Apple claims to be the first to add EKG to a smart watch:
They're not really first, but it's still cool. I'm in favor of pretty much any biometric monitoring that's not invasive, and I can definitely see the use of an EKG.
While adding another type of sensor gives me more data about myself, what I'm really interested in is finding ways to get value out of the data I'm already collecting!
I love my wearable when I'm exercising. But to be honest, I'm doing very little with the data. I view my heart rate myself while running, occasionally review it later, and once in a while I'll show it to friends because I think it's cool (though I don't think they care much about my heart rate).
What we need are ways to share it that are easy and safe. My top priority would be sharing with my health network -- personal trainer, dietitian, physician. (OK, I don't really have a trainer or dietitian just yet, but you get the point.)
It also needs be easier to use data from wearable in analysis tools. By mixing it with other data and visualizing it, I can spot trends and correlations, and maybe even set up triggers and alerts.
I'd love to get some feedback:
Data visualization lets experts “look” for trends and correlations using charts, graphs and maps that combine multiple datasets containing huge amounts of data. Data visualization is already a critical tool in the decision making processes for today’s successful enterprises.
“It is imperative for business leaders to realize and accept that the human brain may not be as compatible with data piles as a computer, but it is indeed immensely capable of interpreting graphics and patterns. Also, visuals are far more easy to interpret data forms than mundane text.”
Today, data visualization is mostly done using desktop PCs and flat screen monitors. But there are very practical limitations to this essentially two-dimensional format. (Yes, you can visually simulate a third dimension moderately well with perspective and shading, and even animate to add time or another dimension. But the amount of data you can correlate visually using a screen is still quite limiting.)
“Today’s Big Data projects often involve amalgamating hundreds of data sources, structured and unstructured, and it’s likely that 2D images, or even 3D ones presented on a flat screen, will no longer cut the mustard.”
With virtual reality, users can visually interpret considerably more data:
“By presenting data inside a 3D canvas which wraps around the user, far more than the traditional three dimensions become available. As well as placement on X, Y or Z co-ordinates, data points can be distinguished by size, colour, transparency, as well as direction and velocity of movement.”
And considering the trend toward big data, where vast seas of new data sources are pouring in from wearables and connected devices, there is clearly a demand for better data visualization tools.
We have a lot of data now, and we’re going to have more, so making it easy to spot these “differences” is of critical importance.
“The major advantages of VR is that it can be used to make perceiving differences in data easier, less dense, and more intuitive.”
VR and AR are not just about what you see -- they are also about how you interact with data. That old keyboard and mouse approach has serious limitations! VR’s human input devices let you use your entire body in highly intuitive ways to control the software. Users will be able to use their hands to choose data and adjust settings, or turn their head or body to change perspective. Once mastered, this interactive capability will even further enhance our ability to understand data trends and correlations.
Given these awesome new capabilities, what kinds of problems can visual data analysis help solve?
“One of the most promising areas where big data can be applied to make a change is healthcare. Healthcare analytics have the potential to reduce costs of treatment, predict outbreaks of epidemics, avoid preventable diseases and improve the quality of life in general.”
That article goes on to describe several cases where big data analytics are currently being used in health care, including: staffing (who, when and where), treatment decisions, real time alerts, predictive analytics and strategic planning. Doctors, nurses and administrators who need to make well-informed decisions can use VR-based data visualization to spot correlations and trends using the ever increasing number of data sets and data points becoming available in today’s (and tomorrow’s) big data landscape.
We are thrilled to announce we’ve produced our workshop product for our first client. It was an exciting and valuable experience for ourselves (and hopefully our client), and I’d like to describe a couple of things we learned.
First a little background. Novana offers an intense four-day workshop designed for ground-floor startups or enterprise workgroups tasked with bringing new product or services to market. The workshop covers most of the basics needed to get a startup off the ground, and can be customized per client to meet specific needs. Our client in this case was an early-stage startups in “stealth” mode. (We should be able to reveal more about them in the upcoming months.)
We held our event at a beautiful setting in Berkeley, California. Each morning involved four hours of full-team meetings, followed by afternoon sessions for individual or collaboration in smaller groups.
Here’s what we learned.
Effective problem solving requires teamsmanship
New products or services are only needed when there is a problem to solve. We know from both research and experience that problem solving is most effective when pursued by a highly effective team. Novana enables teamsmanship through our own particular combination of concepts from Lean Product Management, with a trimmed-down version of Agile project management, all supported by minimalist technology. We call it The 'TEAM WAY', and last week was the first time we employed it with paying customers!
