Fortune 500 companies are big enough, and have enough resources, to assemble and run their own internal analytics teams. In today’s environment, it is becoming impossible for a large corporation to succeed without employing analytics.
The situation is completely different if we make a step down to small and medium business (SMBs), which are typically corporations with less than 500 employees and revenue in hundreds of millions of dollars. Most SMBs do not have enough resources to deploy an internal analytics team. But lack of resources is definitely not the prohibitive argument for why they don’t use analytics. The conventional wisdom of ‘we have been successful for many years, so why do we need analytics now?’ is just now being challenged. The desire for growth is spawning the adoption of analytics. With analytics, SMBs can expand the market share, intelligently manage operations, drive down costs, and gain a new competitive advantage. In layman’s words, analytics can increase the bottom line for a few million dollars.
As mentioned, a SMB typically lacks the size to have an internal analytics team and thus they are ripe for using external software solutions. There is a big opportunity for independent software vendors (ISVs) offering business analytics solutions to target SMBs. If an SMB was established more than five years ago, they most likely only use business intelligence for basic reporting, or Google Analytics if they have an e-commerce site.
The situation is different for most recent start-ups and SMBs, since many of them built their business models around business analytics and from the very beginning it became a key component of their business strategy – this clearly includes all the start-ups in the software space and those using other technologies. In addition, this is also evident in many companies, for example, using social networking data or data from sensors such as telemetry and smart meter data.
ISVs offering analytics-based solutions have a tremendous opportunity to target SMBs in pretty much every vertical: from transportation to healthcare, retail, CPG, manufacturing, etc. SMBs are overshadowed by their big brothers since typical analytics projects cannot drive hundreds of millions of benefits as is the case for big corporations. However, despite a lower per project ROI, the total market should not be overlooked – the large number of SMBs in the U.S. (there are more than 25 million SMBs in the U.S.) creates a huge market opportunity. While percentage-wise, the number of U.S. SMBs is not as high as in many European countries, they still represent a major chunk of the U.S. economy. Since every corporation has sales and marketing, immediate low-hanging fruit can be found in the areas of marketing and customer intelligence analytics.
It is well known that in a successful data-driven corporation, everything starts at the management level. The management has to embrace analytics and then trickle it down throughout the entire organization. SMBs are no exception in this regard. The big advantage of SMBs is the fact that their organizational structure is more shallow and narrower in size. For this reason they are usually quicker to buy into analytics. Let us make no mistake; the buy-in from management in SMBs should not be taken for granted.
To summarize, analytics success stories in SMBs are not sexy – they will not appear in the Bloomberg Businessweek and will not lead to feature films like Moneyball, but nevertheless, they can make a dent in the economy. The opportunity for ISVs to target SMBs is definitely big. One does not have to look further than Intuit to get inspired by focusing on SMBs as a major market segment. Despite traditionally being focused on ‘accounting,’ Intuit now embeds analytics in their solutions such as the online personal financing software Mint and conducts analyses across their customer segments.
Turns out that brainstorming--that go-to approach to generating new ideas since the 1940s--isn’t the golden ticket to innovation after all. Both Jonah Lehrer, in a recent article in The New Yorker, and Susan Cain, in her new book Quiet, have asserted as much. Science shows that brainstorms can activate a neurological fear of rejection and that groups are not necessarily more creative than individuals. Brainstorming can actually be detrimental to good ideas.
But the idea behind brainstorming is right. To innovate, we need environments that support imaginative thinking, where we can go through many crazy, tangential, and even bad ideas to come up with good ones. We need to work both collaboratively and individually. We also need a healthy amount of heated discussion, even arguing. We need places where someone can throw out a thought, have it critiqued, and not feel so judged that they become defensive and shut down. Yet this creative process is not necessarily supported by the traditional tenets of brainstorming: group collaboration, all ideas held equal, nothing judged.
So if not from brainstorming, where do good ideas come from?
At Continuum, we use deliberative discourse--or what we fondly call “Argue. Discuss. Argue. Discuss.” Deliberative discourse was originally articulated in Aristotle’s Rhetoric. It refers to participative and collaborative (but not critique-free) communication. Multiple positions and views are expressed with a shared understanding that everyone is focused on a common goal. There is no hierarchy. It’s not debate because there are no opposing sides trying to “win.” Rather, it’s about working together to solve a problem and create new ideas.
