Category Archives: business

business, entrepreneurship, management and leadership

20 solid business lessons

 

 

20 Business Lessons You Don’t Want To Learn The Hard Way

lessons

(Photo credit: Mashable)

A few months ago, we posed this question to ShortStack‘s Facebookfans: “What is one business lesson you learned the hard way?” It began as a simple question to garner engagement, but it led to a long list of business owners’ reminiscences that included some great advice.

Of course every business owner will have his or her own trials, but here are 20 reminders our community shared that just might save you a headache:

  1. You can’t do everything on your own. Building a team is essential because there are only so many hours one person can devote to a business. Exactly when you reach that limit depends on your other obligations. If you’re a young single person, you might be able to do everything for a year or two. But if you have a family, your dedication will eventually hurt those relationships. Build a team that can carry on when you’re not around.
  2. You may think your product is perfect, but your clients won’t. Listen to user feedback: Your opinion may not be the best one. The key takeaway here is “release your product early and release it often.” You won’t know if you have a great product until it’s in the field and users are beating it up. It’s like some of the contestants on American Idol. They think they’re talented, and their friends and family think so, too, but when they get on a bigger stage, their flaws become obvious.
  3. Do one thing really well. Entrepreneurs try to be everything to everyone, but it’s hard to be the store that sells bait and baby toys and vintage Beatles albums. Specialize, and you can charge for what you do provide. That said, if there is a skill or service that would make your core product better, provide it.
  4. Get paid before you hand over a project to a client. This is especially important if you provide a service. Once you turn over that contract or website or design project, you won’t have much bargaining power. When I was a graphic designer, I watermarked all my projects and hosted websites on a private domain until the bill was paid.
  5. Undercharging is not sustainable. You think, “I don’t need to charge $150 an hour, I can charge $70 and make way more than I was making as an employee!” But you might find out a short time later that your “great” rate is unsustainable. By the time you pay taxes, employees, business licenses, insurance, etc., that $150/hour is looking more realistic. Compete on quality, expertise and your niche focus (see #3) instead of price. When competing on price alone, the clients who are price-shopping will always leave for the person or company that undercuts you.
  6. Patience and flexibility help you survive the lean times. ShortStack started out as a side project at my web and graphic design studio. We weren’t a software development studio, but when a client asked us for a software product, we didn’t say no. We were patient, scaled slowly — partly out of necessity — and it allowed me to build with company without debt.
  7. Build for your actual market. All of my software-building experience so far has been in answer to a demand. It is purely opportunistic. If you’re an app developer and you think “Wow, I think xx industry could use xx,” you might be disappointed. Put another way: I would never start a restaurant without having worked in one…for a long time!
  8. Never enter a partnership without a buy/sell agreement. No matter how well you think you know someone, you just don’t know when he or she will want to retire or do something else. Even if it’s on amicable terms, know how you can get rid of one another when it’s time for one of you to move on.
  9. Be grateful. Appreciate loyal customers who show you there is a demand for what you do. There is no dollar amount you can put on brand advocates. Good will translates to loyal customers.
  10. Look after those who look after you. We offer referral commissions at ShortStack, but it’s very much under the radar. We want people to recommend the product because they like it, not because they’ll say anything for a dollar. If we notice someone said nice things about us publicly, we might send them a t-shirt as a thank you. If they do it again and again, we might say, “Hey, you should become a referrer and earn a percentage of the business you send our way.”
  11. It’s not a sale until it’s paid for. This sounds obvious, but I’ve known small business owners who get very excited about orders and/or meetings with prospective clients. But until the money for those products or services is in the bank, it doesn’t count.
  12. You’ll make more money being “wrong” than proving you are right. Rather than fight with an unhappy customer and say, “You’re using it incorrectly,” or “You don’t know enough CSS to use our product,” we just refund their money. In the long run, these people consume so much of the support team’s time and energy that it’s more cost effective this way. They’re not our ideal client, and that’s OK.
  13. People don’t leave companies — they leave management. This lesson goes for both employees and customers. A manager will lose staff if the employees think they’re not being listened to or valued. Customers will stop using your products or services if they are dissatisfied with them. The quality and reliability of your products and services is a reflection of management.
  14. The way you present your business should be a reflection of your audience. If you have serious clients, be serious. If you have hip, fun-loving clients, have a sense of humor. You have to find your niche and build your content to suit them. For example, Constant Contact and MailChimp do essentially the same thing, but their marketing content reflects very different client bases.
  15. Agree on scope in advance. Have a clear contract before work begins. Once a project goes beyond the documented plan, charge for it. If you agreed to build a website with 10 pages, but soon the site is 20 pages, the client should pay you for them. If your contract makes that clear at the outset, it is easier to control scope creep.
  16. If your company sells a variety of products, make sure you know how to use/operate every single one of them. It might sound like a tall order — depending on how many products your company sells — but learning to use what your company sells will help you look at things with fresh eyes.
  17. When you think you’ve tested your product enough, test it some more. Never release a product until it has been tested and tested and tested by people who don’t work for you.
  18. Understand how social media networks work. When Twitter was first available for businesses, I’d see people use it like an ad in a newspaper. If you go on a channel and use it the wrong way, it could do more long-term harm than good.
  19. Save up. You can operate at a loss for a number of years but you can only run out of cash once. Have a rainy day fund that has at least two or three months’ operating costs in it. And have a line of credit available, even if you don’t plan to use it. Having a CPA look at your books once a quarter is also a must.
  20. Always let the CFO pay for drinks. Cheers!

Have you learned any business lessons the hard way? Let me know in the comments section below.

business, data saving lives, healthcare, management and leadership, policy, rapid learning health systems

Toby Cosgrove: Leaning in to healthcare changes….

 

  • frames consumer need for selection apps
  • frames payer need for analytics

http://www.linkedin.com/today/post/article/20140107180116-205372152–leaning-in-to-healthcare-changes

“Leaning in” to Healthcare Changes

January 07, 2014  


Healthcare is in the midst of an unstoppable transformation. The pressure to reduce costs, improve quality, and provide a better patient experience is relentless. How will providers respond? Which organizations are best positioned to succeed?

