Good ideas but no delivery are just unless.
Wednesday, November 7, 2012
Saturday, October 6, 2012
To Succeed with Big Data, Start Small
While it isn't hard to argue the value of analyzing big data, it is intimidating to figure out what to do first. There are many unknowns when working with data that your organization has never used before — the streams of unstructured information from the web, for example. Which elements of the data hold value? What are the most important metrics the data can generate? What quality issues exist? As a result of these unknowns, the costs and time required to achieve success can be hard to estimate.
As an organization gains experience with specific types of data, certain issues will fade, but there will always be another new data source with the same unknowns waiting in the wings. The key to success is to start small. It's a lower-risk way to see what big data can do for your firm and to test your firm's readiness to use it.
The Traditional Way
In most organizations, big data projects get their start when an executive becomes convinced that the company is missing out on opportunities in data. Perhaps it's the CMO looking to glean new insight into customer behavior from web data, for example. That conviction leads to an exhaustive and time-consuming process by which the CMO's team might work with the CIO's team to specify and scope the precise insights to be pursued and the associated analytics to get them.
Next, the organization launches a major IT project. The CIO's team designs and implements complex processes to capture all the raw web data needed and transform it into usable (structured) information that can then be analyzed.
Once analytic professionals start using the data, they'll find problems with the approach. This triggers another iteration of the IT project. Repeat a few times and everyone will be pulling their hair out and questioning why they ever decided to try to analyze the web data in the first place. This is a scenario I have seen play out many times in many organizations.
A Better Approach
The process I just described doesn't work for big data initiatives because it's designed for cases where all the facts are known, all the risks are identified, and all steps are clear — exactly what you won't find with a big data initiative. After all, you're applying a new data source to new problems in a new way.
Again, my best advice is to start small. First, define a few relatively simple analytics that won't take much time or data to run. For example, an online retailer might start by identifying what products each customer viewed so that the company can send a follow-up offer if they don't purchase. A few intuitive examples like this allow the organization to see what the data can do. More importantly, this approach yields results that are easy to test to see what type of lift the analytics provide.
Next, instead of setting up formal processes to capture, process, and analyze all of the data all of the time, capture some of the data in a one-off fashion. Perhaps a month's worth for one division for a certain subset of products. If you capture only the data you need to perform the test, you'll find the initial data volume easier to manage and you won't muddy the water with a bunch of other data — a problem that plagues many big data initiatives.
At this point, it is time to turn analytic professionals loose on the data. Remember: they're used to dealing with raw data in an unfriendly format. They can zero in on what they need and ignore the rest. They can create test and control groups to whom they can send the follow-up offers, and then they can help analyze the results. During this process, they'll also learn an awful lot about the data and how to make use of it. This kind of targeted prototyping is invaluable when it comes to identifying trouble and firming up a broader effort.
Successful prototypes also make it far easier to get the support required for the larger effort. Best of all, the full effort will now be less risky because the data is better understood and the value is already partially proven. It's also worthwhile to learn that the initial analytics aren't as valuable as hoped. It tells you to focus effort elsewhere before you've wasted many months and a lot of money.
Pursuing big data with small, targeted steps can actually be the fastest, least expensive, and most effective way to go. It enables an organization to prove there's value in major investment before making it and to understand better how to make a big data program pay off for the long term.
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Get Started With Big Data: Tie Strategy to Performance What If Google Had a Hedge Fund? Can You Live Without a Data Scientist? How to Repair Your Data
Successful prototypes is certainly the key with a small but reasonable sample size.
How to Present to Senior Executives
Senior executives are one of the toughest crowds you'll face as a presenter. They're incredibly impatient because their schedules are jam-packed — and they have to make lots of high-stakes decisions, often with little time to weigh options. So they won't sit still for a long presentation with a big reveal at the end. They'll just interrupt you before you finish your shtick.
It can be frustrating. You probably have a lot to say to them, and this might be your only shot to say it. But if you want them to hear you at all, get to what they care about right away so they can make their decisions more efficiently. Having presented to top executives in many fields — from jet engines to search engines — I've learned the hard way that if you ramble in front of them, you'll get a look that says, "Are you kidding me? You really think I have the time to care about that?" So quickly and clearly present information that's important to them, ask for questions, and then be done. If your spiel is short and insightful, you'll get their ear again.
