Friday, April 26, 2013

Exercises in PowerPoint Style

PowerPoint gets trashed in conversations all over the globe, and with good reason. As Edward Tufte has explained in The Cognitive Style of PowerPoint and Peter Norvig masterfully illustrated in The Gettysburg PowerPoint Presentation, PowerPoint has led to innumerable disastrous presentations.

But not all PowerPoint presentations are disastrous. The best PowerPoint decks incorporate fundamental principles of communication and visual design. The best PowerPoint decks actually enhance communication, and they do so through a wide variety of communication styles.

It's this wide variety of communication styles that led me to make a connection between PowerPoint and Raymond Queneaus' classic work, Exercises in Style, first published in  French in 1947. In Exercises in Style, Queneau tells a very simple, almost inane story. And then he retells the same story 99 times in 99 different styles with labels like metaphorically, hesitation, precision, animism, official letter, blurb, noble, speaking personally, and of course polyptotes.

I've embarked on a parallel project, using PowerPoint. This morning I uploaded 4 PowerPoint decks to SlideShare. Each uses a different style to communicate about the same fictitious project. I plan to add new styles on more or less a weekly basis, starting with styles that can be effective when matched with the right circumstances. The four I created and uploaded this morning are:

  • Bare Outline. This is the simple, boring shell that the rest of the styles are based on.
  • SBAR. This one uses a format created in the patient safety world to succinctly communicate about patients. In this case, I use the SBAR format to describe a software development project.
  • Butterfield Powerbite. This is based on the scheme I use most frequently to organize everything from presentations to short emails to announcements at staff meetings. Dick Butterfield taught me the scheme.
  • Inspirational. This one addresses the same fictional project from the point of view of a senior leader inspiring her workforce to rise to a challenge.
I'm having fun with this so far. Check it out and let me know what you think.

Friday, April 19, 2013

Managing Through Influence

I can accomplish very little on my own. So I put a lot of time into influencing other people. This can be especially difficult in a large company, where I need to influence people above me in the hierarchy, people in other departments, and often people I've never even met. Here are some ways I manage through influence, with special thanks to Creative Good Council 1 for their help expanding and fleshing out the list. 

Think of this as 20 tips for developing the art of influence.

As I walk through the list, I'm assuming you have a "target"--a specific individual whose behavior you want to change. I'll group the tips into 3 principles:
  1. Work the relationships
  2. Motivate and inspire
  3. Be practical

Work the Relationships

I can sometimes influence someone with whom I do not have a strong relationship, but it's a steep hill to climb. I always start by understanding, building, and leveraging relationships.

  • Align around something shared. Find something in common with your target. It could be anything from shared values (e.g., we both care deeply about the future of our organization), shared goals (e.g., we both want to meet the June 1stdeadline), or even something completely unrelated to work (e.g., we both love Louis Armstrong's early recordings). The more specific you can get, the better.
  • Understand the web of relationships. Everyone is influenced by someone else. Find out who your target trusts, obeys, follows, or listens to. If you can't directly influence your partner, find the path between you and your target. If your target is Alice, and Alice reports to Bernice, you need to influence Bernice. Maybe you have no influence over Bernice, but Bernice trusts Carlos, and Carlos has great respect for you. Once you've figured out this path of influence, you can get Carlos to talk to Bernice to give Alice an assignment.
  • Identify the saboteurs; defuse the bombs. Take some time to think through who may oppose your work and how they might wreak havoc. Is there someone who will tell your target not to listen to you? Is there someone in a position to make your target's efforts ineffectual? If you don't know, ask someone who does know. Then make an explicit plan for how to neutralize the negative impact. By far the most powerful way to do this is to convert your detractor into your champion. Another tried and true method is to keep the detractor busy with something else--find a way to get them focused on some work that keeps them out of your way. This doesn't have to be cynical or Machiavellian--many people can serve their customers and company better by staying focused on things they can actually accomplish rather than sabotaging the work you're trying to accomplish.

Wednesday, October 20, 2010


I'm at the Mobile Health Expo in the Ceasars Palace Convention Center in Las Vegas. Having succussfully maneuvered past Barry Manillow, Cher, Donny & Marie Osmond, and 20,000 slot machines, I encountered NoMoreClipboard and their interesting use of PHRs with low income diabetes patients.