These changes have been a long time coming. Forces favoring consumerism have completely transformed the airline, manufacturing and retail sectors. Now it’s healthcare’s turn. The primary drivers are information technology and high-deductible healthcare plans. Patients didn’t shop around when it was the insurance company’s dollar they were spending. But when you’re paying for routine healthcare, x-rays, and colonoscopies out of your own pocket, you start looking at the price tag.

Information technology is going to be the comparison driver. Consumers can already compare rates for hotels, airlines and appliances with the swipe of a finger. Soon there will be apps showing you which healthcare providers provide which services at what costs. You’ll be able to sort them from lowest to highest cost, and make your choice: Does it matter to you if your angioplasty (a minimally invasive procedure to open blocked arteries) is performed by a highly regarded academic medical center backed by full cardiac surgery capabilities, or if it is performed less expensively at a private cardiology practice, where you would have to be transported elsewhere for life-saving surgery in case of an emergency? I know what I would choose, but you, as a consumer, will have to make your own risk-benefit calculations.

In addition to consumerism, the Center for Medicare and Medicaid Services (CMS) will be exerting its own pressure, paying doctors and hospitals less for their services and demanding more accountability for quality, safety and patient experience. Private insurers, who usually follow the lead of CMS, will also be paying less and demanding more. Toss in all the unknowns that accompany the federal government’s Patient Protection and Affordable Care Act, and you are looking at Force 5 cost headwinds.

There is no escaping the conditions that are forcing this transformation. The providers who succeed will be those who “lean in” to the changes – hospitals and medical centers who embrace cost awareness not as an onerous duty, but as a patient care issue. Because along with lowering costs, we are improving efficiency, reducing variability of outcomes, and accelerating medical innovation. All of this adds up to better patient care, and that’s what we’re here for.

business, nutrition

McKinsey: How big food actually thinks…

 

 

PDF Report: Tough_choices_for_consumer-goods_companies

Source: http://www.mckinsey.com/insights/consumer_and_retail/tough_choices_for_consumer_goods_companies

Tough choices for consumer-goods companies

Increasingly empowered consumers, rising yet volatile input prices, and tricky emerging markets mean global consumer-packaged-goods companies must rethink how they do business. Here’s a guide.

December 2013 | byJim Brennan, Greg Kelly, and Anne Martinez

Over the past half century, the consumer-packaged-goods (CPG) industry has achieved enviable growth in both revenue and shareholder returns. At first blush, continued growth seems a sure thing—after all, the burgeoning economies of emerging-market countries are fueling an unparalleled boom in global consumption. And given that global CPG companies are selling more of their products to more people in more parts of the world, shouldn’t revenue growth—and, with it, healthy returns—be theirs for the taking?

If only success were that simple. A look back at recent decades of developed-market based CPG companies shows that they have consistently managed to grow, but not always profitably. And today, a series of large-scale trends is causing industry upheaval, forcing companies in mature markets to make tough choices about where to play and how to win. Investment in emerging markets isn’t foolproof: growth, although strong, is uneven, with certain markets and categories far outpacing others. Severe resource constraints are causing volatility in commodity costs. Digital technologies are affecting every part of the value chain, and in sometimes unpredictable ways. New—and newly acquisitive—competitors are emerging. And regulatory risk is rampant as government exerts ever-greater influence over the industry.

Given how fundamentally these trends will transform the industry over the next decade, we believe the strategic choices that CPG manufacturers make in the next few years will be more consequential than those they’ve made in the recent past. Every company will respond to the trends differently. Some companies may choose to keep their focus on core franchises with the hope of delivering stable, even if not stellar, earnings; others may opt for more assertive but riskier moves. In this article, we discuss each of the aforementioned trends, the kinds of choices they will require companies to make, and the actions every company should take regardless of its specific strategic choices.

Changes and choices

In recent decades, CPG companies have posted better returns than other sectors. Between 1967 and 2012, the industry’s 7 percent annual growth in total return to shareholders (TRS) outpaced the S&P 500’s 6 percent. But it hasn’t been a smooth and steady road. In our analysis of the CPG industry since 1967, we see four distinct eras, with one in particular—the period from 1985 to 2000—accounting for the bulk of value creation (Exhibit 1). The years 1967 to 1985 marked a golden age of growth, a time when sales of food, beverages, and household and personal products soared. Americans doubled their consumption of soda (from an average of one serving a day to two), for example, and cheese (from half an ounce a day to a full ounce). However, revenue growth came at the expense of margins, which declined by almost 300 basis points.

Exhibit 1

In recent decades, the consumer-packaged-goods industry has seen four distinct value-creation cycles.

Margins shot up—largely thanks to declining input prices—during what we call the era of expansion (1985–2000), allowing CPG companies to finance forays into new global markets. A wave of mergers and acquisitions followed in the years 2000 to 2007, but the success of these deals was mixed; revenue increased but TRS growth dipped. Then, during the Great Recession and the subsequent recovery, the industry grappled with a tough economy and persistently high commodity costs, limiting both revenue growth and value creation.

How CPG companies fare in the current era remains to be seen: will they sacrifice margins for revenue, as they did during the golden age of growth? Will they be able to grow profitably, as they did between 1985 and 2007? But what’s already evident is that the industry is on the cusp of sweeping change, presenting companies with a range of strategic choices. We believe the five most influential changes, and their implications for CPG companies, are as follows.

Granular growth, globally

By 2025, a staggering 4.2 billion people will be part of the consuming class. For the first time ever, the number of people with discretionary income will exceed the number still struggling to meet basic needs—a phenomenon that may well be the biggest opportunity in the history of capitalism.1 Another golden age of growth could be in the making. Consumption growth, however, isn’t even; it’s happening much faster in certain categories and markets. Some emerging-market cities have higher growth potential than entire countries. In Shanghai, for instance, the skin-care category will grow three times as fast in absolute terms as in all of Malaysia, based on 2010–20 compound annual growth rate (CAGR).

