The Road Ahead

Deep Blue vs. DeepMind’s AlphaGo

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Deep Blue vs. DeepMind’s AlphaGo

IBM’s Deep Blue (Deep Blue) and Google DeepMind’s AlphaGo (AlphaGo) are the two famous computer programs in the history of Artificial Intelligence (AI). What are the difference between the two systems and its meaning to the development of AI? This article will provide you with some fundamental information to answer this question.

1. Deep Blue, An Artificial Intelligence Milestone

In 1997, the Deep Blue system of IBM defeated the world chess champion, Gary Kasparov. It was the first time that the world witnessed the historic event of a computer being worthy contender to one of the world’s sharpest mind. At that time, the victory was widely described as milestone in AI. Though, Deep Blue’s technology turned out to be useful for chess only and not much else. Computer Science did not undergo a revolution.

An overview of Artificial Intelligence’s techniques for Games

Considering the games of two opposing opponents like Chess, Caro or Go…, the answer to these problems can be referred to the state space search or combinatorial optimization problem. In general, we have to deal with two major sub-problems, that’s (i) searching in the state space and (ii) finding the best evaluation function for the game.

For the games like Chess and Caro, the sub-problem (i) can be solved by using a wise optimization strategy and a fast enough computer. Normally, programmers use minimax search with alpha-beta pruning or other heuristics algorithms for searching. To the the sub-problem (ii), there will be various answers which depends on the game and the cleverness of solver.

Deep Blue technology

IBM’s programmers use the two main ideas above for their Deep Blue program. First, they built a function that incorporated lots of detailed chess knowledge to evaluate any given board position. Second, they used an IBM’s supercomputer to find the best possible positions, picking out the move that would force the best possible final board position.

So, here you could think that Deep Blue can not be called “smart”. It just simply used its advantage in high performance computing to calculate millions calculations in a second. That’s it.

But, can we apply the same technique for Go? Until now, the answer is NO.

You might think it’s just a question of working hard and coming up with a good way of evaluating board positions. Though, after decades of attempts to do this using conventional approaches, there was still no obvious way to apply the search strategy that was so successful for chess, and Go programs remained disappointing. This began to change in 2006, with the introduction of so-called Monte Carlo tree search algorithms, which tried a new approach to evaluation based on a clever way of randomly simulating games. But Go programs still fell far short of human players in ability. It seemed as though a strong intuitive sense of board position was essential to success. Why the search strategy cannot be applied for Go?

The reason is Go is a game of profound complexity. The possible positions of Go is more than a googol (10^100) times larger than in chess. Therefore, its state space complexity makes Go hard for computer to play and becomes a big challenge for AI researchers. Traditional AI methods, which construct a search tree over all possible positions, don’t have a chance in Go

2. DeepMind’s AlphaGo takes AI to a new level

In 2015, AlphaGo, the Go-playing system defeated Lee Sedol, one of the strongest Go players in the world. What is behind AlphaGo? How did DeepMind’s AlphaGo do it?

AlphaGo uses deep leaning and neural networks to essentially teach itself to play. This is the same technology that Facebook uses to recognize faces in images that have been processed down to pixel level. AlphaGo’s intelligence is based on its ability to learn from millions of Go positions and moves from human-played games. I will have another post on deep learning and neural networks soon.

Since DeepMind’s AlphaGo has ability to learn based on machine learning technologies, it is a lot more human-like and, of course, artificially intelligent than IBM’s Deep Blue, which beat chess master Kasparov by using brute forte computing power to search for the best moves. That made the Google’s Go win is a such a big deal in AI history.

3. After AlphaGo, what’s next for AI?

AlphaGo’s victories against the Korean legendary Go player in 2015 marked a major milestone in AI research. DeepMind used machine learning and neural networks to give its AlphaGo the ability to learn and play at a world-class level. At the moment, there are many applications and fields in AI are applied these technologies, such as in Natural Language Processing, Image and Speech Recognition…, etc.

