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About me: I'm an unrepentant generalist finding my way in a world of specialists. I started this blog to review books, but I now talk about topics ranging from management to cognition to social software.
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I was talking to somebody last week who had recently moved to San Francisco, and she randomly interjected Big Data into the conversation. She said she’d learned that’s what you do in SF – Big Data is a buzzword that can be used at any time on any topic. I found this amusing, because Big Data is becoming almost messianic – all of our problems will be solved once we have Big Data! Everybody should become a statistician or economist or data analyst!
My response? Don’t believe the hype.
The trends are unmistakable – humans are creating and capturing more data than ever before. IBM estimates that 90% of the data in the world today was created in the last two years. And the tools we have to sift through data are becoming ever more powerful, with open-source packages like Hadoop for map/reduce, and R for statistical computing.
This flood of data and the tools to analyze it are creating market opportunities for businesses and career opportunities for individuals – the story of Target identifying a pregnant teenager from her purchases is a founding myth of Big Data. And some credit Obama winning the presidency to data analysis. So why am I skeptical?
There is a belief that if we could only quantify everything, we would be in control. The management saying is “You can’t manage what you don’t measure.” So if we have more data, and can measure everything, we should be able to manage everything! Except that the world is not that simple. Just because something has been quantified doesn’t mean that it is good or meaningful data – how the data is collected can introduce biases or trends that render it useless for making decisions. And just because an analysis gives a numerical output does not make it into useful knowledge or wisdom.
What I am seeing in the rush to Big Data is the urge to quantify things before understanding them. Recording 600 metrics and tossing them all into a database creates a ton of data, and analysts can spend weeks or months looking through the data. But is that really driving value for an organization? Similarly, I’ve seen situations where an analyst uses a standard ARIMA model to forecast a trend with confidence (because it’s data-driven!), and later being surprised that the forecast is wrong because they never really understood the underlying data. Another example is when a consultant creates a 500-line Excel spreadsheet, where every possible variable is quantified and every change ripples through the spreadsheet… but of those 500 lines, 490 are assumptions, so it’s impossible to tell which variables really matter.
Another potential peril is when analysts start their work with a preconceived notion of the result they want to get. With Big Data, you have enough data to support almost any conclusion if you slice the data in the right way. One of my favorite stories about the perils of data analysis came from my time as an intern at CERN – a grad student was looking for a particular energy resonance from the L3 detector data, and displayed this beautiful graph showing that resonance. Dr. Sam Ting, Nobel Prize winner, smelled a rat – the result looked _too_ clean. He told the grad student to show the data with all of the filters removed, and the raw data showed nothing but noise. The student had applied the filters to show what he wanted to see. Note that I’ve seen similar things happen at Google – as a coworker commented to me recently, if even Google (and MIT grad students) can’t consistently get data analysis right, can anybody?
I worry that the quantification of the world in the form of Big Data is being seen by businesspeople as an end in itself, rather than as the tool it is. Like any tool, data analysis can be used well by those who have trained in its use, or it can be used poorly and cause damage by those without experience. Understanding data is hard. It takes time and effort, and while a well-constructed tool can accelerate that process, it doesn’t replace the need to sit and work with the data to understand its quirks and characteristics. After really understanding the data, you may discover that only 3 metrics out of 600 really matter, and so you don’t need Big Data to run your organization – just a dashboard with the 3 things that matter.
Big Data isn’t a silver bullet that will fix everything with your organization. It is a powerful tool that can help you better understand what is going on, but only if you spend the time to use it properly. Just because your analysts create output that is quantitative doesn’t mean it’s right. Trust, but verify. Use your judgment and all of your tools including walking around to figure out what to do, because in the end, you are the one responsible, no matter what the data says.
In light of my last post on the Anthropology of Innovation, it was apropos that I was just finishing The Idea Factory, by Jon Gertner, a history of Bell Labs and its impact on 20th century innovation. I actually also saw Gertner at the Computer History Museum in March, but had to wait a few months for the book to get through the hold queue at the library.
The book itself is a well-told story of the creation of Bell Labs and its rise to pre-eminence, mostly focusing on the 1930s to the 1950s. Bell Labs started off as just an R&D lab for AT&T, developing technology and materials to better enable phone calls. But in the 1930s, the director started to expand its mandate by hiring physicists and chemists to do basic research. During World War II, the lab was essential to the war effort, contributing to radar among other projects, and after the war, they were given the freedom to work on whatever they wanted. This led to the invention of the transistor in 1947, but also the conception of information theory by Claude Shannon in 1948 – two amazing leaps forward in how we think about the world.