This uneven growth presents tremendous potential for companies—whether they are multinationals or local players—to quickly become industry shapers, if they choose to play in the fastest-growing subcategories in the fastest-growing markets. For example, The Coca-Cola Company, recognizing Chinese consumers’ preference for pulpier juices, launched Minute Maid Pulpy—which became the company’s first billion-dollar brand developed for and in an emerging market. Local companies, too, are making winning choices: our research shows that in the fastest-growing CPG categories in China, Brazil, and Mexico, eight of the top fifty companies are headquartered in emerging markets. These local entities—companies like Mexico’s Grupo Bimbo—are venturing outside their home markets and skillfully leveraging their emerging-market know-how, favorable cost positions, and proximity to a rapidly expanding customer base. As a result, their sales growth in emerging markets (19 percent CAGR in the 2009–12 period) far exceeds that of US-based CPG companies (5 percent).

Emerging-market companies’ budding success on the global stage introduces a new element to strategic planning. We believe CPG companies should take a more data-driven approach to understanding how competitors will grow in each market, and how their own strategic positions will change as a result. They will then be able to predict critical inflection points for particular products in particular cities and regions. McKinsey research has found that consumption growth in each product category follows its own distinct variant of the classic S-curve pattern. Companies that invest just as a category enters the “hot zone” will likely generate the most value. Better insights into competitor evolution, and how it will affect the microeconomics of product categories in each country and globally, will become increasingly important.

Not all growth is coming from emerging markets; companies must identify and invest in pockets of growth in developed markets as well, particularly as growth in emerging markets slows. In the United States, for example, the spending power of certain demographic groups, such as baby boomers and Hispanics, is significant and growing. The “value” segment, which flourished during the recession, continues to appeal to a broad swath of consumers. These and other “niche” opportunities in developed markets can hold as much growth potential as entire countries. Colgate-Palmolive, for one, has launched products targeting Hispanics; P&G has introduced new products and brands to compete in lower price tiers.

No matter what investment decisions a company makes, one key to success will be its ability to allocate resources quickly to the businesses that will yield the highest returns.2 In our experience, companies often underestimate both how big a shift they need to make and how big a shift emerging-market players are already making. The growth of Anheuser-Busch InBev—from a national beer player in Brazil to the world’s biggest brewer and a top 5 CPG manufacturer in less than a decade—shows just how quickly the game can now change.

Volatile commodity costs

Profitability in the CPG industry is tightly linked to commodity costs. When CPG companies raise their prices to offset commodity-price hikes, as they did in the era of expansion, they enjoy strong returns. But when they aren’t able to pass on price increases to consumers, as was the case in the early 2000s, margins and TRS suffer.

Until recently, commodity costs have been trending up. Due to global consumption growth, the rising cost of new supply (the real cost of a new oil well, for instance, has doubled in the past decade), and the interconnectedness of resources (biofuels being one illustration), the spike in commodity prices in the past 10 years has undone the decline of the previous 100 years.3

CPG companies must prepare for continuing volatility in commodity costs. The standard deviation of the McKinsey Global Institute (MGI) commodity-price index is more than twice its historical average. And the majority of key CPG inputs are subject to supply risk, either due to concentration in only a few countries (for example, 75 percent of phosphate reserves are in Morocco); absolute shortages, as is the case with water; a lack of substitutes (for potash, for example); or low recycling rates (such as with tin). Furthermore, the prices of soft commodities could increase by 50 to 450 percent, given unpriced environmental externalities such as CO2 emissions and water withdrawals.4

Sidebar

Questions to ask yourself to stay ahead

Every CPG company must undertake a rigorous risk analysis—including an assessment of “tail” risks—for major commodities across its entire supply chain. It should come up with a productivity plan that exceeds the reasonable range of commodity-price increases by at least 200 basis points. It must then make choices about how to mitigate commodity risks. Some CPG manufacturers are vastly reducing or even eliminating parts of their portfolio that rely heavily on constrained commodities. Some are reformulating their product recipes and using substitutes (for example, high-fructose corn syrup for sugar), taking into account weight and manufacturing trade-offs. Others are pursuing procurement excellence through supplier collaboration or even vertical integration. Still others are experimenting with ways to drive a more “circular” economy—for example, through greater use of recycled materials—that yield cost benefits as well as environmental benefits.

And because commodity risk puts strong pressure on margins, companies must continually find margin-enhancing opportunities. Making operations more efficient is one such opportunity. Our analysis shows that when CPG companies undertake large-scale, cross-functional operations-improvement programs rather than one-off projects in isolated business units, they can boost productivity by 300 basis points. Kraft Foods and SC Johnson have recently achieved this kind of productivity gain. Better revenue management is another margin-enhancing opportunity. Some companies are deploying an arsenal of revenue-management and pricing tools: for instance, they’re investing in sophisticated revenue-management processes and IT, hiring revenue-management experts, and making smaller but more frequent changes to pricing and promotions to reduce the risk of competitive followership.5

Transformative technologies

A recent MGI report identifies 12 technologies that could have massive, economically disruptive impact between now and 2025.6 Of the 12, we see three that could potentially transform the CPG sector and underpin a golden age of growth or an era of expansion: the mobile Internet and, in the longer term, the “Internet of Things” and 3-D printing.

MGI projects that by 2025, 50 percent of retail purchases will be made on a mobile device. That estimate could prove low, given that many product categories are quickly migrating from the physical store to online (Exhibit 2). The online market has shown itself to be supply driven: Zappos.com’s offer of free shipping and no-hassle free returns, for instance, lured consumers who previously never considered buying shoes online. The same could happen in grocery, where companies like Peapod and Amazon.com are making bold moves. Peapod’s mobile sales in 2012 were close to $150 million, up 50 percent from 2011. And Amazon, which plans to expand its AmazonFresh business to as many as 20 urban areas in 2014, could shake up grocery retail the same way Wal-Mart Stores did in the 1990s.

