A Business Technology Place

Solve it!

I carry a paper notebook with me through the work week to records notes, thoughts, and action items. I prefer not to take my laptops into meetings because it helps me stay focused on participating injustsolveit the meeting. The content of a meeting, or other interaction, is often the source of ideas or even blog posts! Typically I transform my notes into an electronic system or put them in a to-do list. As I was reviewing my notes from this past week I found this thought:

“We want a formula to solve our problems.”

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What would our business be like if every problem had a formula to follow for a guaranteed answer of success? That would be great. Sign me-up. Books are released every week with answers to common or recurring questions and problems. They give us checklists, rules, and procedures to find success. The ideas, the process, and the results make us feel good inside. It’s a prescription for success. Let’s get started!

But problems in life and the business are rarely that easy. A formula will give an answer and quite possibly a very good answer. But then I think if all the problems had a formula to follow to solve it, and everyone could do it, then there wouldn’t be winners and losers. Everyone should solve the problem every time. But you and I know that’s not reality.

The next thought in my notebook reads:

“Formulas and methodologies position teams for success but don’t ensure it.”

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I enjoy the experience of a good game of baseball. Recently I read the book Moneyball by Michael Lewis. The book discusses the journey of Billy Beane as a professional baseball general manager who sought a formula to predict the baseball players most likely to succeed at their sport. With the help of some smart data analysts Bean did come up with a formula and it was used as the basis to build some successful baseball teams.  

But even with that formula there was more required. Even with the latest and greatest software development methodology more is required. Even with the dieting rules defined in that book more is required.

What the formulas don’t provide is the ability for someone to read current conditions before making decisions about the inputs and timing. In a business environment I’m thinking about conditions such as when people will be available for a project, when cash is available to fund an investment, or the opportunity cost for two competing projects.

I want to formula to neatly solve all the problems. But I can’t miss the requirement to read the context of the situation to augment the benefits of following the formula. I feel the skill to read the context of a situation and then execute the play is often times what separates a successful outcome from one that doesn’t meet the goals. Easy to say. Not easy to execute. There’s no formula for that.

Onward and upward!

What’s your True North

Sometimes when I read books I realize the author’s point is a variation or derivative of another concept that I studied in the past. It’s doesn’t mean the two authors thoughts are necessarily linked in any-way. I just get the same basis from each of their thoughts as I consider application in my life.

Here’s an example:

In Start with Why Simon Sinek talks about the power of understanding ‘why’ we do something and its relationship to ‘how’ and ‘what’ we do. He argues successful companies are started with a ‘why’ by an individual or group. ‘Why’ is the driving idea for inspiration and innovation.  When companies lose sight of ‘why’ they are in business and solely focus on what they produce, the results are not as beneficial to employees and customers.

I linked Sinek’s idea to basing management decisions on a long-term philosophy, (even at the expense of short-term financial goals), from the book The Toyota Way by Dr. Jeffrey Liker. In the Lean Principles a True North is a vision of an ideal state. True North is a guide to help with long term thinking because it is based on ‘why’ more than ‘how’ and ‘what’.

Why?compass

A while back I considered the lean principle of basing management decisions on a long-term philosophy. I thought about why I chose a professional career in Information Technology. Why am I motivated by certain experiences at work and not others?

I documented my answer as a mission statement.

IT Mission – “We connect people through systems and solutions.”

It’s simple. My ‘why’ is more about people than machines. My ‘why’ is more about solving problems than working with technology.

What’s your True North?

 

Photo Credit: Verino77 via Flickr Creative Commons.

Live to give

This week I said good-bye to my father-in-law Mario Rognoni. It was a time of remembrance, celebration, and reflection. As best I can describe him, Mario Rognoni lived life to give life.

  • He cared more about personal interactions than personal possessions.
  • He cared more about giving money to those in need than making money for his own needs.
  • He cared more about the possibilities of the future than the failures of the past.

Mario was an eternal optimist. He saw possibilities where most people saw none. He embodied the phrase “Carpe Diem”.