The most interesting part of the book to me was how Mervin Kelly engineered a culture of innovation at Bell Labs that will probably never be rivaled. The idea that an industry lab would do research leading to thirteen Nobel Prizes is inconceivable today. To be fair, AT&T had a government-granted monopoly, so they could do research that wouldn’t pay off for 20 years, and know that they would still be in business to benefit. And to keep on earning that monopoly, they had to demonstrate that their research was contributing to the basic good of humanity – I was surprised to learn that they were required to license out all of their innovations for low cost, including the transistor. So that combination of monopoly-protected resources and a requirement to do good was a key factor in enabling Bell Labs to go beyond any other lab.
But Bell Labs wouldn’t be Bell Labs if it was just a monopoly-driven research lab. Kelly designed Murray Hill, the New Jersey home of Bell Labs, to be a building where people had to run into each other going back and forth. This is now pretty common (e.g. at Google, they have a micro-kitchen on every floor to encourage such congregation), but at the time was very unusual. He then populated that building with the smartest people he could find, regardless of their field of expertise – physics, chemistry, mathematics, materials science, electronics – every field was relevant to something AT&T was doing (e.g. going from the vacuum tube to the transistor required inputs from all of those fields). Another aside: the scope of what they had to create included all sorts of things I wouldn’t have thought of but were an essential part of building for the long term – the book talked about burying wood logs in swamps to see how they would hold up to 20 years of service as a telephone pole, or designing materials that could handle seawater so they could insulate their underwater cables.
Kelly also instituted a culture where these bright minds could work on what they wanted, and ask anybody anything – so if you wanted to ask Shockley (the inventor of the transistor) a question about semiconductor physics, you just went and did it. This created a cross-pollination of ideas, where you might have a cockamamie idea, but could go ask the world expert on it, who was just down the hall, and that might lead you together to think of a more reasonable idea, so you’d stroll down the hall some more to talk to an engineer who could build a prototype. And the challenges of running a nationwide communication network meant that there were always new problems to think about. This combination of challenges and bright minds and the need to turn ideas into real products led to an enormous number of breakthroughs.
It’s interesting that nearly a century later, the same principles are still at the forefront of creating innovation. The Anthropology of Innovation panel talked about breaking down silos between fields, and about focusing on the user (Bell Labs was always grounded by the mission of delivering the best possible service to somebody making a phone call). The principles are straightforward, but it’s hard to really apply them, and so it’s impressive to read about an institution that did so and was pre-eminent as a result for decades. I don’t think such a lab could exist today (again, the monopoly-protected revenue stream was a key component), but it’s an inspiring example of how to take those principles and create a beacon of innovation.
I like thinking about how to scale a company without making it feel like a big company. The standard way to scale a company is to use hierarchy and process to manage the larger scale – big decisions get passed up the chain to an appropriate decision maker, and little decisions are handled by a process that has been standardized.
But I have always disliked this approach, as it removes the initiative of smart and independent thinkers at all levels of the organization. Why hire smart people if you won’t let them think for themselves? I have long been fascinated by different management structures or bossless companies that trust their employees to make the right decisions. None of these organizations have been proven to scale past a few hundred people, though.
So how can we build companies that give autonomy to small teams while scaling up to thousands of people? Or to put a finer point on it, how can Google really be run like a startup?
As I watch the leaders at Google, I’ve realized that part of the answer is that the leaders tend to be consistent and principled. I work in the finance department, and Patrick Pichette, our CFO, is a master of this. He tends to ask the same set of questions:
That’s it. He’s so consistent that I feel like I can project his voice into a meeting, and so I have become an extension of him within the org. I understand the principles he uses to make decisions and can therefore give others a good sense of how he’ll react before they go into a meeting. I can also anticipate the questions he is likely to ask, and make sure that my team has good answers beforehand so we’re not scrambling afterwards.
What’s interesting about this to me from an organizational design perspective is that Google is not depending on process or hierarchy to guide me. The thing that keeps the finance org aligned is a consistent set of principles modeled by the CFO, who then trusts employees to use their judgment in applying those principles. That is an organizational model that can scale.
