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Match Supply and Demand in Service Industries

From the Harvard Business Review November 1976 Issue

by W. Earl Sasser

What makes service industries so distinct from manufacturing ones is their immediacy: the hamburgers have to be hot, the motel rooms exactly where the sleepy travelers want them, and the airline seats empty when the customers want to fly. Balancing the supply and demand sides of a service industry is not easy, and whether a manager does it well or not will, this author writes, make all the difference. In this rundown of the juggling feat service managers perform, the author discusses the two basic strategies—“chase demand” and “level capacity”—available to most service companies. He goes on to discuss several ways service managers can alter demand and influence capacity.

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Digitizing Change Management

Research tells us that most change efforts fail. Yet change methodologies are stuck in a predigital era. It’s high time to start catching up.

July 2015 | byBoris Ewenstein, Wesley Smith, and Ashvin Sologar – McKinsey & Co.

Change management as it is traditionally applied is outdated. We know, for example, that 70 percent of change programs fail to achieve their goals, largely due to employee resistance and lack of management support. We also know that when people are truly invested in change it is 30 percent more likely to stick. While companies have been obsessing about how to use digital to improve their customer-facing businesses, the application of digital tools to promote and accelerate internal change has received far less scrutiny. However, applying new digital tools can make change more meaningful—and durable—both for the individuals who are experiencing it and for those who are implementing it.

The advent of digital change tools comes at just the right time. Organizations today must simultaneously deliver rapid results and sustainable growth in an increasingly competitive environment. They are being forced to adapt and change to an unprecedented degree: leaders have to make decisions more quickly; managers have to react more rapidly to opportunities and threats; employees on the front line have to be more flexible and collaborative. Mastering the art of changing quickly is now a critical competitive advantage.

For many organizations, a five-year strategic plan—or even a three-year one—is a thing of the past. Organizations that once enjoyed the luxury of time to test and roll out new initiatives must now do so in a compressed period while competing with tens or hundreds of existing (and often incomplete) initiatives. In this dynamic and fast-paced environment, competitive advantage will accrue to companies with the ability to set new priorities and implement new processes quicker than their rivals.

The power of digital to drive change

Large companies are increasingly engaged in multiple simultaneous change programs, often involving scores of people across numerous geographies. While traditional workshops and training courses have their place, they are not effective at scale and are slow moving.

B2C companies have unlocked powerful digital tools to enhance the customer journey and shift consumer behavior. Wearable technology, adaptive interfaces, and integration into social platforms are all areas where B2C companies have innovated to make change more personal and responsive. Some of these same digital tools and techniques can be applied with great effectiveness to change-management techniques within an organization. Digital dashboards and personalized messages, for example, can build faster, more effective support for new behaviors or processes in environments where management capacity to engage deeply and frequently with every employee is constrained by time and geography.

Digitizing five areas in particular can help make internal change efforts more effective and enduring.

1. Provide just-in-time feedback

The best feedback processes are designed to offer the right information when the recipient can actually act on it. Just-in-time feedback gives recipients the opportunity to make adjustments to their behavior and to witness the effects of these adjustments on performance.

Consider the experience of a beverage company experiencing sustained share losses and stagnant market growth in a highly competitive market in Africa. The challenge was to motivate 1,000-plus sales representatives to sell with greater urgency and effectiveness. A simple SMS message system was implemented to keep the widely distributed sales reps, often on the road for weeks at a time, plugged into the organization. Each rep received two to three daily SMS messages with personalized performance information, along with customer and market insights. For example, one message might offer feedback on which outlets had placed orders below target; another would alert the rep to a situation that indicated a need for increased orders, such as special events or popular brands that were trending in the area. Within days of implementing the system, cross-selling and upselling rates increased to more than 50 percent from 4 percent, and within the first year, the solution delivered a $25 million increase in gross margin, which helped to swing a 1.5 percent market-share loss into a 1 percent gain.