May your soul rest in peace Don Mario. You left the world better than you found it.

Pick your team.

I have fond memories from my youth when I was with a group of friends and we picked teams for a game. The games varied; baseball, kickball, capture the flag, football, or war. But the act of picking teams usually followed the same process. Two captains were selected and then each captain would take turns picking team members from the rest of the group. The order of selection was based on skills and the kid the captain thought provided the best chance to win. Sometimes it was based on friendships and alliances made outside the field of play. Then we played.the-sandlot-crew

When I select members for a technology department today, I have a different perspective. I like to look for team members that can contribute beyond a specific technical skill set. A base technical skill is required, but it is not enough to be on the team I would pick. Daniel Pink writes in his book A Whole New Mind that technical skills are increasingly being replaced by someone who can do it cheaper (think Asia) or a computer that can do it faster. Pink argues knowledge workers who can contribute beyond direct technical output will find more options for employment and a higher likelihood of career fulfilment. These workers can detect patterns, see opportunities, and combine results into new inventions and stories to connect with customers and coworkers.

This past week my wife interviewed two candidates for a position on her team. She asked me for advice on how to approach the process and make a distinction between the two candidates. I recommended looking for the candidate who showed interest in the mission of her workplace. Did they ask questions about the business, the workflows used by the team, the current challenges, etc.? This employee would become more fully engaged in looking at the big picture and trying to help find solutions and make improvements.

In another conversation this week, I was asked about replacing a member on our technology steering committee. The basis for the question was the new prospective member was younger and more comfortable with technology solutions. I reminded my colleague the primary purpose of the committee was to discuss the direction and impact of technology solutions on the business more than any specific technology used. The skill set I want on the committee requires more institutional knowledge of the business than it does technical knowledge.

Picking teams today is different than when I was a kid. I want team members who are engaged enough to ask clarifying questions, to ask why, and to suggest areas of improvement. I want team members to make an intentional effort to understand the whole solution and not just the tasks assigned to them. When we play the game, these are the skills that will help us win. You in?

Onward and upward!

Judging a computer algorithm

Does your GPS have a name?

Years ago when I bought the first GPS unit for our family we gave it a name within a week. There was a human voice. That voice gave us instructions and told us when we made mistakes and needed to correct our route. It was like having a live person in the car with us. The kids liked the naming process because we tried to match a name with the voice that came from the device.nuvi-265wt

But something else happened.

We started to rate the instructions we received from the device. We would get a little excited when we knew multiple ways to navigate a route and preferred another option from what the GPS determined to be the best route. We would talk to the device as if it could understand us and tell it that we knew a better way. We would stay on the larger interstate when the GPS wanted us to exit and drive on smaller two-lane roads. .

But why?

It’s just an algorithm in a computer program. It’s performing math calculations to determine the shortest route between two distances. This particular version of the GPS did not have current information related to traffic patterns that factored into the algorithm. Yet we wanted to treat the unit like a person. We judged the instructions and the outcome and expected the GPS to know about new roads and road detours.

Do we judge algorithm mistakes differently than we judge human mistakes?

There was a recent story on NPR from Shankar Vedantam in which he discusses research from the University of Pennsylvania about human’s use of algorithms. The research found that humans will typically stop using a computer algorithm after they experienced a mistake even though the computer algorithm was less likely to make a mistake than a human counterpart.

Vedantam goes on to discuss that algorithms are getting smarter and more complex. They learn from mistakes. They have the ability to make decisions based on a variety of inputs. So it’s illogical to judge the algorithm more harshly than a human but yet it feels so natural to many people.

Do we feel threatened by algorithms? Perhaps movies like The Matrix or Ex Machina make us more aware of just what a truly learning algorithm could be like. Maybe that’s what influences us to judge simple computer programs more harshly.

I will say this.

When the GPS takes us on a tangent, I’m always the one saying “Trust her. She’s always gets us there.”  I stand by her instructions even though she’s taken me to a few dead-end roads.

But I’ve never trusted Siri. :-O

Onward and upward!