Exhibit 2

Digital technology is shaping all markets and categories.

To benefit from the mobile Internet, companies will need to make careful choices about where to place their bets and how big those bets will be. Which of their products should they sell online? How, if at all, should they engage with Amazon? (Some CPG players are putting their best people on Amazon-dedicated account teams. CPG companies will, of course, need to weigh the risks and trade-offs of partnering with Amazon, including the potential for channel conflict and the loss of control over the “virtual shelf.”) How much of their marketing budget should they shift to mobile media? Digital marketing, including mobile, now accounts for 22 percent of global ad spending and could grow to 27 percent by 2017, according to eMarketer.

The mobile Internet is already prevalent; the Internet of Things—the embedding of networked sensors in physical objects—is just beginning to make waves. It’s not a stretch to imagine that in a few years CPG companies will be using sensors to track consumers’ use of products (for example, sensors that can be ingested to measure caloric intake), customize marketing messages (as in shelf displays that change depending on who is standing in front of them), or revolutionize their manufacturing and logistics processes.

3-D printing, or additive manufacturing, is already in use in the CPG sector, with 3-D-printed jewelry and toys being sold in online marketplaces. Other CPG categories—apparel, furniture, sporting goods—may soon follow. In the near term, product designers can use 3-D printing to reduce prototyping time from weeks to minutes; in the longer term, it will open up mass-customization opportunities.

Taking full advantage of these transformative technologies will require companies to invest in building the relevant capabilities, including digital-content creation, mobile marketing, and advanced data analytics. CPG manufacturers should closely follow the evolution of these technologies and foster a test-and-learn mind-set within their organization, building an experimentation “engine” that can quickly scale up successful pilots.

Merger mania—with a global twist

A new M&A wave seems to be gathering strength—and this time it’s global. As we said earlier, emerging-market companies are expanding aggressively and becoming global winners. Our analysis shows that since 2007, Brazilian companies have made 13 CPG deals valued at more than $500 million each; Chinese companies have completed 7 such deals, and Mexican companies another 7. Most of these deals were in categories in which global or regional scale is an advantage, such as snacks, nonperishable beverages, paper products, personal care, and tobacco. (US-based companies completed 51 deals of comparable size over the same period.) The combined 27 major CPG deals originating in Brazil, China, and Mexico represent a huge jump from the 5 deals those three countries completed in the 2000–06 time frame (3 for Brazil, 2 for Mexico, and none for China).

Even after recent mergers, many CPG categories remain fragmented both within and across countries. Companies will need to make choices about how best to capture synergies in both developed and emerging markets. How will they position themselves to be the acquirer rather than the acquired? How will they avoid paying too much for acquisitions—a mistake many companies made during the M&A wave in 2000–07? How—and how aggressively—will US manufacturers lower their cost base to compete with emerging-market players?

We see three potential growth archetypes: global giants, from both developed and emerging markets, will consolidate categories that benefit from economies of scale (such as those previously mentioned as well as apparel and footwear); regional leaders will concentrate on value segments in categories where scale is less of an advantage (such as food, paper products, and dairy); and small, agile innovators will introduce new business models and capture premium niches.

In any case, CPG companies would do well to build their M&A capabilities. They should identify and carefully assess potential targets or partners in emerging markets. And they should be financially prepared to pounce on an M&A opportunity when it arises—specifically, by reducing their debt and loading up on cash.

Regulatory risk and the expanding role of government

Government’s influence on the consumer sector is increasing rapidly and will only continue to do so, given the ubiquity of CPG products and the role they play in people’s daily lives. The financial impact of regulation on the industry won’t be trivial: extended producer responsibility regulation, for example, which has been implemented in Europe, could cost the US CPG industry upwards of $7 billion per year according to prior McKinsey research.

Some industry leaders are taking action before government—or the public—demands it. Wrigley, a division of Mars, took its Alert Energy caffeinated chewing gum off the market in order to give the Food and Drug Administration time to pass regulations on caffeine-enhanced food and drinks.7 Coca-Cola is partnering with groups in Mexico to invest in an effort to increase recycling of materials for sustainable packaging. CPG companies and industry associations have formed coalitions to tackle issues such as front-of-package labeling, tax policy, and waste management.

CPG companies must decide what stance to take toward government. Will they take a leading role on one or more topics, or will they instead take a wait-and-see position and be prepared to act quickly when regulations change? Our prediction is that more companies will choose to be proactive and collaborative, following the example set by Unilever, whose Sustainable Living Plan outlines a set of ambitious social and environmental goals for the company.

Regardless of its regulatory strategy, each company must earn the “social license” to be in business. It must become aware of the issues and the potential impact of regulation on its business and on the overall industry, particularly in three areas: economic, environmental, and health-related. Best-practice companies regularly review emerging regulatory issues and plan for plausible scenarios, give regulatory issues a place on the agenda at both the top-management level and the board level, and ensure that exposure to government affairs is part of leadership development and job rotation for high-potential managers.8

The CPG industry will look very different in just a few years. It will be a bigger industry, with much larger global players and more competition from up-and-coming companies in emerging markets. Resource constraints and scale will lead to very different value-chain structures. New technologies will play an increasingly central role in business, as will regulation and government affairs. Already, these changes are compelling CPG companies to rethink how they do business and pursue growth. Companies that fail to adapt to these changes—or that make suboptimal choices—will be left behind by more thoughtful, action-oriented competitors.

About the authors

Jim Brennan is a principal in McKinsey’s New Jersey office, Greg Kelly is a director in the Atlanta office, and Anne Martinez is a specialist in the Stamford office.

business, healthcare, startup

Steve Blank – Lean LaunchPad class in Life Science

Steve Blank’s Lean LaunchPad start up class covering life sciences, digital health, diagnostics and medical devices.