2. Personalize the experience

Personalization is about filtering information in a way that is uniquely relevant to the user and showing each individual’s role in and contribution to a greater group goal. An easy-to-use system can be an effective motivator and engender positive peer pressure.

This worked brilliantly for a rail yard looking to reduce the idle time of its engines and cars by up to 10 percent. It implemented a system that presented only the most relevant information to each worker at that moment, such as details on the status of a train under that worker’s supervision, the precise whereabouts of each of the trains in the yard, or alerts indicating which train to work on. Providing such specific and relevant information helped workers clarify priorities, increase accountability, and reduce delays.

3. Sidestep hierarchy

Creating direct connections among people across the organization allows them to sidestep cumbersome hierarchal protocols and shorten the time it takes to get things done. It also fosters more direct and instant connections that allow employees to share important information, find answers quickly, and get help and advice from people they trust.

In the rail-yard example, a new digital communications platform was introduced to connect relevant parties right away, bypassing middlemen and ensuring that issues get resolved quickly and efficiently. For example, if the person in charge of the rail yard has a question about the status of an incoming train, he or she need only log into the system and tap the train icon to pose the question directly to the individuals working on that train. Previously, all calls and queries had to be routed through a central source. This ability to bridge organizational divides is a core advantage in increasing agility, collaboration, and effectiveness.

4. Build empathy, community, and shared purpose

In increasingly global organizations, communities involved in change efforts are often physically distant from one another. Providing an outlet for colleagues to share and see all the information related to a task, including progress updates and informal commentary, can create an important esprit de corps.

Specific tools are necessary to achieve this level of connectivity and commitment. Those that we have seen work well include shared dashboards, visualizations of activity across the team, “gamification” to bolster competition, and online forums where people can easily speak to one another (for example, linking a Twitter-like feed to a work flow or creating forums tied to leaderboards so people can easily discuss how to move up in the rankings).

This approach worked particularly well with a leading global bank aiming to reduce critical job vacancies. The sourcing team made the HR process a shared experience, showing all stakeholders the end-to-end view—dashboards identifying vacancies; hiring requisitions made and approved; candidates identified, tested, and interviewed; offers made and accepted; and hire letters issued. This transparency and openness built a shared commitment to getting results, a greater willingness to deliver on one’s own step in the process, and a greater willingness to help one another beyond functional boundaries.

5. Demonstrate progress

Organizational change is like turning a ship: the people at the front can see the change but the people at the back may not notice for a while. Digital change tools are helpful in this case to communicate progress so that people can see what is happening in real time. More sophisticated tools can also show individual contributions toward the common goal. We have seen how this type of communication makes the change feel more urgent and real, which in turn creates momentum that can help push an organization to a tipping point where a new way of doing things becomes the way things are done.

Digital tools and platforms, if correctly applied, offer a powerful new way to accelerate and amplify the ability of an organization to change. However, let’s be clear: the tool should not drive the solution. Each company should have a clear view of the new behavior it wants to reinforce and find a digital solution to support it. The best solutions are tightly focused on a specific task and are rolled out only after successful pilots are completed. The chances of success increase when management actively encourages feedback from users and incorporates it to give them a sense of ownership in the process.

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Has Stephen Wolfram made knowledge a searchable commodity?

An interesting perspective on the future of jobs as we know them, from the man that made knowledge a searchable commodity.

Stephen Wolfram spoke with TechRepublic about his work in science and technology, his new book, and how technology is automating the world.

One of the key themes in Stephen Wolfram’s career has been the long road to fruition taken by technological advancement. In the beginning, there is often a glimmer of how something might work, or be useful, but it can take years for that vision to become a reality.

For example, computational models for neural networks were invented in the 1940s, and Wolfram worked on them in the 1980s. However, they are only now at a point where they can be utilized in a meaningful way, such as the Wolfram Language Image Identification Project.