With that said, systems like AlphaGo are genuinely exciting. We have learned to use computer systems to reproduce at least some forms of human intuition. Now we’ve got so many wonderful challenges ahead: to expand the range of intuition types we can represent, to make the systems stable, to understand why and how they work, and to learn better ways to combine them with the existing strengths of computer systems. It’s a tremendously promising time for artificial intelligence.

Reference:

1. https://en.wikipedia.org/wiki/Deep_Blue

2. https://en.wikipedia.org/wiki/AlphaGo

3. http://www.theverge.com

4. http://ftp.bstu.by/ai

5. https://www.quantamagazine.org/20160329-why-alphago-is-really-such-a-big-deal

6. https://blog.google/topics/machine-learning/alphago-machine-learning-game-go

7. https://www.nvidia.com/en-us/deep-learning-ai

Complexity Classes

In Computer Science, in order to understand the problems for which solutions are not there, the problems are divided into classes and we call them as complexity classes. In complexity theory, a complexity class is a set of problems with related complexity. It is a branch of theory of computation that studies the resources required during computation to solve a given problem. The most common resources are time (how much time the algorithm takes to solve a problem) and space (how much memory it takes)

Types of Complexity Classes

P Class

The complexity class P is the set of decision problem that can be solved by a deterministic machine in polynomial time (P stands for polynomial time). P problems are a set of problems whose solutions are easy to find.

NP Class

The complexity class NP (NP stands for non-deterministic polynomial time) is the set of decision problems that can be solved by a non-deterministic machine in polynomial time. NP class problems refer to a set of problems whose solutions are hard to find, but easy to verify. That means, if someone give you a solution to the problem, you can tell them whether it is right or not in polynomial time. For the NP class problems, if the answer is yes, then there is a proof of this fact, which can be verified in polynomial time.

Let’s consider this example to understand the P and NP problems better. Suppose that you are organizing housing accommodations for a group of five hundred university students. Space is limited and only one hundred of the students will receive places in the dormitory. To complicate matters, the Dean has provided you with a list of pairs of incompatible students, and requested that no pair from this list appear in your final choice. This is an example of what computer scientists call an NP-problem, since it is easy to check if a given choice of one hundred students proposed by a coworker is satisfactory (i.e., no pair taken from your coworker’s list also appears on the list from the Dean’s office), however the task of generating such a list from scratch seems to be so hard as to be completely impractical.

Indeed, the total number of ways of choosing one hundred students from the five hundred applicants is greater than the number of atoms in the known universe! Thus no future civilization could ever hope to build a supercomputer capable of solving the problem by brute force; that is, by checking every possible combination of 100 students. However, this apparent difficulty may only reflect the lack of ingenuity of your programmer. In fact, one of the outstanding problems in computer science is determining whether questions exist whose answer can be quickly checked, but which require an impossibly long time to solve by any direct procedure. Problems like the one listed above certainly seem to be of this kind, but so far no one has managed to prove that any of them really are so hard as they appear, i.e., that there really is no feasible way to generate an answer with the help of a computer.

Co-NP Class

Co-NP (Complement of NP) is the opposite of NP. If the answer to a problem in Co-NP is no, then there is a proof of this fact that can be checked in polynomial time.

Relationship between P, NP, and Co-NP

Every decision problem in P is also in NP. If a problem is in P, we can verify YES answer in polynomial time. Similarly, any problem in P is also in Co-NP.

np-complete-8-638

One of the important open question in theoretical computer science is whether or not P = NP.  Until now, nobody knows. Intuitively, it should be obvious that P NP, but nobody know how to prove it.

Another open question is whether NP and Co-NP are different. Even if we can verify every YES answer quickly, there is no reason to think that we can also verify NO answer quickly. It is generally believe that NP Co-NP, but again nobody knows how to prove it.

NP-hard Class

It is a class of problems such that every problem in NP reduces to it. All NP-hard problems are not in NP, so it takes long time to even check them. That means, if someone gives you a solution for NP-hard problem, it takes a long time for you to check whether it is right or not.

