“There is no fertilizer like the owner’s footprint in the fields.”

Regular inspection makes for fertile ground

My grandparents had a nice business raising cattle. The market for free-range beef drove growth in their business and they cleared more fields and shifted resources to produce the feed they needed for the larger herd over the winter.

The business soon required more work than two people could handle and they decided to hire permanent help to support the daily operations of the farm, maintain the fields and tend to the hay and corn production required for the winter.

The spring and summer went well with crops planted on time and the cattle remaining healthy under new management. Revenues were up and my grandparents thought they were getting what they expected.

They went to Florida.

Returning in March they noticed the herd seemed smaller. Inspecting the numbers, revenue was flat but revenue per head was down. When pressed, the farm manager said the cattle were not keeping weight like they had in the summer. Inspecting further, my grandparents found that the management team had only turned the hay field twice, instead of the three turns they used to achieve. Also, the professional crew had not used proper fertilizer reducing the yield in the corn crop. To make it through the winter feed was rationed and the cattle had lost weight. To meet revenue targets, the one well understood metric for the business, the number of cattle sold per month had been increased.

This was not sustainable. The need for more granular metrics was obvious.

My grandparents assumed that by inspecting revenue they could expect the other measurable aspects of the business to be managed properly. They did not think to set targets for turns of the hay fields, corn yields and total volume of feed projected based on weekly growth. They did not set targets for herd size or average weight per head and did not measure this key driver of revenue sustainability at regular times throughout the year.

In our world of technology start-ups someone once said

“You get what you inspect, not what you expect.”

As your business scales, farming your data can drive significant value. Set goals and measure success against the data that flows out of daily operations. A culture where metrics are transparent and everyone is empowered to take action based on the data is a culture that scales. When this works each team member leaves fertilizing footprints in the fields and, as a founder, you may get what you expect without being inspector and chief.

Defining the data to measure can be difficult, but there is a lot of guidance available. This piece from Josh on cohort analysis is great as is the SaaS metrics PDF published by Bessemer. No matter what your business, a data driven management approach can help you succeed. If you have specific metrics that you use to manage your business or other resources you feel are good sources of guidance I would love to discuss best practices in the comments.

In the 200 milliseconds it takes you to draw your gun, my algorithmic gun slinger could make 39 stock trades and shoot you in the heart

I believe we are now seeing a change in data processing and decision-making that will be equally significant for investors and entrepreneurs.

Historically, data analysis and computation was done on log files and stored data pools.  In these types of businesses, the data decisioning was done “out of band” — or not in real-time.  However, we’ve now started to see a whole series of applications and businesses where data analysis and decisioning is happening “in band” on streams of data.  In these applications, milliseconds matter.  Massive data analysis and computation are being performed in real-time — and the user’s experience is affected by this analysis.

This is a fundamental change.  Humans do not operate in milliseconds. For the real time web to function, the human decisions have to occur before the clock starts. We need to focus on predictive analysis and algorithms that make rule based decisions for us informed by the data stream.

The Facebook Newsfeed (already has machine intervention) and the Twitter Stream are the most frequently noted “data streams”, but the auto-generated data created by every consumer action, ad impression and click are orders of magnitude larger.  Including the data streams generated by CDNs and ISP’s you can see the exponential nature of the decision requirements in this new streaming data world.

The first vertical to move to real-time is advertising (Spark Cpaital’s Mo Koyfman has a nice summary of the shift in on-line advertising on his blog). It is not surprising that advertising is the first industry to move in this direction. It is most similar to the financial markets and over the past ten years the percentage of equity trades on US exchanges driven by algorithms has grown to over 70%. This was the insight behind Appnexus and Invite Media and may explain why some of the first guys to envision a transparent market for display inventory and real-time bidding came out of a finance school.

In our portfolio I see the power of operating in stream. Ad insertion order compliance can now happen in real-time based on contextual data streams analyzed by Double Verify.  VigLink can identify un-affiliated links across the web and not only append the link with an affiliate code, but choose the profit maximizing link in each instance, in real-time. Knewton’s testing platform is able to provide each student with a customized and personalized test-prep experience, based on their real-time adaptive education platform.  Aggregate Knowledge automatically produces personalized and dynamic creative for advertisements by using real-time algorithms.  In milliseconds Monetate applies a specific set of merchandising rules to individual consumer data streams. The result is a unique shopping experience for each visitor to an e-commerce site.

As we move from a world of data pools to data streams and processing power is distributed to the edge, what other changes will take place now that milliseconds matter? Will infrastructure changes take place as well? Will the real-time web increase the value of a millisecond enough to force companies to co-locate their algorithms at the CDN site or even the end-point device level?

I would love to discuss it in the comments, @phineasb or phin@firstround.com