Here's how you can earn their attention and support:
Summarize up front: Say you're given 30 minutes to present. When creating your intro, pretend your whole slot got cut to 5 minutes. This will force you to lead with all the information your audience really cares about — high-level findings, conclusions, recommendations, a call to action. State those points clearly and succinctly right at the start, and then move on to supporting data, subtleties, and material that's peripherally relevant.
Set expectations: Let the audience know you'll spend the first few minutes presenting your summary and the rest of the time on discussion. Even the most impatient executives will be more likely to let you get through your main points uninterrupted if they know they'll soon get to ask questions.
Create summary slides: When making your slide deck, place a short overview of key points at the front; the rest of your slides should serve as an appendix. Follow the 10% rule: If your appendix is 50 slides, create 5 summary slides, and so on. After you present the summary, let the group drive the conversation, and refer to appendix slides as relevant questions and comments come up. Often, executives will want to go deeper into certain points that will aid in their decision making. If they do, quickly pull up the slides that speak to those points.
Give them what they asked for: If you were invited to give an update about the flooding of your company's manufacturing plant in Indonesia, do so before covering anything else. This time-pressed group of senior managers invited you to speak because they felt you could supply a missing piece of information. So answer that specific request directly and quickly.
Rehearse: Before presenting, run your talk and your slides by a colleague who will serve as an honest coach. Try to find someone who's had success getting ideas adopted at the executive level. Ask for pointed feedback: Is your message coming through clearly and quickly? Do your summary slides boil everything down into skimmable key insights? Are you missing anything your audience is likely to expect?
Sounds like a lot of work? It is, but presenting to an executive team is a great honor and can open tremendous doors. If you nail this, people with a lot of influence will become strong advocates for your ideas.
This is the first post in Nancy Duarte's blog series on creating and delivering presentations, based on tips from her new book, the HBR Guide to Persuasive Presentations (October 2012).
A skill that is highly needed in nowadays challenging business.
Monday, October 1, 2012
Are Entrepreneurs Really More Comfortable with Risk?
Most people think entrepreneurs are willing to take on more risk than the average person. I've often wondered if that's really true. After almost three decades of working with large corporations and entrepreneurs, I've developed a theory. Now, this theory hasn't been vetted with controlled experiments and testing. It is based solely on experiential and intuitive data drawn from my life experiences. For instance, I have 12 years of working with entrepreneurs as an early-stage venture capitalist; 19 years working for a large corporation (Bell Labs & AT&T) and consulting to their multi-national, multi-billion dollar customers; 10 years of mentoring entrepreneurs; and created a carve-out start-up within AT&T.
Here's my theory: most entrepreneurs aren't more risk-o-philic than anyone else — they just define risk differently.
For some I've known, the risk of losing autonomy and control of one's "destiny" was far riskier than losing "guaranteed" income and benefits. Working for someone else's company, reporting to a boss, and living under rules they weren't sure made sense were a lot riskier than creating their own business. The risk of not pursuing their passion, of not making a meaningful and significant impact on the world around them, feels much riskier than starting their own venture.
For them, risk isn't as defined by losing tangibles (e.g., income, benefits, "stuff") as it is by losing intangibles: fulfilling a passion that won't let go, defining their own sense of purpose, sating their own curiosity, looking themselves in the mirror.
The difference here is between risking outputs and outcomes. Outputs (such as products, profits, etc) are necessary and good, but they have their most profound effect when driving significant, palpable outcomes — like reducing chronic pain, creating a prosthetic leg for an Olympic runner, or inventing an app that eliminates a time-consuming task. Most of the entrepreneurs I've worked with would gladly risk a few outputs for an outcome they believe in.
For many entrepreneurs, another critical risk worth taking is making themselves vulnerable in order achieve the outcomes they envision. As John Hagel has said, the risk of embarrassment, ridicule, skepticism, perhaps even humiliation is much less than the risk of not putting oneself out there to try. Anthony Tjan astutely summarized it this way: "The willingness to be vulnerable isn't driven by the desire for exposure, but by the possibility of what that exposure might lead to — be it a meaningful role, the possibility to affect change, and, of course, greater financial gain."