NP-complete Class

Finally, a problem is NP-complete if it is part of both NP-hard and NP. NP-complete problems are the hardest problems in NP. If anyone finds a polynomial-time algorithm for one NP-complete problem, then we can find polynomial-time algorithm for every NP-complete problem. This means that we can check an answer fast and every problem in NP reduces to it.

k8ggs

Relationship between P, NP, Co-NP, NP-hard, and NP-complete

The relationships between different components is as shown below (remember, this is just an assumption).

p_np_np-co_np-hard

The set of problems that are NP-hard is strict superset of the problems that are NP-complete. Some problems (like halting problem) are NP-hard, but not in NP. NP-hard problems might be impossible to solve in general. We can tell the difference in difficulty between NP-hard and NP-complete problems because the class NP include everything easier than its “toughest” problems – if a problem is not in NP, it is harder than all the problems in NP.

Problem: P vs. NP?

The P versus NP problem is a major unsolved problem in computer science. Informally speaking, it asks whether every problem whose solution can be quickly verified by a computer can also be quickly solved by a computer (Wikipedia). The problem P vs NP is also one of the seven Millennium Prize Problems selected by the Clay Mathematics Institute to carry a $1,000,000 prize for the first correct solution.

Does P==NP? This is a big question, because right now there are lots of NP-complete that can’t be solved quickly. If P=NP, that means there is a way to solve them fast. Remember that “quickly” means not trial-and-error.

Reference:

  1. Wikipedia
  2. http://www.claymath.org
  3. http://www.spiritofsoft.com

A Note On Technology Trend and Startup

This post is my note taken when I joined in a talk on topic Technology Trends in Hanoi by Vitaly Golomb, an investor and startup evangelist at HP Tech Ventures. It was an intriguing and encouraging talk delivered by an entrepreneur and keynote speaker from Silicon Valley. During the speech, Vitaly gave some advices on How, Where and What you should be investing in your entrepreneurial adventure. He also emphasized on building a business for it is going to be the next day after tomorrow. So, if you already start your startup or are still thinking of it, or even this area is totally new to you, this note could give you some ideas on it.

  • Startup – An Entrepreneurial Adventure

To most people, a good life will be like this: get good grades, go to a good college, get in a good company, get regular promotions, retire, play golf and “rest in peace”. That is the usual career that every mom wants their kids to have. But, how it looks like for a startup career?

Actually, it is not easy starting a startup. Let me give you an example. Ben Horowitz from Andreessen Horowitz said “As a startup CEO, I slept like a baby. I woke up every 2 hours and cried.”. Experts say that it takes long time to build a startup. Normally, it takes 1 year to develop an idea, 2 years to see if anyone cares, if there is potential customer. If you are successful, it takes about 5 to 8 years to see it through. Assume you start your first startup at age of 22 after graduating from college, you may start and fail several times. Even you are lucky, then congratulations you are in thirty with your first startup. The next one could be when you are in mid-thirty. Obviously, you have to face the trade-off between building a company and your lifetime. But, to be an entrepreneur, that is the choice you have to make. So, the entrepreneurial adventure is a tough journey. Though, there are always some things you can learn.

  • On How

There are some theories here. First, you must distinguish between a startup and a company. What is a startup? “A Startup is not a smaller version of a large company. A startup is an experiment in search of a business model”, Steve Blank [1]. Startup is the special kind of new business, where your first stage is looking for a business model. In the transition period, you need some management, you start breaking even point, getting some profits, hiring some experienced guys or the gray-hairs to build a company and then you become a company with employees. Startup is very different to other kinds of business like restaurants, hotels, or professional services firms.

Startup1

Startup2

Now, look at the Clayton Christensen’s Technology Life Cycle “S-Curve”, it’s also important to think about when you are going to a certain technology. This framework, which operates alongside the Bass Model, is used to determine performance in regards to time and effort. It assists in determining the level of maturity of the industry/product. As a result, when evaluating a product or an industry, it is crucial to understand where it is on the S-curve due to the many implications that result out of that such as the possible risks and pitfalls that are associated with certain phases on it.

