While we don’t get there 100%, though, I would argue that my program at Babson College gets closer than most other schools:

• Unlike traditional programs organized around a semester system, Babson eschews stand-alone courses for integrated, just in time knowledge delivery. Our first year is organized to follow the life-cycle of an archetypal corporation: evaluating the opportunity, assembling the team, developing the plan, securing funding, expanding operations, and becoming global. Subject matter such as finance, operations, and law are combined.
• Real-world experience is explicitly integrated. Every first-year student is required to complete a year-long consulting project for a local company. Many (if not most) second year students engage in unpaid, for-credit work projects: managing teams of undergrads, consulting for area businesses, managing the school’s endowment, or starting a business in the school’s incubator.

Babson is the entrepreneurship school. Most students don’t start their own companies but the focus throughout our two years is on identifying and realizing opportunities. For employers who primarily want someone to do valuations, or design marketing plans, of do cost accounting, we might not be the best choice. But for the sorts of businesspeople Seth Godin imagines, Babson could be just the right program.

Earned value, percent complete, and other measures of work performed on a project have always seemed useless. Perhaps that’s why I like Scrum so much–it only requires participants to estimate the hours of work remaining. Johanna Rothman wrote a short but important piece: Managing Product Development: There is No Such Thing as Percent Complete. While some of the comments are critical, I think they highlight the real challenges of giving a percentage. To pull out two:

The difference between Physical Percent Complete and Percent Complete needs to be clarified. On software projects where the delivered features are produced through Work Packages the comcept of Physical Percent Complete can be used. (Glen B. Alleman)

This is only a problem if you take the percentage as a percentage of time. A percentage of requirements fulfilled works just fine. (Michael Lucas Smith)

To be confident in % complete, you need to be confident in your estimates, in the amount of work completed, in the amount of work remaining, and in the speed at which the remaining work can be completed. That’s a lot of moving parts and merely watching the percentage change over time provides little insight into those underlying numbers.

When you ask a team member for percent complete, you’re generally only trying to learn two things: when will their work be completed and how will that timeline affect other parts of the overall project. Ask only the questions you need answered and you’re more likely to get the answers you need. The fact that it takes less effort to answer smaller and narrower questions is just gravy.

Photo by juliehicks75

In sixteen hours we leave for two weeks in Israel and Italy – a last hurrah before an MBA and a PhD in Social Work. While we’re both getting an extremely generous amount of assistance, money will be tight over the text few years and I’ve been wondering what tools the Internet provides for keeping track of our cash.

A while back, Lifehacker asked about good tools for budgeting. Perhaps not surprisingly, most users suggested Excel or other spreadsheet tools. Spreadsheets have the advantages of flexibility and ad hoc reuse. With the advent of Google Spreadsheets, Zoho Sheet, and other similar online tools the primary disadvantage–locking the user to a single computer–has been obviated.

Other commenters suggested Mvelopes, a full featured cash and financial management application, and Snowmint Budget, a desktop budgeting application. These both are based on the envelope budgeting methodology–fine if that’s what you want to follow but not so flexible for the rest of us.

PearBudget is a neat tool built in Excel that combines budget setting with budget tracking, but requires you to save and transcribe receipts. It looks like they’re working on a web version.

The downsides of these web and computer tools–that you need to be at a computer to use them–may be addressed by Filo, a printable expense register. Perhaps this (or any other paper-based expense tracker) could be combined with Pearbudget to avoid having to carry around receipts.

Some tools aren’t designed to help you track your spending. Instead, they motivate you to save. The Lunch Savings Calculator is one example: by being a cheap bastard with my PB&J I can save over $1000 a year!

If your problem is paying bills on time, perhaps reminder services like billQ would, erm, fit the bill.

The problem with most of these solutions are that they don’t provide the full solution set (building a budget, tracking expenses, and measuring performance), lock you in to a proprietary platform, and require that you physically be at a computer. My requirements would be:

• Ability to set budget categories, amounts, and time frames arbitrarily
• Ability to record expenses as they happen with little or no data reentry
• Ability to generate reports showing actuals vs. budgeted, where the money’s going, etc.
• Live access to budgeting an expense data in a structured format like XML for analysis wherever and however I like

Unfortunately, I have yet to find what I want. Lifehacker has a clever trick that accomplishes some of what I want–they hack up some Perl scripts to interface with AIM to allow users to instant message or SMS their expenses. Ubiquity is provided, and the data is accessible as a local text file, but it’s hardly convenient for the non-techies among us.

Finally, we must not be the only ones stressing about money. Also via Lifehacker is Oprah’s Debt Diet.