“The ideas it’s using are not that different than the ideas that I was playing with in 1980,” Wolfram said. “But, what makes it possible in that case is a lot of ambient technology that didn’t exist back at that time.”

Another interest of Wolfram’s is the coding of everyday discourse. As he began researching this field to see what had been conducted, he found that most of it was done by philosophers 300 years ago or more. Again, it shows the disconnect between when ideas come about and when they are fully realized.

Even current iterations of some of Wolfram Research’s key products such as Mathematica, Wolfram|Alpha and the recently announced Wolfram Language are innovations with three decades of development behind them, Wolfram said.

Automating work

Wolfram became a student of physics at a young age, eventually earning a PhD in theoretical physics from Caltech when he was only 20 years old. After he became even more interested in computer science, his began working in a fairly distinct pattern.

“The thing that has turned out to work really well for me — and I’ve probably done about four or five cycles of this — is do basic science, figure out some principles and ideas and so on, use those ideas in technology, build up a bunch of practical technology, use that technology to understand more about basic science, and then repeat,” he said.

Because of his pioneering work in automation, Wolfram and his work are often brought up in conversations around artificial intelligence. While AI is generally regarded as the “mystery thing” behind many tech products, Wolfram said, he believes it is merely continuing the story of technology, which is merely the automation of things we had done by hand before.

Automation in the workforce is a paramount concern at the moment, but Wolfram said it’s nothing new.

“If you look at the US workforce from 100 years ago, 80% of it was in agriculture,” he said. “Almost none of it is in agriculture anymore because that stuff was automated. There are a large collection of professions, many of whose functions will be automated and probably fairly soon.”

In terms of what will the people do when their job is eliminated by automation, Wolfram said that somewhere, someone still has to define the goals of those systems. And, the kind of goals we have had as humans have changed over time.

For some people, he said, the nightmare scenario is that in the future people will simply be sitting around playing video games. But if you look at today’s society from the perspective of human society 1,000 years ago, many of the things we do today could be viewed similar to that nightmare scenario.

Automating knowledge

As technology continues to advance and new forms of automation become apparent, Wolfram said that he is interested in how that affects the ways we gather and use information.

“One question is: Our civilization has accumulated a certain amount of knowledge,” he said. “There are questions that can be answered on the basis of that knowledge. Can we do that automatically or, do we have to go find an expert and ask them?”

Of course, this is what he has tried to accomplish with Wolfram Alpha. Additionally, he is also interested in automation of programming and he believes we’re right on the cusp of being able to program things at a dramatically faster pace.

Certain industry tools have converged between consumer-grade and professional grade – such as video editing software. It’s fairly easy for hobbyist video editors to access professional video editing suites.

The same hasn’t been done with programming yet, he said, and that’s what he wants to accomplish with Wolfram Language. That product is central to the future of the company.

As Wolfram Research continues to move forward, it’s undeniable the impact that Wolfram has had on the scientific and technology communities. When asked what advice he’d give to aspiring scientists and technologists, he said it is difficult to give general advice because of how unique each individual is.

But he said two questions to ask are: What are you good at, and what do you like to do? These are actually more difficult to answer than you think.

“I have a, perhaps, optimistic view of the world that for every person there’s kind of an optimal niche,” he said. “Finding that niche is often quite a puzzle.”

In his own words…

If you weren’t working in science and technology, what other profession would you love to try?

“The story of my life is I do the things I like to do. I’ve figured stuff out, run businesses, these are things I like to do. Actually, another story of my life is anything that starts as a hobby doesn’t stay as a hobby. There was a time when I used to do business as a hobby and pretty soon I was running companies. There was a different time when I was doing science as a hobby and that turned into a profession too. So, I’m very bad at hobbies from that point of view. I’ve been lucky in that I’ve managed to spend my life doing things that are really the things that I want to be doing.