I've seen, heard, and felt so many entrepreneurs' intense passion and purpose for the outcomes they want to create. It is what defines who they are and why they're here. I know that risk-reward equation. While food, shelter, education, and health matter a lot, I need to see outcomes when I look my children, husband, friends and clients in the eye, not just outputs. If I don't see a positive, wonderful impact on their lives and the lives they are responsible for and encounter, then my life was just a series of outputs — maybe even large ones — but not outcomes; and I will have failed tragically.
While this is a theory ripe for a more scientific validation, I'm pretty confident it will prove out, at least in some great part. The risk of not pursuing that passion, of not fulfilling that purpose, of having lived a life of stuff without also living a life of significance, is the greatest risk of all.
They are more willing to take the risk to the level where cooperates aren't willing to go and could be yes, because they define risk differently as the article says.
Tuesday, September 25, 2012
Accepting that Managers need a vital Performance Management Process to sustain a business, who should define and manage the tools that make it work?
Last week I had the chance to sit in on a review of an Executive Information System used in a leading Power Utility. The implementation was done on a mature infrastructure covering end-to-end from ERP, finance and planning, considered as the whole bu
My latest piece
Friday, September 7, 2012
Use Big Data to Predict Your Customers' Behaviors
"It's tough to make predictions, especially about the future." So said Yogi Berra, baseball great and amateur philosopher.
Sensible (and amusing) as it sounds, his dictum no longer rings true. The Age of Big Data has arrived — and, with it, the ability to predict the future is increasingly a part of a new business reality. Whatever your discipline, doing business today means immersing yourself, and your organization, in a wealth of messy, unstructured, real time data from customers, competitors, and markets — and finding ways to use such data visibility to see what's coming.
Advantage lies in a capacity to predict the future before your rivals can — whether they're companies or criminals. Consider how the New York Police Department is using Big Data to fight crime in Manhattan. According to a series on Big Data in The New York Times, the NYPD and other big city police departments are using data-crunching technology to geo-locate and analyze "historical arrest patterns," while cross-tabbing them with sporting events, paydays, rainfall, traffic flows, and Federal holidays to identify what NYPD calls likely crime "hot spots." As immortalized in a "Smarter Planet" commercial from IBM, such insight can help deploy officers to locations where crimes are likely to occur before they are actually committed.
The beauty of such Big Data applications is that they can process Web-based text, digital images, and online video. They can also glean intelligence from the exploding social media sphere, whether it consists of blogs, chat forums, Twitter trends, or Facebook commentary. Traditional market research generally involves unnatural acts, such as surveys, mall-intercept interviews, and focus groups. Big Data examines what people say about what they have done or will do. That's in addition to tracking what people are actually doing about everything from crime to weather to shopping to brands. It is only Big Data's capacity for dealing with vast quantities of real-time unstructured data that makes this possible.
For example, retailers like Wal-Mart and Kohl's are making use of sales, pricing, and economic data, combined with demographic and weather data, to fine-tune merchandising store by store and anticipate appropriate timing of store sales. Similarly, online data services like eHarmony and Match.com are constantly observing activity on their sites to optimize their matching algorithms to predict who will hit it off with whom. The same logic is being applied to economic forecasting. For example, the number of Google queries about housing and real estate from one quarter to the next turns out to predict more accurately what's going to happen in the housing market than any team of expert real estate forecasters. Similarly, Google search queries on flu symptoms and treatments reveal weeks in advance what flu-related volumes hospital emergency departments can expect.
Much of the data organizations are crunching is human-generated. But machine sensors — what GE people like CMO Beth Comstock called "machine whispering" when I talked with her this past summer — are creating a second tsunami of data. Digital sensors on industrial hardware like aircraft engines, electric turbines, automobiles, consumer packaged goods, and shipping crates can communicate "location, movement, vibration, temperature, humidity, and even chemical changes in the air." As the volume of both human and machine data grows exponentially, so too will organizations' ability to see the future.
The net of all this is hardly a cold quantitative world. Rather, as marketers and machine systems learn more about our attitudes and behaviors, they're likely to achieve greater intimacy with consumers and customers than ever before. Yes, there is the risk of an Orwellian nightmare, if the inferences from Big Data become too intimate and too intrusive — and end up in the wrong hands. But there is also the opportunity to deliver services and marketing with unprecedented precision and accuracy, meeting and exceeding customer expectations in preternatural ways at every turn. Knowing the right time to deliver the right message (or action) in the right place before the time has come will bestow extraordinary power to those who wield such intelligence with intelligence. Use prediction wisely, and Big Data has the potential to make the world small again. That is every marketer's dream: getting closer to customers.