So we argue. And discuss. And argue. A lot. But our process is far from freeform yelling. Here are five key rules of engagement that we’ve found to yield fruitful sessions and ultimately lead to meaningful ideas.
Breaking down hierarchy is critical for deliberative discourse. It’s essential to creating a space where everyone can truly contribute. My first week at Continuum, I joined a three-person team with one senior and one principal strategist. A recent graduate, I was one of the youngest members of the company. During our first session, the principal looked me in the eye and said, “You should know that you’re not doing your job if you don’t disagree with me at least once a day.” He gave me permission to voice my opinion openly, regardless of my seniority. This breakdown of hierarchy creates a space where ideas can be invented-- and challenged--without fear.
It’s widely evangelized that successful brainstorms rely on acceptance of all ideas and judgment of none. Many refer to the cardinal rule of improv saying “Yes, AND”--for building on others’ ideas. As a former actor, I’m a major proponent of “Yes AND.”
But I’m also a fan of “no, BECAUSE.” No is a critical part of our process, but if you’re going to say no, you better be able to say why. Backing up an argument is integral in any deliberative discourse. And that “because” should be grounded in real people other than ourselves.
We conduct ethnographic research to inform our intuition, so we can understand people’s needs, problems, and values. We go out dancing with a group of women in a small Chinese village; we work in a fry shack in the deep South; we sit in living rooms and listen to caregivers discuss looking after a parent with Alzheimer’s. This research informs our intuitive “guts”--giving us both inspiration for ideas and rationale to defend or critique them.
During ideation, we constantly refer back to people, asking one another if our ideas are solving a real need that people expressed or that we witnessed. This keeps us accountable to something other than our own opinions, and it means we can push back on colleagues’ ideas without getting personal.
We’ve all heard of T-shaped people and of multidisciplinary teams. This model works for us because deliberative discourse requires a multiplicity of perspectives to shape ideas. We curate teams to create diversity: Walk into a project room and you may find an artist-turned-strategist, a biologist-turned-product designer, and an English professor-turned-innovation guru hashing it out together. True to form, my background is in theater and anthropology.
On a recent project, I realized the best way to tackle a particular problem was to apply a text analysis tool that actors use with new scripts. I taught this framework to the team, and we used it to generate ideas. Another time, a team member with a background in Wall Street banking wrote an equation on the whiteboard. It was exactly the framework we needed to jumpstart our next session.
When we enter deliberative discourse, arguing and discussing and arguing and discussing, we each bring different ways of looking at the world and solving problems to the table.
Deliberative discourse is not just arguing for argument’s sake. Argument is productive for us because everyone knows that we’re working toward a shared goal. We develop a statement of purpose at the outset of each project and post it on the door of our project room. Every day when we walk into the room, we’re entering into a liminal play space--call it a playing field. The statement of purpose establishes the rules: It reminds us that we are working together to move the ball down the field. As much as we may argue and disagree, anything that happens in the room counts toward our shared goal. This enables us to argue and discuss without hurting one another.
We work on projects ranging from global banking for the poor to the future of pizza and life-saving medical devices. Our work requires intensity, thoughtfulness, and rigor. But no matter the nature of the project, we keep it fun. It’s rare for an hour to pass without laughter erupting from a project room. Deliberative discourse is a form of play, and for play to yield great ideas, we have to take it seriously.
But we don’t brainstorm. We deliberate.
[Images: Kazarlenya, aboikis, and Jakgree via Shutterstock]
This is truly awesome. Only years away from building a meta brian.
Mimicking the Brain -- In Silicon: New Computer Chip Models How Neurons Communicate With Each Other at Synapses
ScienceDaily (Nov. 15, 2011) — For decades, scientists have dreamed of building computer systems that could replicate the human brain's talent for learning new tasks.
MIT researchers have now taken a major step toward that goal by designing a computer chip that mimics how the brain's neurons adapt in response to new information. This phenomenon, known as plasticity, is believed to underlie many brain functions, including learning and memory.