Ties in to lean start up approach.

http://steveblank.com/category/life-sciences/

Discovered via this MedGadget interview:  http://www.medgadget.com/2013/12/leaning-out-the-life-sciences-interview-with-steve-blank.html

Blank’s HBR article: HBR_LeanStartUp

Business Model Canvas care of Business Model Generation: business_model_canvas_poster

BizModelCanvas

business, management and leadership

Gittins: Properly pitching the Darwinian tent

  • Darwinian economics needs to be applied in a nuanced way to firms because of the Darwinian dynamics which play out internally
  • Darwinian selection at the level of groups implies that the interests of group members are weaker or synonymous with the interests of the group as a whole. In the real world, they are not.
  • The key to improving the performance of firms, we’re told, is not to strike some inefficient compromise between the interests of individuals and their group but to work with the grain of human nature to bring individual and group interests into alignment. If you know what you’re doing, this can be achieved relatively easily and at low cost.

Darwinian model of economics flawed for firms

Ross Gittins
Published: December 28, 2013 – 3:00AM

What can the theory of evolution tell us about how the economy works? A lot. But probably not what you think it does.

Famous economists such as Joseph Schumpeter (author of the notion of ”creative destruction”) and Milton Friedman, and the contemporary economic historian Niall Ferguson, have viewed economies as Darwinian arenas: competition among firms reflects the ruthless logic of natural selection. Firms struggle with each other, with successful firms surviving and unsuccessful ones dying.

Thus evolution seems to support three pillars of the conventional, neoclassical model of the economy. First, that ”economic actors” are self-interested, second, that self-interest works to the good of the public (propelling Adam Smith’s ”invisible hand”) and, third, that together these lead the market to deliver the community ideal outcomes (”optimisation”).

But there’s a basic fault in this contention, as Dominic Johnson, of Oxford University, Michael Price, of Britain’s Brunel University, and Mark van Vugt, of Amsterdam’s VU University, point out in their paper, Darwin’s Invisible Hand.

In conventional economics, ”economic actors” can be either individuals or firms, although the theory tends to treat firms as though they were individuals. In reality, however, firms are groups of individuals – in the case of big national and multinational companies, thousands of them in one firm.

So if Darwinian selection applies to competitive markets, this implies that selection pressure acts on groups, not individuals. And group selection, as opposed to conventional Darwinian selection at the individual level, leads to the emergence of traits that act against self-interest.

With group selection, ”we should expect the suppression of self-interest among individuals, not its flourishing”, the authors say.

”Firms with less self-interested workers will compete more effectively and spread at the expense of firms with more self-interested workers, which will compete less effectively and decline. In other words, the model predicts nasty firms but nice people.

”Firms vie for market share and profits, group selection would predict, while individuals within those firms sacrifice their own interests for the good of the group. They will work long hours, accept low status and low salaries, co-operate with each other, share resources, accept hierarchy, obey their bosses, volunteer for extra duties and never help – or move to – rival firms.”

Does that sound realistic to you? No, me neither.

”In reality,” the authors say, ”firms are made up of individual human beings, with various goals and motives but, most importantly, considerable self-interest.

”Darwinian selection at the level of groups implies that the interests of group members are weaker or synonymous with the interests of the group as a whole. In the real world, they are not. There is often some overlap, of course: the boss will want his workers to perform well; the workers will want the firm to survive. But we also have strong personal desires for salary, status, rank, reputation, free time and better jobs.

”In short, any evolutionary model must account for two opposing processes that operate simultaneously: competition between firms and competition between the individuals within them.”

So the authors are adherents to a relatively new school of thought holding that selection occurs at both levels: ”multi-level selection theory”. And this leads them to conclude that taking account of the role of evolutionary selection doesn’t really bolster the conclusions of the neoclassical model.

Economic actors are self-interested only sometimes. Self-interest promotes the public good only sometimes. And these things mean markets produce optimal results only sometimes.

Great. But where does that get us? The authors argue that being more realistic by integrating the factors at work at group level with those at work at the individual level allows us to make better predictions on which interests – individual or group – will dominate in particular circumstances.

”At one extreme, if selection among groups is frequent and severe, we may expect an increased alignment of individual and group interests resulting in successful firms with hard-working, groupish, highly committed employees,” they say.

”At the other extreme, if selection among groups is rare and weak, we may expect increased conflicts of interest resulting in inefficient firms and lazy, self-interested workers.”

By group selection they mean cultural selection – some ideas and practices beat others – not biological selection. And, because ideas can spread so quickly, not needing to wait for genetic evolution to occur generation by generation, cultural evolution is much faster and more powerful.

The authors say competition between firms may be a quintessential example of cultural selection.

A weakness of the neoclassical model is that it exalts competition between economic agents while ignoring the co-operation within firms that is such an important part of real-world competition in markets.

The evolutionary approach, however, does much to illuminate the role of co-operation.

”Individuals are adapted to co-operate in groups but do so in individually adaptive ways,” they say. ”That is, we are co-operative, but only so long as our own individual costs and benefits are taken into account.”

People want to be rewarded for their contribution but also to see that their reward doesn’t compare badly with the rewards fellow workers are getting relative to their contribution.

But whereas the conventional economic model focuses on only monetary rewards and punishments, the evolutionary approach predicts that individuals will be powerfully motivated to strive for social status and prestige within their firm, even at the expense of material rewards or the risk of punishment.

The evolutionary approach also offers a better explanation of why individuals would want to take on stressful and time-consuming leadership positions, which are not always compensated by higher salaries: higher social status rewards.

The key to improving the performance of firms, we’re told, is not to strike some inefficient compromise between the interests of individuals and their group but to work with the grain of human nature to bring individual and group interests into alignment. If you know what you’re doing, this can be achieved relatively easily and at low cost.

Ross Gittins is the economics editor.