And when I thought about the rest of Google, I realized that’s a lot of what makes it work – each of us Googlers has an internal model of key decision makers (Larry Page, Patrick Pichette, Nikesh Arora, Susan Wojcicki, Jeff Huber, etc.) and has a good idea of how each of them would react to a proposal. That enables us to make decisions without having to pass them up the hierarchy and without having an explicit process, and still be confident that the decisions will be consistent with the corporate direction.
I think this is how a lot of other great companies have worked. Whether it’s Walt Disney or Steve Jobs or Herb Kelleher at Southwest, their people knew how their leaders would react and could act more independently because of that knowledge. It’s not quite a cult of personality, because that would imply that the followers have no independent thought and are only doing what they’re told. It’s more like teaching a team a playbook and letting them figure out how to apply it in their particular situation. I also read once that the military does a good job of this, making sure that everybody knows the overall strategic goals for an engagement, such that if the situation changes, they don’t blindly follow their orders to “Take that hill!” if it doesn’t help with the overall strategic goal (some Googling reveals this is called Commander’s Intent).
I like this idea of scaling by trusting your people to do the right thing while not hog-tying them with a process. It lets them adapt the leaders’ guiding principles to their individual situations such that they have autonomy, but without having the organization dissolve into chaos. It does have the challenge that it won’t work if you have bad people in the org, but my guess is that pretty much no management tactics work if you have bad people – they will circumvent your process.
Anyway. I’ve been mulling this over for a while, and figured it’d be a good topic for my first blog post in nearly a year. Work has actually been calm for a couple weeks, so I have finally overcome my activation energy to post. I need to make the time to do it more often, as I have dozens of post ideas floating around, and I like myself better when I’m writing regularly.
One particular issue I’ve been thinking about with startup vs. big company culture (and that is referred to in a comment on my last post as well as comments over on Facebook) is how to encourage useful failure – failure where you learn something and then apply what you learned to improve next time.
This sort of grit to struggle through failure (what Seth Godin calls “The Dip”) to find the next level of success is rare in a big company. As is typical for me these days, I would argue this is an issue of incentive alignment.
At a startup, walking away from a failure means quitting and finding a new job, whereas pushing through to find the bigger success (what Marc Andreesen has called product-market fit) has the potential for tremendous upside in the form of stock options. The risks are higher, but it’s worth it.
Big companies and their annual performance reviews tend to reward piling up little successes rather than long struggles with a big success at the end. Sticking with a project that isn’t working can lead to a bad performance rating, so people look for a quick transfer to a different project where they can ride on somebody else’s coattails to success and keep their ratings up. Those that do stick around and try to turn a failing project around rarely benefit from the upside if they succeed – maybe they get one good rating that doesn’t make up for the previous poor ones.
At an organizational level, it’s also easier for the big company to walk away from a “failure” because the company has other projects and revenue streams. As The Only Sustainable Edge points out, companies that only do one thing (e.g. startups) are driven to be the best in the world at it because they have nothing else to fall back on. That lack of a safety net drives further achievement than they would achieve if they could give up more easily.
Another perspective comes from this description of successful startups from Glenn Kelman (CEO of Redfin): “They weren’t afraid of failure, and they didn’t “pivot” when faced with their first setback”. And sometimes by having the grit to stick with a project that they were initially doing for their own passion without regard for commercial potential, they found a way to inordinate success.
How can we instill that kind of grit and passion into a big company? I can think of a few cases where a strong leader has bet the company on a change of direction (e.g. Bill Gates’s Internet memo, Steve Jobs turning Apple into a consumer electronics company, Jeff Bezos mandating that Amazon transform its infrastructure into a service-oriented architecture, Larry Page trying to focus Google on social), but this can also backfire (e.g. Elop’s “oil platform” memo). And these cases are more about a top-down change in direction rather than creating a new culture.
On the topic of encouraging useful failure, I could see some ways of trying to design an incentive system that would encourage people in that direction. Unfortunately, I think the people who work at a big company would rarely agree to such an incentive system. And in my experience, the people who would like such a system will try to do the right thing regardless of the incentive system.
So to re-state the question in a different way – is it possible to create more “startup” people who are willing to take chances and struggle through failure? I wonder if it would involve a re-design of our education system – the US education system is designed to reward people who follow directions and respond to incremental incentives (aka grades), and punishes those who fail even intermittently. Could any incentive system be powerful enough to overcome a lifetime of cultural conditioning?