Looks pretty straightforward—view portions of the medical record, enter blood glucose, send prompts to patients and to physicians.
Uses desktop web, mobile web, and SMS

They’re conducting a pilot w/ Howard University Hospital Diabetes Treatment Center in Washington, DC, in neighborhoods that have a high incidence of diabetes. Patients are typically low income and either Medicaid or uninsured. The program begins with community-based screening and initial treatment in a tricked-out RV (aka mobile health clinic). In the RV, their information gets entered in Howard’s EMR.

When they get off the RV, the patient is greeted by a “PHR Educator” (first time I’ve heard that term). The PHR Educator gets them set up with an account, which includes downloading their data from the Howard EMR system into the PHR, as well as filling in gaps in the data. Patients are encouraged to enter their glucose readings several times/day. About every three months, they collect HEDIS data from patients via online surveys.

They have 232 patients using the system so far. They've only recently launched the mobile component, and it's growing fast.

For the patients: The program provides “medical minutes,” essentially subsidizing part of the patient’s data plan. But they’re very clear that they don’t want to pay for everything. The patient needs to pay for at least part of the phone and part of the data plan, to ensure they have skin in the game. The program will provide new phones, or patients can use their existing phones.

For the physicians: Cupcakes. They’ve succeeded in getting clinical buy-in by providing cupcakes. Every time a physician gets another 20 patients signed up, they get a hand-delivered box of Georgetown Cupcakes, which are evidently delicious.

Preliminary findings & observations
  • Not all the patients use the system, but those who use it tend to use it a lot. This is consistent with findings from the California Health Care Foundation study that showed low PHR adoption by people with low socioeconomic status, but high usage by those who do adopt.
  • Age 60 appears to be dividing line—over 60 they tend not to use it. This is different from other data I’ve seen, which shows 70 or 75 as a clearer dividing line
  • 1/3 use once/week or more; 1/3 use PHR at least once a month; 1/3 rarely use it
  • MDs report enhanced dialog between patients and providers. Communication is more frequent, complete, and accurate
  • They’re claiming reduced HA1C, BP, cholesterol, ER visits, and hospital readmissions, but didn’t provide any specifics (to be published, but not yet)

Friday, September 17, 2010

Data Visualization, Information Overload, and Compression

In his TED Presentation on data visualization, David McCandless touches on information overload (starting ~16:38), suggesting that data visualization is one tool in our battle with information overload--that good data visualizations enable us to take in data through our eyes and process it in our brains much faster than similar amounts of data communicated through text and numbers.

This reminded me of Mark Hurst's Bit Literacy work:
Bits are heavy. Though they have no physical weight, bits--the electronic data that flows in and out of our e-mail inboxes, cell phones, Web browsers, and so on--place a weight on anyone who uses them. A laptop computer weighs the same few pounds whether it holds one e-mail or a thousand, but to the person who has to deal with all those e-mails, there is a big difference. Appearing in large numbers as they often do, bits weight people down, mentally and emotionally, with incessant calls for attention and engagement....

The problem can be solved by learning bit literacy, a new set of skills for managing bits. Those who attain these skills will surmount the obstacles of overload and rise to the top of their professions, even as they enjoy a life with less stress, greater health, and more time for family and friends. Bit literacy makes people more effective today, even as it equips them for the future.
Mark points out that you can read every day about the information overload problem, but it's very difficult to find practical help dealing with information overload. So his book, Bit Literacy, provides elegant, practical techniques for just that, most of which involve filtering, prioritizing, and organizing incoming data.

I see an intriguing connection between data visualization and bit literacy--an underlying suggestion of a powerful technique that I'll call "compression." Think of it this way:
When a program like WinZip or iTunes compresses a file, it creates a new file that contains most or all of the source information, but using fewer bits to represent that information.

And data visualization does the same thing. A good data visualization takes a large amount of data, either qualitative or quantitative, and displays it in form that conveys most or all of the source information, but using fewer bits to represent that information. This suggests the notion of "compression" as one technique for dealing with information overload.
A few compression examples come to mind.

In the last few years, management "dashboards" have started proliferating. These dashboards essentially take a large amount of information about how a product or company is performing, and compress it into one or two pages of charts, key performance indicators, and short explanatory text. This compressed version of the information enables a manager to quickly take in a tremendous number of bits very rapidly.

Design personas fulfill a similar function. We start with mountains of data from many sources to understand our customers and their needs, and we compress that data into a small number of composite characters called personas. Then we use those personas to communicate with the project team and stakeholders. Essentially, we create compressed versions of the data.