This story was found at: http://www.smh.com.au/business/darwinian-model-of-economics-flawed-for-firms-20131227-2zzns.html

business, data saving lives, facts & data points

2014 Big Data Predictions

  • growth will be 6 times the overall IT market
  • shortage of talent > analytics as a service, small/nimble analytics, cloud will grow quickly at 50% CAGR
  • VC investment moving to the top layer – from information management to analytics, discovery and applications
  • “Analytics 3.0” (IIA) and “Digitization of Everything” – companies across industries will use analytics on their accumulated data to develop new products and services — G.E. is the poster boy for this
  • automation solutions – cognitive computing, rules management, analytics, biometrics, rich media recognition – will replace knowledge worker roles
  • over-automation of decisions will result in an optimal mix of human and machine learning
  • Heightened focus on governance and privacy will improve results – governance will be a driver for ROI (Capgemini)

 

Gil Press, Contributor

I write about technology, entrepreneurs and innovation.

12/12/2013 @ 11:18AM |18,465 views

$16.1 Billion Big Data Market: 2014 Predictions From IDC And IIA

Both IDC and The International Institute of Analytics (IIA) discussed their big data and analytics predictions for 2014 in separate webcasts earlier this week. Here is my summary of their predictions plus a few nuggets from other sources.

IDC predicts that the market for big data will reach $16.1 billion in 2014, growing 6 times faster than the overall IT market. IDC includes in this figure Infrastructure (servers, storage, etc., the largest and fastest growing segment at 45% of the market), services (29%) and software (24%). IDC commented that the benefits of big data are not always clear today (indeed, BNY Mellon recently asked its 50,000 employees “for ideas about how to harness the power of Big Data”). IIA predicted that companies will want to see demonstrable value in 2014 and will focus on embedding big data analytics in business processes to drive process improvement.

The much-discussed shortage of analytics and data science talent led IIA to make three separate but related predictions. One prediction is that the adoption of analytics-as-a-service will accelerate with “ready-made analytics in the cloud” offering an attractive option for quickly testing big data analytics or scaling up existing programs. Similarly, Capgemini predicts (in an email to me) “smaller, nimble analytics,” as a result of the rise of machine-to-machine data, “making cloud the de facto solution.” And IDC predicts that cloud infrastructure will be the fastest-growing sub-segment of the big data market, with a 2013-2017 CAGR of close to 50%.

Another IIA prediction related to the dearth of talent is the increasing attention paid by companies to organizing in teams the analysts and data scientists they currently have on board, either embedded in the business units or in a center of excellence. The focus will be on making these teams more effective by establishing and sharing best practices and by “operationalizing and managing models,” with the rest of the world getting closer to the proficiency level of the financial industry in this regard (in other words,keeping up with the quants? hopefully, also learning from the financial industry’s failures in this regard—see financial crisis, 2008 edition).

As for the prospects for alleviating the talent shortage, IIA commented that there are now well over 100 programs at universities in the US where analytics and data science “are in focus” (see my list of graduate programs here). IDC, for its part, cautioned that these programs “will bear fruit only in four to five years,” referring obviously to the newly-established data science programs. IDC agrees with IIA that companies providing big data analytics services will fill the gap in the meantime and predicts that the big data professional services market will exceed $4.5 billion in 2014. The number of vendors providing such services will triple over the next three years, according to IDC, and these firms will “aggressively acquire scarce big data talent,” making it scarcer.

A very interesting dimension to the dearth of talent raised by IDC is the shortage of IT professionals capable of dealing with the new big data requirements. 33% of respondents to an IDC and Computerworld survey earlier this year noted as one of their big data challenges the “lack of sufficiently skilled big data and analytics IT staff” (“lack of sufficient number of staff with appropriate analytics skills” was selected by 45% of respondents).

Also interesting was IDC’s expansion of the services part of the market to include “value added content providers.” These include “traditional vendors” such as Thompson, LexisNexis, and Experian; “new wave vendors” such as DataSift, Gnip, and LinkedIn; “company and personal information vendors” such as Acxiom, Equifax, and Tarsus; and “search engine/aggregators” such as Yahoo, Google, and Salesforce/Data.com. IDC believes that this market segment will be “challenged by lack of business model clarity and standards.”

A related prediction from IDC is that VC investment will shift to the top layers of the big data software stack, from information management to the “analytics & discovery” and “applications” layers. New types of applications (“use cases”), such as personalized medicine, will emerge out of what IDC predicts will be the blurring of the boundaries between high-performance computing (previously limited to scientific/engineering applications) and “enterprise big data” (i.e., mainstream applications managed by an IT department). IIA sees other new horizons for the application of big data, predicting that companies in a variety of industries will increasingly use analytics on the data they have accumulated to develop new products and services. GE has been the poster boy for this emerging trend, called “Analytics 3.0” by IIA, or “the digitization of everything” by me (you decide).

Another application, security, will become the next big front for big data, IDC predicts, as security infrastructure will increasingly take on big data-like attributes. Big data will be used to correlate log data and identify malicious activity in real time, allowing companies to react quickly, rather than after the event. Gartner begs to differ, however, predicting that “big data technology in security contexts will stay immature, expensive and difficult to manage for most organizations as targeted attacks become more stealthy and complex to identify in progress. … The noise about big data for security has grown deafening in the industry, but the reality lags far, far behind.”

In a somewhat far-out prediction, IIA talked about facial recognition and wearable device data that will be incorporated into predictive analytics. One of the examples given was “pet stores could use facial recognition to greet dogs as well as customers.” IDC was a bit closer to 2014 (or was it?) when it predicted that the “proliferation of sensor, mobile, wearable, and embedded devices (Internet of Things) will become a significant driver of the big data market,” stressing the need for investment in “Data-in-Motion” and “real-time analysis of geo-dispersed incoming data streams,” primarily in the cloud (that you don’t need wearables or geo-whatever to satisfy your obsession with quantifying your life, was recently demonstrated by the resident data scientist at MarkITx who crunched his lunches to come up with a happiness-per-gram metric).