Hard questions. I don’t have any answers. And, obviously, a lot of digressions. But I’ll keep exploring these sorts of topics over the upcoming weeks. Let me know if you have any thoughts.
Since Larry Page became Google’s CEO again in April, his focus has been on “making a company of more than 24,000 employees act like a startup“. And because of my interest in mapping out organizational space and understanding the different ways in which people can organize themselves, I’ve been trying to figure out what, exactly, differentiates a startup culture from a big company culture.
My current theory is that the difference is in incentive alignment. At a startup, it is difficult to be individually successful while doing the wrong thing for the company, because if the company fails, everybody is out of a job. At a big company, though, fiefdoms can develop, where within a fief, people can get promoted for improving the position of that group despite being obstructionist to the rest of the company. This is often what people disdainfully refer to as corporate politics.
This reminds me of Mancur Olson’s book Power and Prosperity, where he describes how it makes economic sense for special interest groups to subvert democracy in harmful ways – if they represent 1% of the population and push for an action that will benefit them while hurting the overall democracy, they reap 100% of the benefit but only feel 1% of the pain. A similar dynamic is at work for groups within big companies, where they push for their own agenda even when it might hurt the overall company’s position.
This difference in incentives drives many of the differences in behaviors between startups and big companies. At a startup, nobody says “That’s not my job” when asked to do something that’s critical to the company’s success, because they won’t have a job if the company isn’t successful. At a startup, people have an understanding of what drives the company’s success and re-prioritize on the fly if necessary if market conditions are changing. Everybody is invested both economically and personally in the startup’s success, and that drives a unity of purpose that overrides individual agendas.
At a big company, people want to avoid risks and perpetuate the status quo, because creeping up the corporate ladder is the safer path. It’s easier to say no than yes, leading to the big-company phenomenon where every new project has to be signed off on by 10 different departments (legal, finance, security, PR, marketing, sales, engineering, etc), creating 10 opportunities for “No” without having a single person that can say “Yes” and have it stick. It’s possible to get promoted and get paid more without doing anything to benefit the company, if you are advancing your group’s agenda and hitting your individual targets even if the targets are no longer meaningful.
So what does it mean to have a big company with a startup culture? Part of it is figuring out how to get everybody at the company aligned on what the priorities of the company are (this is incredibly difficult at a sprawling company like Google), and rewarding them appropriately. Part of it is to encourage appropriate risk-taking – rewarding those who said “Yes” when it was the right thing to do even if the project failed. Part of it is creating a more risky environment in general – the people who are attracted to safe big companies with a well-defined ladder are not the people that will function well in a startup culture where things are changing fast. And I’m sure there is lots more that I haven’t figured out yet.
I’m fascinated to be part of Larry Page’s Google experiment on creating a big company with a startup culture. I’m not sure it’s possible without addressing the questions of incentive alignment and risk I raise here, but I want for it to be possible. The scale of projects that can be done at a big company are mind-boggling, but I also miss the free-wheeling all-for-one-and-one-for-all culture at the startups I’ve been at in the past. I will be watching closely and looking for opportunities to help with this culture shift as somebody who has startup experience and is interested in these sorts of culture questions.
I was having a conversation with a friend the other day about what we thrived on in a job, and it was interesting to see how our perspectives differed. She talked about the thrill of fixing a problem, of figuring out what was happening, and designing a process or system to solve the problem forever. I talked about how I love the challenge of understanding how all the different parts of a system fit together and figuring out what actually matters. The conversation was a good reminder for me of how important it is to have the right mix of people to get things done in an organization.
I’ve been thinking about this recently as I start a new role at Google where I am trying to articulate to my new team the value that I bring. My strength is as a systems analyst – understanding all of the different parts of a complex system, seeing how they inter-relate, and being able to describe the levers that drive the whole system. This applies whether the system is conversation, corporate culture, or the intricacies of Google’s revenue. I believe that my ability to both understand the big picture as well as the details allows me to extract insights that other people could not from just one level. And I am driven to keep on poking at the system until I feel I understand which stimuli will provoke which responses. The collection of observations on this blog over the years is a reflection of my drive to understand.