“If I’d lived in a different age when there weren’t computers and those kinds of things — I don’t know. I think I was, again, lucky to be living at this time when…a number of things, particularly in science had just become possible to do right around the time when I did them, so to speak. Had I lived 100 years earlier or something, they wouldn’t have been even close to being doable. The situation not to be in is, your in the Isaac Newton time, 300 years ago, and you figure out that artificial satellites are possible, but then you can’t start a rocket launch company in 1687.”

What’s the best thing you’ve read lately?

“I’m really bad at reading books. I own maybe 8,000 books or something and my wife has always pointed out that we had to build a house just to accommodate the books… Actually, I happen to be writing a book again, which I thought I might never — I wrote a big book called A New Kind of Science that came out in 2002, and that book took me ten and a half years to write. It was definitely the single most grueling activity that I’ve undertaken in my life. I consider one of my main achievements with the book in addition to its content was just the fact that I completed it…

“The last few weeks I’ve been writing a book, which I’m happy to say has been going at like 100 times the rate of A New Kind of Science. It’s a very different thing. It’s basically a very elementary introduction to the concepts of the Wolfram Language. The question is, what are the minimal set of concepts that you need to understand to be able to become literate with this language. My model was a strange model which is elementary Latin textbooks. There’s one approach to teaching language, which is immersive, where you say ‘Okay, I’m going to learn French. Let’s go to France and not speak a word of English.’ Pretty soon you’re going to end up learning French. That doesn’t work with a dead language like Latin and it doesn’t work with a computer language because we can’t live our lives purely in a computer language…”

By  Connor Forrest, TechRepublic

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The ‘Gig Economy’ Revolution

The Labor Department issued guidance aimed at cracking down on employers who misclassify their employees as subcontractors, however this is primarily aimed at traditional employers such as the construction and hospitality industries.

Politicians and Silicon Valley prospectuses are all atwitter over the perils and promise of the next big thing, the gig economy.
Hillary Clinton warned of the downsides of this informal workforce in a recent economic speech, including the potential erosion of workplace protections. Eyeing an opening, Jeb Bush used the ride-hailing app Uber to get to a meeting with Thumbtack, a company that helps people hire everyone from handymen to DJs. Companies like these have been portrayed as the “race-to-the-bottom economy” and “the industrial revolution of our time.”
Harder to find so far is proof of the revolution.
Far from turning into a nation of gig workers, Americans are becoming slightly less likely to be self-employed, and less prone to hold multiple jobs. Official government data shows around 95% of those who report having jobs are accounted for on the formal payroll of U.S. employers, little changed from a decade ago.
If Uber and its ilk were fundamentally undermining the relationship workers have with employers, that shift would be showing up in at least some of the key economic indicators. Hundreds of thousands of Americans, or even a few million, may have dabbled in the gig economy, but in the context of the 157 million-strong U.S. labor force, the trend remains marginal.
“It could be companies like Lyft and Uber look terribly important by their capital market valuation, but the actual economic activity they’re responsible for might not be all that great,” said Gary Burtless, a labor market economist at the centrist Brookings Institution.
Uber, with around 160,000 active drivers under contract in the U.S. at the end of last year, has sought to hold a funding round this year that would value the company at $50 billion. That’s approximately the market capitalization of General Motors, which sold 2.4 million cars in the last quarter alone.
Many workers cobbling a living from tech platforms in the gig economy should be classified as self-employed. But the share of Americans who are self-employed and unincorporated has slowly declined over the past decade, to about 6.5% of workers today, down from as high as 7.7% in 2005 and as high as 8.5% in the mid-1990s, according to Labor Department figures.