The best book I’ve read about managing money is the Five Rituals of Wealth. It teaches that wealth comes from the discipline to know where your money is spent.

1. If you’re going to go through a process more than once, build a tool and automate it.
2. You’ll never do anything just once.

That said, for many of us (particularly non-developers) there’s a substantial cost to building that tool. I’m not so good with Perl or Ruby or Visual Basic and often I’d find that the tool that took me so long to build didn’t really meet my needs. If I were a better toolsmith, I could just build one to throw away, learn from my mistakes, and build a second that’s better. Instead had to postpone the building, struggle with the manual process, and hope to use that struggle to really suss out the requirements for automation.

I think that organizations are in a similar situation: they’re often encumbered by too many manual processes and in need of better tools. But just like individuals, before you start building the tool it pays to know if you’re a good toolsmith. Organizations with those skills know to build their first version quickly, try it out, throw it away, and try again, learning from their mistakes. Most organizations, like most of us, are bad at building their tools. IT projects come in late and frequently don’t meet users needs. Does that sound like you? Don’t jump to build the tool, but take your time, pay attention to the manual process, and really understand what you’re trying to do.

(On reread, you could just think of the manual process as a first draft for people and organizations that aren’t good at developing software tools.)

He quotes Brad DeLong indicating that between 1980 and 2004, the share of private national income earned by the top 1% of wage earners doubled from 8% to 16%. As usual, I have a few responses:

• After reading through the responses, I agree that single year rates can be misleading as many individuals may end up in the top 1% after cashing out an asset in which they had been investing earnings. For example, the small business owner who takes a smaller salary but sells for half a million dollars. A more interesting measure would look at lifetime earnings by some population cohort.
• Cost of living tends to have a more egalitarian distribution than earnings. Within a geography, health care, food, and transportation costs tend to be fairly equal. If anything, the wealthy tend to have better prices in the form of cheaper food, lower interest rates, and generally more choice (which may be offset through upscale brands, etc.).
• Finally, it’s worth noting that an increase in earning is very different from an increase in utility. In fact, those who make the most are best able to lose the most. I can’t spend $300k a year – therefore, it’s easy for me to set aside a third of that for a risky investment. Even if I make $100k per year–a very nice salary–I’ll be much less able to afford to lose any of that. My investments will be less risky and therefore, in general, less profitable.

Keeping in mind that I have absolutely no hard data to back me up, I think that Professor Cowen touches on one primary cause in mentioning, “[A]n increase in the ability of very smart and very wealthy people to buy up undervalued assets and turn them into greater value.” I’m not sure that smarts enters into the equation. What the wealthier have (and the wealthiest have lots of) is sufficient liquidity to take advantage of opportunities. Some of these opportunities will come in the form of real or financial assets, but others will take the form of moving cross country to follow job prospects, taking a few years off of school, or even deferring salary in the first place to start a company. See above with regard to risk and reward.

There’s also the nasty possibility of rent seeking behavior. Given the constant news of government bribery scandals and under performing firms getting generous government contracts we would expect that some amount of that excess income could be invested in bribery, graft, and lobbying.

Closely related is the principal-agent problem. Especially in an economy with rapidly advancing communications and information technologies, we would expect the cost (in terms of time as well as dollars) of identifying opportunities to increase. The “agents” in our economy: lawyers, realtors, other professionals and elected officials have pursued their own rent seeking behavior and those with the least excess are least well able to discern good advice from bad. Scandals with Ameriprise Financial, physician owned hospitals providing sub-par care, trial lawyers who take too large a share of a settlement, and graft-seeking congresspeople are some recent examples.

I see nothing inherently wrong with hard work and business success rewarded with wealth and I’m confident that most of the wealthy in this country have honestly earned that status. At the same time, concentration of wealth introduces and encourages some (economically) bad behaviors and it behooves us all to identify and correct them.

“From Manufacturing to MIS and Medicine: The Theory of Constraints in Knowledge Industries”

“Limits of the Balance Sheet: How Financial Reports can Obscure Operational Problems”

“Aligning Operations and Strategy using the Discipline of the Project Triangle”

In reading the comments, it was interesting to note that almost all conversation seemed focused on whether it was appropriate for individual CEO compensation to be linked to market capitalization. My read was slightly different. The research makes an empirical observation about CEO salary in aggregate, and comparing that to aggregate market capitalization. It doesn’t surprise me that individual CEO pay would be more linked to market performance than individual performance–that’s the way other knowledge worker salaries are negotiated. My best developer and my worst developer earn roughly the same amount.