However, I struggle in taking the understanding I develop and doing something about it. I can understand how the system is put together and where the friction in the system is, but not how to fix those things. Part of understanding the whole system is understanding why different design decisions were made in the construction of that system, and that understanding sometimes makes it difficult for me to envision a different way of doing things that would solve the issues I identify.
My friend is more pragmatic as she is more interested in fixing important things that are broken. She has worked in a couple different industries, and in each case, it was more about identifying the systemic things wrong with her company, and figuring out how to make them work better by instituting a new process or a new system element. She also has a good understanding of systems, as she wouldn’t be able to fix things effectively if she didn’t. But for her, it’s the fixing that matters, not the understanding.
I think both roles have value to an organization. And a particularly good combination is to pair an understander with a fixer so that the system insights that the understander develops can be fed to the fixer. An understander without a fixer identifies problems but those problems linger since nothing is being put in place to counter them. A fixer without an understander is sometimes fixing symptoms rather than the underlying problems that are driving problems in the system. Together, though, they can be a truly powerful force.
P.S. There are a few other themes inspired here that I’m going to set aside for a future post:
When I was considering whether to take a job in Google’s finance department, a successful entrepreneur friend of mine told me I was making a mistake. He felt that designers and engineers added value to the world by creating new products, but the only thing finance people did was to say no. Given the pride I had taken over the years in creating valuable products like the CellKey system, I wondered whether I was making the right choice.
After a couple years here at Google, I agree with my friend that there are far too many people within corporate finance departments that are beancounters. Their only goal is to make sure the sums add up and that the processes are being painstakingly followed. Anything that disrupts their routine is fought with every fiber of their being. I made a mistake last fall that meant that Google had to pay out invoices faster than net 30 terms, and I spent weeks begging the team in accounts payable to vary their process this one time. Other finance teams have frustrated me by sticking resolutely to their quarterly plans even when the environment had shifted since those plans were made.
That being said, good finance people provide a level of clarity and objective vision to the executives. Finance takes a separate look from outside the product domain to review revenue and cost trajectories, as my team at Google does for the Revenue Force team. Our CFO, Patrick Pichette, asks every product leader what they’re going to get done next quarter and what resources they’ll need to get there, and then he follows up the following quarter by evaluating their success on achieving those goals with those resources. By having that outside check, it forces product teams to re-evaluate their own success every quarter rather than trying to launch at all costs.
Finance can also help the executives make decisions across product lines. Product people often want to invest in all the cool ideas they have and won’t prioritize to make the hard tradeoffs, because it’s like choosing one’s favorite child. The finance team can provide a framework to the execs for valuing the different product initiatives for the company to help the execs make those tradeoffs at the corporate level. This doesn’t necessarily mean making decisions purely based on profits – corporate objectives might include other metrics like user adoption, as is the case for Google products like Chrome and Android. But having a consistent framework makes it easier to compare products across the company.
Evaluating the business model for a product is also part of finance’s responsibility. Even if a product is technically excellent, the business model surrounding it may not be successful (e.g. Signature going bankrupt despite the CellKey instrument being on the path towards success, or Google Wave). Good finance people understand the product vision and the potential market, but can tie those lofty goals back to the prosaic P&L statement, and provide a viewpoint on whether the assumptions embedded in that model make sense and are achieving corporate objectives.
Lastly, great finance people can change the way executives think by giving them a new way to frame their businesses. Because the finance team is looking at things from a different perspective, they can provide insights that the executive team might be missing. It means going beyond the numbers to provide strategic insight that changes the priorities of the executives. I’ve been fortunate enough to see my manager do this a few times with the Google execs, and the value of providing that new perspective is huge.
This vision of a good finance person is actually well aligned with the value I provide as a generalist, connecting different perspectives and providing new viewpoints based on integrating those perspectives together. So while I agree with my friend that product people are creating value in a more concrete way, I believe that finance people can create value through changing the way the rest of the company thinks about the business. We’ll see if I can start changing the way product people think about their counterparts in finance.
Scott Berkun just posted about situations in life where good data is impossible, which reminded me of a quote I’ve been meaning to share.
I once went to a talk by Bob Sutton where he cited a quote by Andy Grove, CEO of Intel:
“I think it is very important for you to do two things: act on your temporary conviction as if it was a real conviction; and when you realize that you are wrong, correct course very quickly.Investment decisions or personnel decisions and prioritization don’t wait for the picture to be clarified. You have to make them when you have to make them. You take your shots and clean up the bad ones later.