Made popular as a jazz term as far back as the 1920s, gig work defies easy definition. The consulting firm McKinsey & Co., in a June report, described it as “contingent work that is transacted on a digital marketplace.” McKinsey estimated that less than 1% of the U.S. working-age population fell into this category, including some people who already work a part- or full-time job.
The Labor Department collects data on workers in different ways: surveying the civilian population to ask if they have jobs, tracking the number of people paying into the unemployment insurance system and surveying companies on the size of their payrolls.
No discrepancy has emerged between people who report having jobs in a survey and the number of people companies report on their payrolls.
Some workers might have a primary job and do some TaskRabbit work on the weekend for extra cash, or sell artisanal greeting cards on Etsy as a hobby. But the share of people who hold multiple jobs is also in decline—only 4.8% of workers do, down from 5.5% in 2005 and 6.3% in 1995.
Alternate definitions seeking to measure the gig economy have produced a range of estimates. The Government Accountability Office recently estimated the “contingent workforce” makes up about 8% of the employed U.S. workforce, using a definition that includes agency temps and on-call workers.
From 1995 to 2005, the Labor Department tracked irregular work with a biannual Contingent Workers Survey. In recent years, though, Congress hasn’t granted the agency funding to carry it out.
Whatever its size, gig work has become a new political fault line.
New York City Mayor Bill de Blasio sought to squelch Uber’s growth in his city last week, prompting Republican presidential candidate Marco Rubio to boast about riding Uber around the city. GOP candidate Rand Paul has said such services stimulate the economy and lower prices. California has waged a legal battle against Uber over whether its drivers ought to be classified as employees, rather than contractors.
The Labor Department recently issued guidance aimed at cracking down on employers who misclassify their employees as subcontractors. But David Weil, the administrator of the department’s Wage and Hour Division, said that the guidance is largely aimed at traditional employers, such as in the construction and hospitality sectors.
“What we are really concerned about is its prevalence in the longest-established parts of industries,” said Mr. Weil.
Economists note that regular work and irregular work have always coexisted; some are skeptical of whether gigs arranged via a smartphone are truly novel.
The narrative of new apps upending the world may be seductive to coastal elites in New York, Washington and San Francisco, said Mr. Burtless of Brookings, noting that some have devised “big theories” based on “their own interaction sitting in the back of a car.”
But these theories, he worries, lack “hard evidence.”
By Josh Zumbrun – Wall Street Journal

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Looks like it’s time to acknowledge the move to digital

From Wells Fargo IT/BPO Services Weekly – Thought of the Week:
Separating From the Pack. This week highlighted that while discretionary demand remains strong, particularly in “digital” (e.g., omni-channel, mobility, analytics, etc.) areas, not all providers are benefitting from it equally. Those doing well have been ahead of the curve in investments (both organic and inorganic) to reposition their businesses to these emerging areas of demand and are led by Accenture (ACN) and Cognizant (CTSH), in our view. After two years of uneven discretionary spending, clients appear to have placed a higher priority on digital initiatives and have become more consistent in their deployment of budget dollars. Much of the current digital work is helping clients to “digitize” their existing systems, architectures and processes, along with some digital front-end development and agency/creative work. While clearly requiring foresight and investment from providers to position their businesses (both with the right skillsets and appropriate demand-creating front-end resources), digital enablement seems to us to be a natural evolution of IT services work as technology architectures evolve. It is the next phase of digital (for clients: allowing them to explore new business models and turn the significant amount of data now being captured into a business advantage; for providers: building increasingly IP-enabled [intellectual property] solutions) where we believe there will be even more separation amongst providers as a new approach will be required, in our view.

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War With Uber Hurt de Blasio With Allies

Read this and then think about what will happen to the employee independent contractor issue….