The research part may be in universities or research centers. The sweet part is somewhere in the middle. This is when you should build your startup. Because you can scale very quickly, create product very quickly. The new generation of technology is built there.

S-CurveIn term of stage financing, let’s look at the curve below. So, for long time, you are going to be burning your money. Until you start breaking even, you start making profit. [2].

Financing curveSo what’s coming next? We are now in the end of mobile era. The mobile era has been done. There are thousands to millions applications in App Store and Google Play Store. You have to find what comes next.

Innovation Cycle

  • On Where

Where a startup should be? A startup needs its ecosystem or an innovation cluster. “Clusters affect competition by increasing productivity of companies driving direction and pace of innovation stimulating the formation of new businesses” – Clusters and the new economics of competition, Micheal E. Porter. [3].Ecosystem

Here is the top 20 startup ecosystem around the globe you may refer to [4] [5]. In Vietnam, do you know some startup ecosystem? Try googling it 🙂

top-20-startup-ecosystems-header

  • On What

Finally, what should you work on? What should you spend your time on? What should you invest your years of your life into? What is coming next? What’s worthwhile?

What is the next big thing?

Notice that we are now in the end of mobile era. There are millions applications out there in the stores. Almost ideas have been had. If you just think of building a startup in mobile application development, you may be very boring soon. We need to find something more interesting, something bigger for the next years to come.

And you may hear about the terms like the Internet of Things or the Internet of Everything, Hyper Mobility, Smart Machines, 3D Transformation, AI…People will be surrounded with real reality, virtual and digital reality altogether soon…What does it look like in the future?

Well, you may think we have hypermobility, we have smartphones with data connections, smart watches…Though, hypermobility in the next few years will mean nano-technology. There will be computer inside of you that can fix diseases.

HyperMobilityAnd, Internet of Thing (IoT) means internet can connect everything, every device, any transaction you make every day…Another interesting thing is about smart machines. It will be not just about robot. It will be about the machine that can think, do tasks and solve problems better than we can. An example is Google’s Artificial Intelligence did beat Go world champion Lee Sedol to win the five-game series 4-1 in March 2016. There are a lot of examples that you find easily on this point.

IoT

SM3D is considered as another next big thing in the future to drive the next industrial revolution. Now, you may think of 3D printing that helps to make a prototype of a product.

3DSo what’s next is completely digital design and digital production. With the innovation of new materials, think of a world with on-demand production, without waste, without inventory, without warehouses. Let’s see:

In summary, the speaker gave a message that as a startup, you should build things that aligned with future. That way, you will have better opportunity to growth your business and compete with startups worldwide.

Now, are you excited? Are you ready to move on?

See also:

[1] https://steveblank.com/2010/01/25/whats-a-startup-first-principles

[2] https://startupxplore.com/en/blog/types-startup-investing

[3] https://hbr.org/1998/11/clusters-and-the-new-economics-of-competition

[4] http://tech.co/top-20-startup-ecosystems-ranked-2015-07

[5] http://martapancaldi.com/swengineering/2015/09/23/comparing-the-worlds-top-startup-ecosystems

Reference: A talk of Vitaly Golomb, HP Tech Ventures, Technology Trends, Hanoi 2016

Hai bộ phim về học sinh thi toán quốc tế

Required Skills for Management Consulting Jobs

'Leadereship' highlighted in green

Soft skills are very important when evaluating likability or fit for a certain job. Unlike hard skills, which are about relevant skill set or particular abilities to carry out certain type of tasks, soft skills relate to one’s ability to interact effectively with people.

In consulting, it is extremely important to develop the following soft skills:

Charismatic and Sociable

Consultants need to interact with different types of people on a regular basis. That’s why being charming and likable will definitely do wonders for your career as a consultant. How people perceive you will have a direct effect on your consulting career. Apparently, if your clients perceive you as personable it will be easier for them to trust you. Also, if your team members find you approachable, it will be much easier to collaborate and achieve your goals. However, being highly sociable must not be confused with cockiness.