For those interested in examining the relationship between CEO compensation and company performance, I would like to suggest another test: If it’s expected that large firms are expected to a market driven salary for their CEO, and if it’s assumed that every large firm needs a CEO, there should be little relationship between a firm’s spending on CEO pay and the firms financial performance. Commenters seem agreed on this point. Instead, measuring a relationship between CEO performance and corporate performance would require measuring CEO pay from the CEO’s perspective, and this requires a cumulative measure. Something like average annual salary during period when active in CEO labor market would work. My hypothesis would be that while instantaneous employed CEO compensation is relatively flat, CEOs of more successful companies would spend a greater percentage of their time in the labor market actually employed. Assuming a strong positive relationship between time employed and total compensation (another testable hypothesis) we would have a better indication as to whether CEO pay is reflective of corporate performance.

UPDATE: One additional thought: as stock options and stock grants were considered CEO compensation in the research study, increases in market capitalization would directly increase CEO pay. As stock options become a larger percentage of CEO compensation the effect will increase. Seems like the same variable is being used in both sides of the equation.

Which route is more efficient?

This isn’t really an SAT question – it’s a management question and it illustrates the problem with questions of efficiency and similar fuzzy concepts of effectiveness. My car gets about 33 miles per gallon at highway speeds. In stop and go congestion, though, my car’s only getting 15 MPG. Which is more efficient? In terms of total gas use, the numbers are reversed. The usual route will only use a gallon while the alternate will require almost 50% more. On a “gallon’s per commute” basis it’s better to sit in traffic. Of course, there’s also the issue of efficient use of my time – what’s the value of 15 minutes driving saved?

This is the same problem faced when juggling the trade off between project cost (typically a function of people hours worked) and project (calendar) time. Project management metrics can illustrate the problem and the trade offs but in the end it’s a matter of differential valuation of requirements: a matter of values.

(As an aside, it’s interesting that hybrid systems like the Toyota Prius tackle efficiency at both ends. A very small gasoline engine provides even better highway mileage while the low horsepower but high torque electric engine prevents wasteful idling and low-RPM movement in stop and go traffic.)

This concept is promoted by Eliyahu Goldratt and his Theory of Constraints and in his books like The Goal. He argued that in in the case of discrete manufacturing–where individual goods are produced in a continual but not continuous process through the discrete application of heterogeneous transformations–as the utilization (or efficiency) of the individual steps approaches their maximum, the productivity (or throughput) of the system as a whole approaches a minimum. Now, software development looks to me a lot like discrete manufacturing. You have a set of inputs of varying quality: requirements, best practice documents, etc. In a factory, the machines that perform a step in the manufacturing process often differ – they could be different models, have different maintenance histories, have different tolerances with regards to inputs or throughput, or produce at different levels of quality. Tom DeMarco reminds us that knowledge workers–and this includes the analysts, designers, developers, and engineers–are similarly not fungible. Not only does each individual have their own specialties and deficits but people have task switching costs analogous to the set up costs with factory machines.

While Slack was the first book I read to apply TOC methodologies to software development, I’ve been noticing that it’s not an uncommon perspective. The Agile Management Blog is thick with these ideas as is Steve Hebert’s Development Blog, the Creative Generalist, and Frank Patrick’s Focused Performance Weblog.

Using the TOC approach provides two primary advantages:

1. The opportunity to apply an empirical science to the fuzzy art of software development management–and a science tested in modern manufacturing industry.
2. A concrete and tested method for examining, evaluating, understanding and improving your development processes

As the name implies, a central tenet of TOC is the identification of your system’s primary constraint. Often called the bottleneck, this the step in your system that controls the maximum throughput, and systemic throughput, according to TOC, is the most important metric of effectiveness. As the constraint control the throughput of a system, no increase in resource utilization outside the constraint will increase systemic throughput. The only option, then, is to increase utilization of the constraint itself.

In the software world, the constraint could be code review by the lead architect. It could be sign off by legal. It could be client feedback. It could be any number of things. However, once the constraint is identified there are a limited number of available actions:

1. Add capacity to the bottleneck. Typically this means increasing the number of people who can perform the bottleneck task(s).
2. Ensure the bottleneck only does high quality work–improve the quality of its inputs. Before the architectural code review, code could be peer reviewed. The legal department could prepare guidelines or an inexpensive paralegal. Internal client surrogates could be used.

Remember, though, that these changes can possibly move the bottleneck. Code review is fine but QA is stalled. Client feedback is coming in fast and furious but issues are no longer being adequately prioritized. Moreover, resources cannot be added indiscriminately–there’s still a cost to task switching and adding resources to an already late project typically only increases the delay.

That’s enough out-loud thought for me. Something to think about – what limits your organization’s productivity? And what can you learn from other disciplines?