Both IDC and IIA got a bit more into the technologies behind big data analytics, with IDC predicting the co-habitation for the foreseeable future (my words) of traditional database technology (RDBMS) with the newer Hadoop ecosystem and NoSQL databases, concluding that “in the short term,” information management will become more complex for most organizations (see shortage of qualified IT staff above); and IIA predicting that “the adoption of data visualization will accelerate in both the high and low ends of the complexity spectrum [for analytics].” Humans, however, don’t comprehend things in more than two dimensions or, at most, three dimensions, so IIA advised tempering our enthusiasm “a bit” (this came from self-described Tom “Curmudgeon” Davenport so you may want to consider how much tempering you want to do; as for me, I always opt for being “uber-curmudgeon”).

Last but certainly not least, both IDC and IIA talked about automation in the context of big data. IDC predicts that “decision and automation solutions, utilizing a mix of cognitive computing, rules management, analytics, biometrics, rich media recognition software and commercialized high-performance computing infrastructure [phew!], will proliferate.” Some of these solutions, IDC says (warns?), “will begin to replace or significantly impact knowledge worker roles.”  IIA predicts that “we will see a continued move to machine learning and automation to keep pace with speed and volume of data” and that “as they strive to operationalize analytics but encounter challenges with the over-automation of decisions, companies will focus more on the optimal mix between human and machine capability and judgment.” If you take humans too much out of the equation, their decision making will atrophy, warned IIA, asking “If you don’t have experts, who will train the next generation of [machine learning] software?” From the IIA’s lips, to the NSA’s ears, I say. (Well, we can assume these words were collected and stored by the omnipresent sleuths the second they were uttered; the question is: do they understand what the words mean?)

One prediction that didn’t make the official list of IIA’s predictions, but Davenport nevertheless managed to include in the webcast, was that “companies will need to hire lawyers to verify that they actually own the data.” Indeed, the nagging issues—that I think will be even more prominent in 2014—of privacy and governance were largely missing from the IDC and IIA discussions (Capgemini, in contrast, contributed this: “A heightened focus on governance will improve analytic results… Governance will need to be a driver in shaping the ROI story for Big Data in 2014”).  Also missing were discussions of “open data” and the increased use of big data by the public sector (outside of the NSA) to name just a few pertinent big data trends not on their list of predictions. But of course, the challenge is to select the nine or ten most important ones and we have lots to chew on with IDC’s and IIA’s lists.

Listeners to the IIA webcast were given the opportunity to vote on which predictions they thought would come true:

IIA_Poll-Results

Participants in the IIA webcast included Sarah Gates, Tom Davenport, Bob Morison, Bill Franks, Greta Roberts, Omer Sohail and Sanjeev Kumar; IDC’s webcast was delivered by Dan Vesset and Ashish Nadkarni; Capgemini’s predictions were attributed to SVP for Business Information Management Scott Schlesinger.

Follow me on Twitter @GilPress or Facebook or Google+ 

business, data saving lives, entrepreneurship, healthy habits, meaning, policy, rapid learning health systems

FDA rearguard frame…

It’s all happening anyway. Eventually, the tide will surge and the wall will burst.

Already, an explosion of monitoring, testing, and sensing devices are coming on the market, providing consumers with instant analysis of their fitness, blood chemistry, sleep patterns and food intake. It’s only a matter of time before regulators feel compelled by consumer demand to find a way to accommodate better and cheaper innovations, and for slowly changing industries to dramatically restructure themselves in the face of overwhelming new opportunities. The long-term potential of vast databases of genomic data to improve health outcomes, reduce costs, and reorient the debate on medical priorities is too valuable to be held back for long — and arguably the biggest transformation for the healthcare industry since the discovery of antibiotics in the early 20th century.

http://www.wired.com/opinion/2014/01/the-fda-may-win-the-battle-this-holiday-season-but-23andme-will-win-the-war/

Regulating 23andMe to Death Won’t Stop the New Age of Genetic Testing

  • BY LARRY DOWNES AND PAUL NUNES
  • 01.01.14
  • 6:30 AM

 

Image: ynse/Flickr

 

Market disruptions often occur — or not — as the direct result of unintended collisions between breakthrough technologies and their more incremental regulators. In the latest dust-up, the U.S. Food and Drug Administration (FDA) last month ordered startup 23andMe to stop marketing its $99 genetic analysis kit, just before the Christmas shopping season kicked into high gear.

To date, over half a million customers have taken the swab in return for detailed ancestry data and personalized information on 248 genetic traits and health conditions. The company, which launched in 2007 with substantial backing from Google, has been working closely — albeit more slowly than the FDA would have liked — with the FDA to ensure it complies with federal health and safety regulations. But the agency concluded in its recent warning letter that 23andMe was marketing a “device” that was “intended for use in the diagnosis of diseases or other conditions,” and as such, its marketing materials required pre-approval from the FDA, which includes extensive research studies.

23andMe is an example of what we call a “Big Bang Disruption” — a product or service innovation that undermines existing markets and industries seemingly overnight by being simultaneously better andcheaper than the competition. What’s happening in genomic testing (and healthcare in general) is consistent with our research in over 30 different industry segments, from manufacturing to financial services to consumer products.

When technologies improve exponentially, many industry incumbents — and the regulators who oversee them — are kept constantly off-balance. That’s because incumbents have been indoctrinated by a generation of academic literature and MBA training to ignore disruptive products until they had a chance to mature in the market, assuming they would first appear as cheaper but inferior substitutes that would only appeal to niche market segments.

Doctors — who are also incumbents in this situation — are struggling to respond to disruptive medical technologies that change the power dynamic in the patient relationship. Several 23andMe users have reported taking the FDA’s advice of reviewing their genetic results with their physicians, only to find the doctors unprepared, unwilling, or downright hostile to helping interpret the data.