(So you have to keep your own spirits up even though you well understand that you don’t know what you’re doing)”
I think this is one of the hardest things to learn as I progress in the business world – many situations I’m asked to handle are novel, because routine decisions are handled by bureaucracy in the form of established processes or at a more junior level. Taking action when I know I don’t have enough data requires a leap of faith that I’m best positioned to make a decision anyway.
Babe Ruth pointing to the stands, and then hitting a home run.
Joe Namath guaranteeing a Super Bowl victory despite being an 18-point underdog, and then going out and winning it.
There’s something magical about calling your shot – telling people you’re going to do something impressive and then doing it.
Even in the workplace, the way to earn more credibility, more trust, and more freedom to do what you want without interference, is to call your shot. Tell your audience, whether it’s your managers, your team, or your investors, that you’re going to do something ambitious and then execute. Every time you call your shot and make it, you earn yourself a longer rope. If you watch the dynamics at your workplace, you’ll see this play out repeatedly.
Of course, the downside is that if you call your shot and fail, then you may lose credibility. It’s a risky ploy in that way.
But the bigger risk may be not committing to any goals at all for fear of failure. Not calling a shot means that you are subject to those around you – the freedom and credibility will go to those who take risks, while you are left behind.
Which risk do you prefer? The risk of inaction or the risk of trying something ambitious and failing? And does it change the decision to realize that trying and failing is more respected and more satisfying by far?
One of the broader points that I don’t know if I made clearly in my last post is that effective communication depends not only on the message you are delivering, but also on the audience which the message is targeting. In the case of writing a resume, you have to remember that you are targeting a busy hiring manager who will spend less than ten seconds in glancing at your resume before making a decision. To get the phone screen, you need to tailor your resume for that audience, rather than doing what is most convenient for you.
This idea of knowing your audience resonates in all aspects of business life. It’s difficult to design an effective communication without knowing who the recipient is. But if you know who are you speaking to and the message you want to deliver to that person, it makes it much clearer how to design that message to reach your target. For instance, when a presentation is not coming together, I am often able to help coworkers by asking who the target audience of the presentation is, and what message they want to deliver to that audience. I’ve learned from my manager to ask of each element of the presentation “So what?” – why should the audience care about what I’m presenting?
As an aside, another aspect of designing effective presentations is realizing that you need to get the audience’s attention in the first 30-60 seconds, just like with a resume. These days, every audience has their smartphones or their laptops in easy reach with lots of distracting possibilities. So your presentation has to grab their attention in the first minute, or they’ll tune you out and go catch up on email or Twitter or Facebook. Any presentation that depends on the audience paying attention for ten minutes before delivering any sort of pay-off is going to fail because the audience will have been lost. As with the resume, what you are really trying to do with a presentation is earn the right to the audience’s attention for a little while longer. Structure the presentation in such a way to deliver value to the audience throughout, or you will lose them.
Being able to understand your audience well either involves empathy or experience. Empathy in the sense that it depends on being able to put yourself in the position of your audience to understand what they care about. Experience can sometimes substitute for empathy as you may have been in the position of your audience yourself (e.g. my experience as a hiring manager has made it clearer to me what other hiring managers might be looking for on a resume). Either way, though, the first step is to step away from your own knowledge and needs to think about what your audience needs to get from your communication.
This is also a key skill as a product manager – understand the target user, figure out what problems they are having and design a new product or feature to solve their problem. All too often, product managers start from a self-centered point of view and create a new product/feature based on what they can offer without thinking through what their user wants. This is particularly common in larger corporations where the product managers are often separated by many layers from dealing with actual customers or users. Meanwhile, in my time at Fog Creek, I spent enough time on the phone doing tech support and sales that the perspective of our customers was never far from my consciousness. Again, either empathy for or experience as the potential user is crucial to making the right decisions.
Developing the ability to effectively construct communications for a variety of audiences, whether the communication is in the form of a presentation, a white paper, an email, or a product requirements document, is a skill that is essential to corporate life (and, really, all of life). So before your next important communication, think about who your audience is, what they want, and how you can construct your communication in such a way as to get your message across more effectively.
P.S. It’s interesting to note how my thinking on this has evolved slightly from my post in 2009 asking what is the story, as I now realize that getting the story right involves understanding the audience. Stories are not universal – they are just one way to convey a message from me to you.