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CUSTOMER INTELLIGENCE INSIGHT CENTER
Using Market Research Just for Marketing Is a Missed Opportunity Can Big Data Smoke Out the Silent Majority? Retailers Turn to "Soft Surveillance" to Fight Customer Anonymity What Data Can't Tell You About Customers
It's coming, faster than you can crunch.
More Vacation is the Secret Sauce
For the first time in many years, I didn't take a vacation during the winter. It was a costly mistake. By the time I left for vacation three weeks ago, I was feeling spent. That's not a complaint. One reason for my fatigue is that The Energy Project has grown so rapidly during the past year. Managing our growth has prompted a whole new set of challenges.
For the first two weeks of my summer vacation, I let work go almost completely, in part because I had nothing left to give and in part because I knew how valuable it would be to chill out. I played tennis and worked out. I spent time walking on the beach with my wife. Family members came for visits, and we spent a lot of time just talking on the porch. I also read a lot of books — mostly fiction, which I rarely do when I'm working.
I did check my email occasionally, but I rarely responded. Each day, I felt a little more rejuvenated, much the way you sense your strength returning after an illness. In truth, I was hoping time away from the office might prompt some creative thoughts about our business, but for two weeks not a single interesting idea entered my mind.
In the third and final vacation week, something changed. I felt drawn back to reading non-fiction, specifically to books related to my work. I reread Tribal Leadership, which makes a compelling case that the vast majority of leaders operate at sub-optimal levels of personal development, and that the higher the level they reach, the more successful their organizations become. I also read The Fear of Insignificance, an extraordinary book by the Israeli psychiatrist Carlo Strenger about how our behaviors are powerfully, unconsciously and often pathologically influenced by our deep need to feel we matter.
These books, along with a couple of others, shifted my mind into high gear at a time when I was unburdened and undistracted by the preoccupations of everyday work. In short, I had time to truly reflect and think strategically rather than tactically.
I also learned about the importance of vacations from observing others on our team. The intensity of demand had begun to wear them down, too, and it showed up in a collective tendency to be more emotionally reactive — shorter and sharper — and more willing to settle for an easy solution rather than do the hard work necessary to get the best result.
I encouraged people to take longer vacations — we give four weeks beginning the second year of employment — and most did. Two of our employees (who happen to be married) went to Amsterdam for two weeks, fell in love with it and asked if they could work from there for a third week. They worked U.S. hours, set up their phones so clients could reach them dialing their regular office numbers, and it came off seamlessly.
The result is we're headed into the fall with an office of people recharged and eager to face a busy season. The one employee who didn't get away, in part because she was overseeing our move to new offices, grew more and more exhausted until I finally told her she had to take time off. Literally the next morning she ended up in the hospital with an infection. The cause wasn't exhaustion, but I can't help believing it must have made her more vulnerable to illness.
At a broader level, the famed Framingham Heart Study followed 750 women with no previous heart disease over 20 years. Those who took the fewest vacations proved to be twice as likely to get a heart attack as those who took the most. A 2005 study of 15,000 women found that the risk of depression diminished dramatically as they took more vacation. A 2006 Ernst & Young study found that for each additional ten hours of vacation employees took, their performance reviews were 8 percent higher the following year.
The problem is that in the face of relentlessly increasing demand, we're collectively vacationing less and for shorter periods of time. What's the solution?
- Take every day of vacation you're given. Don't hold it over and don't tell yourself the story that you don't have the time to spare. You'll get more overall work done at a higher level of quality if you take your vacations.
- Take some sort of vacation (even if you stay at home) at least every three months.
- Truly disengage when you go on vacation. If you don't, you'll be trading away the value of taking one. If you feel you have to answer email, set aside one short period to do so, and then disconnect the rest of the time.
- Don't settle for three or four days off. Short periods are fine, but they're not sufficient. If you have an intense job, my experience is that it takes at least two consecutive weeks away from work to fully restore yourself.
As they say, "Take every day of vacation you're given"
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