Often, incumbents’ only competitive response — or the only one they can think of — is to run to the regulators. That’s what’s has been happening to car-sharing services such as Uber, Lyft, and Sidecar; to private drone makers; and casual accommodation services such as Airbnb, to name just a few examples. And now it’s happening to 23andMe, one of hundreds of new startups aimed at giving healthcare consumers more and better information about their own bodies — information that has long been under the exclusive and increasingly expensive control of medical professionals.

Absent any real law on the subject, the agency has strained credulity to categorize 23andMe’s product as a diagnostic “device” — making it subject to its most stringent oversight. The FDA’s letter focuses intently on the potential that consumers will both under- and over-react to the genetic information revealed. The agency fears that users will pressure their doctors for potentially unnecessary surgery or medication to treat conditions for which they are genetically pre-disposed, for example. And it assumes that the costs of such information abuse outweigh any benefits — none of which are mentioned in the agency’s analysis.

The company, of course, has agreed to comply with the FDA’s stern warning, and has ceased providing its customers with anything other than hereditary data. For now. Perhaps it will reach some accommodation with the agency, or perhaps the FDA’s ire will prove untamable, an end to the innovative startup and whatever value its technology might have delivered.

But as with every Big Bang Disruptor in our study, winning the battle and winning the war are two very different things.

The FDA is applying a least common denominator standard to 23andMe, and applying it arbitrarily. Already, an explosion of monitoring, testing, and sensing devices are coming on the market, providing consumers with instant analysis of their fitness, blood chemistry, sleep patterns and food intake. It’s only a matter of time before regulators feel compelled by consumer demand to find a way to accommodate better and cheaper innovations, and for slowly changing industries to dramatically restructure themselves in the face of overwhelming new opportunities. The long-term potential of vast databases of genomic data to improve health outcomes, reduce costs, and reorient the debate on medical priorities is too valuable to be held back for long — and arguably the biggest transformation for the healthcare industry since the discovery of antibiotics in the early 20th century.

The information flood is coming. If not this Christmas season, then one in the near future. Before long, $100 will get you sequencing of not just the million genes 23andMe currently examines, but all of them. Regulators and medical practitioners must focus their attention not on raising temporary obstacles, but on figuring out how they can make the best use of this inevitable tidal wave of information.

Whatever the outcome for 23andMe, this is a losing battle for industry incumbents who believe they can hold back the future forever.

 

Larry Downes & Paul Nunes

Larry Downes and Paul Nunes are co-authors of Big Bang Disruption: Strategy in the Age of Devastating Innovation (Penguin Portfolio 2014). Downes is Research Fellow with the Accenture Institute for High Performance, where Nunes serves as its Global Managing Director of Research. Their book has been selected as a 2014 book of the year by the Consumer Electronics Association.

business, cool, data saving lives, healthy habits, policy

A behavioural vaccine

  • the marshmallow experiment gone wild >> a behavioural vaccine
  • paying tobacconists for cigarettes they refuse to sell to kids
  • paying smoking mothers to quit

 

Listen to the story: 

Good Behavior’ More Than A Game To Health Care Plan

by KRISTIAN FODEN-VENCIL

Danebo Elementary in Eugene, Ore., is one of 50 schools receiving money to teach classes while integrating something called the “Good Behavior Game.” Teacher Cami Railey sits at a small table, surrounded by four kids. She’s about to teach them the “s” sound and the “a” sound. But first, as she does every day, she goes over the rules.

“You’re going to earn your stars today by sitting in the learning position,” she says. “That means your bottom is on your seat, backs on the back of your seat. Excellent job, just like that.”

For good learning behavior, like sitting quietly, keeping their eyes on the teacher and working hard, kids get a star and some stickers.

Railey says the game keeps the kids plugged in and therefore learning more. That in turn makes them better educated teens and adults who’re less likely to pick up a dangerous habit, like smoking.

The Washington, D.C., nonprofit Coalition for Evidence Based Policy says it works. It did a studythat found that by age 13, the game had reduced the number of kids who had started to smoke by 26 percent — and reduced the number of kids who had started to take hard drugs by more than half.

The fact that a teacher is playing the Good Behavior Game isn’t unusual. What is unusual is that Trillium is paying for it. Part of the Affordable Care Act involves the federal government giving money to states to figure out new ways to prevent people from getting sick in the first place.

So Trillium is setting aside nearly $900,000 a year for disease prevention strategies, like this one. Jennifer Webster is the disease prevention coordinator for Trillium Community Health, and she thinks it’s a good investment.

“The Good Behavior Game is more than just a game that you play in the classroom. It’s actually been called a behavioral vaccine,” she says. “This is really what needs to be done. What we really need to focus on is prevention.”

Trillium is paying the poorer schools of Eugene’s Bethel School District to adopt the strategy in 50 classrooms.

Trillium CEO Terry Coplin says changes to Oregon and federal law mean that instead of paying for each Medicaid recipient to get treatment, Trillium gets a fixed amount of money for each of its 56,000 Medicaid recipients. That way Trillium can pay for disease prevention efforts that benefit the whole Medicaid population, not just person by person as they need it.

“I think the return on investment for the Good Behavior Game is going to be somewhere in the neighborhood of 10 to one,” Coplin says.

So, for each dollar spent on playing the game, the health agency expects to save $10 by not having to pay to treat these kids later in life for lung cancer because they took up smoking.

Coplin concedes that some of Trillium’s Medicaid recipients will leave the system each year. But he says prevention still makes medical and financial sense.

“All the incentives are really aligned in the right direction. The healthier that we can make the population, the bigger the financial reward,” he says.

The Oregon Health Authority estimates that each pack of cigarettes smoked costs Oregonians about $13 in medical expenses and productivity losses.

Not all the money Trillium is spending goes for the Good Behavior Game. Some of it is earmarked to pay pregnant smokers cold, hard cash to give up the habit. There’s also a plan to have kids try to buy cigarettes at local stores, then give money to store owners who refuse to sell.

This story is part of a reporting partnership with NPR, Oregon Public Broadcasting and Kaiser Health News.