With about 400 transistors, the silicon chip can simulate the activity of a single brain synapse -- a connection between two neurons that allows information to flow from one to the other. The researchers anticipate this chip will help neuroscientists learn much more about how the brain works, and could also be used in neural prosthetic devices such as artificial retinas, says Chi-Sang Poon, a principal research scientist in the Harvard-MIT Division of Health Sciences and Technology.
Poon is the senior author of a paper describing the chip in the Proceedings of the National Academy of Sciences the week of Nov. 14. Guy Rachmuth, a former postdoc in Poon's lab, is lead author of the paper. Other authors are Mark Bear, the Picower Professor of Neuroscience at MIT, and Harel Shouval of the University of Texas Medical School. Modeling synapses
There are about 100 billion neurons in the brain, each of which forms synapses with many other neurons. A synapse is the gap between two neurons (known as the presynaptic and postsynaptic neurons). The presynaptic neuron releases neurotransmitters, such as glutamate and GABA, which bind to receptors on the postsynaptic cell membrane, activating ion channels. Opening and closing those channels changes the cell's electrical potential. If the potential changes dramatically enough, the cell fires an electrical impulse called an action potential.
All of this synaptic activity depends on the ion channels, which control the flow of charged atoms such as sodium, potassium and calcium. Those channels are also key to two processes known as long-term potentiation (LTP) and long-term depression (LTD), which strengthen and weaken synapses, respectively.
The MIT researchers designed their computer chip so that the transistors could mimic the activity of different ion channels. While most chips operate in a binary, on/off mode, current flows through the transistors on the new brain chip in analog, not digital, fashion. A gradient of electrical potential drives current to flow through the transistors just as ions flow through ion channels in a cell.
"We can tweak the parameters of the circuit to match specific ion channels," Poon says. "We now have a way to capture each and every ionic process that's going on in a neuron."
Previously, researchers had built circuits that could simulate the firing of an action potential, but not all of the circumstances that produce the potentials. "If you really want to mimic brain function realistically, you have to do more than just spiking. You have to capture the intracellular processes that are ion channel-based," Poon says.
The new chip represents a "significant advance in the efforts to incorporate what we know about the biology of neurons and synaptic plasticity onto CMOS [complementary metal-oxide-semiconductor] chips," says Dean Buonomano, a professor of neurobiology at the University of California at Los Angeles, adding that "the level of biological realism is impressive.
The MIT researchers plan to use their chip to build systems to model specific neural functions, such as the visual processing system. Such systems could be much faster than digital computers. Even on high-capacity computer systems, it takes hours or days to simulate a simple brain circuit. With the analog chip system, the simulation is even faster than the biological system itself.
Another potential application is building chips that can interface with biological systems. This could be useful in enabling communication between neural prosthetic devices such as artificial retinas and the brain. Further down the road, these chips could also become building blocks for artificial intelligence devices, Poon says.
Debate resolved
The MIT researchers have already used their chip to propose a resolution to a longstanding debate over how LTD occurs.
One theory holds that LTD and LTP depend on the frequency of action potentials stimulated in the postsynaptic cell, while a more recent theory suggests that they depend on the timing of the action potentials' arrival at the synapse.
Both require the involvement of ion channels known as NMDA receptors, which detect postsynaptic activation. Recently, it has been theorized that both models could be unified if there were a second type of receptor involved in detecting that activity. One candidate for that second receptor is the endo-cannabinoid receptor.
Endo-cannabinoids, similar in structure to marijuana, are produced in the brain and are involved in many functions, including appetite, pain sensation and memory. Some neuroscientists had theorized that endo-cannabinoids produced in the postsynaptic cell are released into the synapse, where they activate presynaptic endo-cannabinoid receptors. If NMDA receptors are active at the same time, LTD occurs.
When the researchers included on their chip transistors that model endo-cannabinoid receptors, they were able to accurately simulate both LTD and LTP. Although previous experiments supported this theory, until now, "nobody had put all this together and demonstrated computationally that indeed this works, and this is how it works," Poon says.
Fortune 500 companies are big enough, and have enough resources, to assemble and run their own internal analytics teams. In today’s environment, it is becoming impossible for a large corporation to succeed without employing analytics.