We built our ad hoc team by combining the client’s existing personnel with three people from Novana. We brought project management, product management, UX design and knowledge related to a wide array of emerging technologies. The client provided everything else: a deep understanding of the problem, some rough solution concepts, knowledge of the industry, the market, and their potential competition and customers.
It was pleasantly surprising how quickly the two groups integrated and started to gain value from the larger collaborative effort. By loosely controlling the conversation (i.e. letting ideas run their course), we were able to explore a wide range of ideas in a short amount of time. Most of the ideas came from the client’s team members -- not surprising, but it does beg the question why putting them in this new setting makes it easier to generate and capture new ideas. (I’ll discuss this in later articles, but for now, please just accept that it does!)
One thing that didn’t work perfectly was our system of capturing ideas. We had decided to go analog (sticky notes) to capture ideas on a wide range of topics. While this worked OK, it caused more problems than it solved. For one thing, it was not as easy to reorganize them as we had thought. It was also difficult to edit them after initially writing them - we found ourselves re-writing them a lot, or combining several into one. All of this might have been made easier with our digital tool.
Once we switched to our project management software, things went a lot smoother. For one thing, all team members could quickly add ideas to the “soup” without leaving the conversation.
And our client immediately understood the value of our project management tool and was able to utilize it without any training due to its simple interface. So that pretty much eliminated the main reason we liked the post-its.
And once we showed the ability to create dashboards for specific people or subject, everyone on the team agreed the digital tool was the way to go.
Goal setting and deliverables
We entered this workshop believing we needed to define the goal of each segment (usually about two hours), and to keep all team members focused on that goal for short sprints. For the most part, this proved highly effective.
This uncovered a couple of issues:
First, what happens when you can’t reach the goal in one or more segments? What we found was that, even when we didn’t accomplish a given goal in completely, defining that goal made it easier to build consensus on next steps, and to assign responsibility for future actions. We left with high confidence that these steps can be easily tracked in our project management software.
Second, when you do reach a goal, what indication do you have to show the client (at a later date)? It would be helpful to have a deliverable, clearly defined in advance, for each segment. While this might not seem reasonable for some segments (such as exploring the problem/solution statements), it may be worthwhile to “invent” a deliverable just to standardize the experience.
Learn-while-doing is awesome!
Do you love sitting through training courses? I don’t. It’s boring and largely ineffective.
Experiential learning offers a much more effective (and interesting) way to learn. (See "8 Reasons Why Experiential Learning Is The Future Of Learning", October 24, 2014, Kydon Holdings, eLearning Industry.)
We expect our clients to be relatively new to the many of the skills, practices and methods we use in our workshop. Through this real-world collaborative project, we were able to give our client a practical understanding of what’s involved with new product development. This included concepts like lean product management and agile project management, as well as hands-on use of software tools for project management and collaborative document creation.
There is no question that our alpha test of the learn-while-doing concept was tremendously successful. Our clients came with minimal prior knowledge, and without even realizing they were doing it, they left with a collection of new skills, and practical experience using those skills, that will serve them well in any of their future product development efforts.
Ideation is (almost) everything.
Look, I’m not in love with the word “ideation”. But it does effectively describe what we feel is the highest value we can bring to our customers. Think about how much time and effort goes into engineering, marketing and supporting a new product or service. How much time should we spend on just thinking about, discussing, brainstorming, and vetting ideas?
Ideation is not limited to the early stage of product management. In fact, if done properly, ideation can and should be applied to pretty much every aspect of the strategic planning phase.
Here’s a short list of the items we found valuable to explore during in our workshop:
That last broad, mission-critical topic of validating our assumptions is certainly obvious to some -- but it was not to our client! We feel our client gained the most value out of practicing the art of ideation to explore simple ways to validate questions like: does the proposed solution really solve the problem; how much would customers be willing to pay for the solution; can the solution be built and supported affordably; and whether our proposed sales/distribution channel partners gain enough value to justify their effort? More than simply trying to answer each of these questions, we were able help our client understand the importance of identifying where assumptions were made, and build a repeatable process of gathering evidence to defend these assumptions. This is a critical step on the route to getting funding or buy-in from executive management.
All in all it was a tremendous experience. We learned a lot, proved a few assumptions right, and significantly modified a few others. Given that our goal is to offer this workshop to all our new customers, we are excited about what we’ve learned and the prospects of making the experience even better moving forward!