Aides to the mayor say they weren’t prepared for the force of Uber’s campaign-style attack of TV ads

Mayor Bill de Blasio’s summertime battle with Uber exposed vulnerabilities in his political operation and has given rise to resentment among many of the allies he will need to advance his agenda at City Hall.
The mayor’s office was caught flat-footed by the car service’s potent blend of local politicking and multimedia ad buys that aimed to kill a City Council bill to constrain the growth of the city’s for-hire car fleet, according to City Council members, City Hall aides, business leaders and longtime political observers. Many council members were drawn into a fight they considered unwinnable and unnecessary.
And Mr. de Blasio alienated one of his important liberal allies, Council Speaker Melissa Mark-Viverito, who lashed out at him for suggesting he could unilaterally put the Uber cap back on the table.
“City Hall had a deep miscalculation on this issue,” said Mitchell Moss, a professor of urban policy and planning at New York University. “What this showed you was the power of an intelligent, sophisticated campaign. You never see a business take on City Hall like this.”
Uber launched a “De Blasio’s Uber” feature on its app to protest the New York City mayor’s proposal to limit the number of Uber drivers on the city streets. Photo: Tom Vigliotta/The Wall Street Journal
It all ended July 22 when the mayor’s aides dropped the proposed cap on the service for now. Uber, in turn, agreed to participate in a traffic study and discuss other issues.
“Despite a $10 million surprise attack campaign launched by Uber as good faith negotiations were still under way, the city won significant concessions that Uber has refused to provide to other cities,” said Karen Hinton, a spokeswoman for the mayor.
The city said Uber will now share data it previously hasn’t and will be part of a larger conversation on drivers’ wages and accessibility for disabled riders.
Aides to the mayor said they weren’t prepared for the force of Uber’s campaign-style attack of television ads, which began to air on July 14, the day after they met with Uber officials to negotiate.
Uber also ran a sophisticated digital strategy, with more than 40,000 people emailing the mayor and almost 20,000 sending him twitter messages.
City Hall repeatedly stumbled when it tried to fight back.
Aides managed to send emails to thousands of Uber users, saying they were only trying to slow the car service’s expansion—while studying the issue—but were flooded by many people incorrectly accusing them of trying to totally ban the service.
When the mayor’s office stopped talking to Uber for several days, company officials continued talks with Ms. Mark-Viverito. They also huddled with state officials and many members of the council, who were supportive of the company, according to people familiar with the matter.
By July 17, aides inside City Hall realized they had to shift their message. After initially arguing the cap was largely about congestion, they began to portray Uber as a corporate behemoth that didn’t want to play by the rules. While some of the new arguments seemed to work, the changing messages allowed Uber to advance its contention that City Hall had no real reason for banning them.
City Hall’s arguments were largely lost in the noise, said Brooklyn Councilman Steve Levin, who sponsored the bill.
“By the end, it was like, why the hell are we doing this,” said a liberal City Council member and ally of the mayor. “The messaging was just all over the place.”
Another council member said he decided to vote against the bill because City Hall couldn’t articulate why he should support it after a series of meetings. Neither council member would discuss the mayor’s political operation on the record.
After Uber staged several large rallies, the mayor’s office aggressively tried to find supporters. But a rally on City Hall steps had fewer than 200 people, and many other officials didn’t want to enter the fray.
Many of the city’s influential black leaders were already backing Uber and had appeared at a July 14 news conference. Aides to the mayor were furious. “It was the African-American ministers that turned this fight,” said Kathy Wylde, president and CEO of the Partnership for New York City, a pro-business group.
By last Tuesday, Mr. de Blasio’s aides had at least 27 votes, according to City Council members—enough to win approval from the 51-member council—and had said the council vote would happen two days later.
Many on the council said they would vote for the bill but thought a vote was unnecessary and wanted to slow the process. Many also already disappointed in the mayor for picking other fights that hurt them politically, such as his proposed ban on horse carriages.
Ms. Mark-Viverito, frustrated at how the mayor’s office had handled the situation and in a difficult position with her members, decided last Tuesday a vote wasn’t worth it. So when Uber and the mayor had a final conversation Wednesday, the mayor’s office had no choice but to offer a deal Uber liked far more. The company quickly accepted.
“No one comes out of this looking good, neither the mayor’s office or the council,” said Bronx Councilman Ritchie Torres.
– Wall Street Journal

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