Both of these are examples of "lossy" compression. In the world of compression, "lossless" compression means the compressed file contains all of the information from the original--it's just stored more efficiently. When you download a software application, that software is typically stored in a lossless format, so that when you decompress it, you get all the information of the original. Contrast this with "lossy" compression, in which the compressed file is both smaller, and takes up less space, than the original. This is what you get with an mp3 audio file--you can still enjoy the song, but some of the audio fidelity has been removed so you can fit more songs on your iPod. The trick with lossy compression is to systematically determine a) how much fidelity is required, and b) which data can be removed while still retaining the key information.

Back in our information overload space, this becomes the key question--how can we systematically reduce the bits coming at us so that we can send and receive the essence of a large data set while retaining the key information we need to make informed decisions.

One more example highlights the potential power, and the risk, of using data visualization to combat information overload:

A stock ticker widget essentially compresses all of the data about stock trading into a handful of numbers. After millions of trades today, the Dow Jones was up 1.2%, ending at 10,603.54. This is an attempt to compress not only the stock market, but the economy as a whole. If the Dow is at 10,603.54, the economy is probably better than it was last year, but still struggling.

So the stock ticker saves me the trouble of having to look at all of the data about today's trading. This is good. On the other hand, when there's a TV screen in my elevator barraging me with data about how the Dow, NASDAQ, and S&P 500 are changing from one minute to the next, that's way more information than I need or want. Some further compression would help. As in software compression, it's not only a question of which data to keep and which to remove--it's primarily a question of how small I need the compressed version to be. In the case of a typical consumer, we could add information and compress it even more by presenting a weekly updated graph of performance over the past 10 years.

So I'm having fun playing around with this metaphor, and I have three main questions:

1) Who else has written about compression and/or data visualization as a means to combat information overload?
2) What are some more examples of compression being used effectively to combat information overload?
3) How might we apply this concept in fresh ways to make ourselves more productive and happier each day?

Wednesday, August 11, 2010

eHealth Disparities - strategies continued

A few more thoughts on potential strategies based on meaningful access...

For those who do not currently have meaningful access, but who could get meaningful access as a result of our efforts, we might think of two complimentary paths:

  1. Bring the people to the technology
  2. Bring the technology to the people
In the first case, we're changing the people. In the second case, we're changing the technology.

By "changing the people," I simply mean finding ways to help these folks take advantage of tools others already have. For example:
  • Public access computers in libraries, medical centers, etc.
  • Subsidized access (e.g., some health plans give away cell phones with unlimited minutes for interactions with the health plan)
  • Training on how to purchase, use, maintain, and troubleshoot
In the second case, "bring the technology to the people," we're changing the technology, content, and functionality to make it more accessible, appropriate, and useful to people. For example,
  • Change our push messages from phone and email to SMS
  • Optimize existing web sites for access on pocketable devices
  • Convert key Web interactions to work on IVR (touch-tone telephone trees)
For folks who don't have meaningful access and who won't have meaningful access regardless of what we do, when I blogged a couple of days ago I left off what could be a key strategy:
  • Use higher end technologies with other people so as to free up more traditional resources to attend to the needs of those who don't use those technologies. Here's a way to think about it: If we can use the web to save phone calls to a call center, that should free up call center resources. We would then need to deploy those call center resources to better serve the needs of the people who don't use the web.
I'm liking this basic approach of organizing our strategies based on meaningful access. But I also have a suspicion that we might do better to simply look at age and socioeconomic status (income & education). There's a ton of data out there, and the trip remains finding ways to simplify our approach while respecting the integrity of all that data.

Monday, August 9, 2010

eHealth Disparities Segmentation by Meaningful Access

Many of the same populations that suffer from health disparities also have lower Internet usage. How can we use the Web and mobile technologies to close the gap between the haves and have-nots, rather than increasing the gap?

As always, we need to start by understanding the people involved.

There are many ways to describe the people likely to get the short end of the stick in terms of health, healthcare, and technology. The most obvious are:

  • Demographics (e.g., ethnicity, age, language, socioeconomic status)
  • Psychographics (e.g., those deeply engaged in their health vs. those who don’t pay much attention to their health, or those who love the latest gadget vs. those who fear computers)
  • Access to Technology (e.g., those with desktop broadband vs. those with dial-up, vs. those with smart phones, vs. those with cell phones & SMS, vs. those with none of these)

The problem I keep bumping into is that these factors overlap in very complex ways, and all simple approaches to segmentation seem to oversimplify way too much. For example, Hispanics are more likely to have adverse health outcomes than whites, and they’re also less likely to have broadband, but they’re more likely to access the Internet on their phones. Does this mean we can use smartphones to decrease health disparities for Hispanics? Not necessarily—I'd guess that the Hispanics suffering most from health disparities are those least likely to have smartphones.

