hints at a packing factor. Playgrounds use a variety of surfaces intended to reduce impacts of falls and jumps. It turns out that pebbles make for a very soft surface, because there is so much air around each pebble. Compression forces some of that air out of the way. The air around each pebble is a matter of its packing factor.

Sales Packing Factors

Sales Packing Factors

An organization has a certain capacity for lead generation and sales close processes. These capacities generate a packing factor. Mid-sized firms tend to be more alike where a Fortune 200 market will scale over a range of company sizes in terms of seats and budget dollars. The yellow in the figure represents the gaps in revenues from the sales. You might want to think of the yellow areas as continuity risks.

Actors in Sale

Sales packed into a signal timeline have an internal structure. In a small company, you sell to one manager without purchasing or multiple stakeholders complicating the deal. In a large company, there are many players. In a small company, the buyer might be the user. In a large company, the economic buyer is distant from the users. These considerations define a collection of personas beyond the user and buyer.

Actors in Sale

Actors in Sale

The actors in the sale can be represented as vectors. As a collection of vectors, the representation would look like a morpheme. Linguistics has been applied to the genome and proteins. I could be applied to the organizational structure of a firm.

Representations provide implementation options when we code. Representations provide management options when we manage. Enjoy.

What do you think? Leave a comment.