Four years ago, in the report Expanding the Reach and Impact of Consumer eHealth Tools, Cynthia Bauer and colleagues at the Dept. of Health and Human Services did an impress job of researching, analyzing, and organizing the field of eHealth Disparities. One of their main conclusions was that we needed more data at the subpopulation level. That gap in our understanding has closed a little in the last four years, but we're still struggling to understand the individuals most at risk of being caught between health disparities and digital disparities.

That said, I think we're close to having a practical starting point.

As we think about strategies to address eHealth Disparities, we might find it helpful to start segmenting in terms of meaningful access to technology. “Meaningful Access” refers to the need to have more than just a computer. Meaningful access requires:

  • hardware
  • Internet connection
  • skills to use them
  • ongoing technical support
  • relevant useful content and functionality

If we take the people most vulnerable to health disparities and subsegment them by meaningful access, then some high-level strategies start to emerge:

The “haves”

Those who already have meaningful access, or those who will gain meaningful access in the next few years with or without our efforts.


Promote existing content and functionality to them

Enhance current content and functionality to be more useful to them

Create new content and functionality for them

The “could haves”

Those who don’t have meaningful access, but who could gain meaningful access as a result of our efforts.


Use the same strategies as for the “haves” above, and also…

Support public access points (libraries, medical centers, shopping malls, etc.)

Support simple and inexpensive access on devices they already own, e.g., SMS texting, including paying the per-message fee

Support public policies and funding that increase access for the underserved (e.g., community-wide wi-fi, extend universal access programs to cover not just phone but also Internet)

The “won’t haves”

Those who don’t have meaningful access, and who still won’t have meaningful access 3 years from now regardless of our efforts.


Support “infomediaries” such as family members who use the Web and mobile devices on behalf of those who don’t

Maintain and enhance non-technology-based services

This might be a starting point. The next step would be to gather more information about each of these groups to understand whether these groups are homogeneous enough to have similar needs that can be addressed with similar efforts.

Wednesday, July 14, 2010

Mobile Health - the 2 big deals

I've been doing online consumer health for over 15 years, most of it with Kaiser Permanente. As I think back on some of the key capabilities that were originally visions on the far horizon and are now simply part of the landscape around us, I remember when each of these was "the next big thing."
  • health information previously available only to professionals, made widely available to consumers
  • health risk assessments with personalized feedback
  • online appointment requests
  • online prescription refills
  • online appointments booked in real time
  • select a physician online
  • apply online for coverage
  • email my doctor
  • secure messaging with my doctor
  • view my medical record
Each of these is now everyday reality to millions of Kaiser members. We've reached these horizons and moved on to the next. So what's next? When someone asks me, "What's the next big thing," I usually end up talking about two areas:
  1. A better user experience
  2. Broader reach
Despite lots of powerful and valuable possibilities for new functionality, from personalization to portable medical records to home monitoring, I think the biggest value to individuals and society will come from improving the user experience of the current functionality, and making that experience available to a broader audience.

1. Better user experience
We need to take all the capabilities we've already implemented, and make them...
  • easier to use
  • more integrated
  • better adapted to real-life scenarios and tasks of our users
2. Broader reach
Over 3 million Kaiser members use the powerful tools we've provided. That's not nearly enough. In addition to increasing the number of web-using Kaiser members who use this stuff, we need to expand these tools to...
  • people who are traditionally underserved by the healthcare system
  • people who don't have easy access to PCs with broadband connections
  • people whose physicians aren't currently part of an integrated group practice
The Mobile Factor
Cell phones won't take us all the way to these horizons. But they can certainly help us get there. In terms of user experience, mobile devices can make simple transactions ridiculously easy, and they can fill in the gaps between in-person, telephone, and desktop web interactions. If we do it right, mobile interactions will become a lynch pin of ubiquitous, integrated, cross-channel experiences.

Not only can mobile devices support much better experiences, it's getting clearer all the time that they can help us extend these services to people who are traditionally left behind by the latest technology. If we do it wrong, our mobile efforts will just exacerbate the already shameful chasm between the haves and have-nots. But if we do it right, and I think we can, we can use mobile technologies as a powerful tool in shrinking that gap.