Strong Work Ethic

This skill is a major requirement perhaps for any kind of job. In consulting, it is imperative that you display this characteristic every single time. As you will be working with big, reputable companies as well as influential and intelligent people, it is only fit that you show professionalism. Also, strong work ethic means being willing to go the extra mile to help a client achieve its goals. Good consultants are ready to go beyond the call of duty just to get the job done.

Positive Attitude

Having a positive attitude towards work, and perhaps towards everything, would be beneficial to your career as a consultant. Go-getters are very much attractive to top firms. As a consultant you should be able to help improve employee morale or motivate team members. And you can only achieve this if you display a positive attitude. Even if you are not naturally bubbly and tend to be more low-key, there are many ways to exhibit positive energy, like always smiling or perhaps simply saying a few encouraging lines or giving compliments.

Oral and Written Communication Skills

The ability to communicate your ideas clearly is perhaps one of the most important skills you need as a consultant. You see, the main product that you are selling is your ideas or insights. And in order for your client to buy this idea from you, you need to let them know exactly what it is. You need to be able to express your thoughts in the simplest and clearest manner. Most tension and stressed are due to inability to communicate clearly. So it is extremely helpful if you have a way with words. That’s why excellent communicators generally do well in consulting.

Ability to Listen

Good consultants are good listeners. Why? Because listening takes more than hearing what the other person is saying, it requires understanding. You won’t be able to help any organization deal with their problem if you don’t fully understand what their needs and goals are. Many people tend to listen passively. If you want to succeed in consulting, effectively listening skill is a must have. This means being able to know what and when to ask questions and when to be quiet and simply listen to every word. Good communication is not just about expressing yourself, it is also about engaging and understanding the other party.

Leadership

Consultants are expected to have strong leadership skills. They are generally achievers and socially involved. While many say that some are born leaders, this skill can be developed. As a consultant you will manage different types of people so you need to possess the ability to lead and manage effectively. Remember, the mark of a true leader is not about the position held, it’s about taking responsibility and influencing your team towards achieving a common goal. Lead by example – motivate and show initiative.

Teamwork / Team Building

Consulting is not a job for someone who doesn’t want to collaborate with people on a daily basis. Yes, you need to have strong leadership skills to be a good consultant, but you also need to have a teamwork mindset. It’s not just about you making the big decisions. You must learn to acknowledge other people’s expertise and make time to help those people who are working with you on your project.

Conflict Resolution

As client and team interaction would be an integral part of your life as a consultant, it is important that you know how to resolve conflicts within the team and even more prevent them from happening. In fact, it is a vital trait for any leadership role. This skill is key to the longevity of any relationship. Conflicts generally arise from differing needs, ideas, values or opinions. When handled in a respectful manner, conflict may provide an opportunity to strengthen the bond between parties. Be patient and recognize the ways to come to a compromise.

Time Management

Many people tend to struggle in terms of managing their time, tasks and responsibilities effectively. As a consultant, you may need to juggle around multiple clients at certain times. With that, it is really important that you have efficient time management skill. Learn how to set priorities and stick to your schedule.

Self-confidence

As a consultant, you would be making big decisions and you should not be afraid to make them. You must then have confidence in your knowledge and skills. If you don’t seem look pretty confident, you won’t earn the trust of your clients, colleagues and team members. Speak, dress and act with confidence.

Work under Pressure

Every work has a deadline to meet. And you need to be pretty good at working under pressure in order to hit challenging deadlines in consulting. You must learn the art of achieving maximum results in a short amount of time. In order to do this you need to stay focused.

Persuading, Influencing and Negotiating Skills

Consultants also need to master the art of persuasion. It will be part of your daily consulting life to influence and negotiate with other people, particularly with your clients and team members. This is actually a primary skill for anyone in the business field. Influencing people in a positive way will greatly help an organization achieve its goals. However, this must not involve coercion in any form. Rather, it’s about acknowledging other opinions but being able to change their minds.

Adaptability

To succeed in the consulting world, you need to have a passion for constant learning. You should also have the ability to stretch your skills in order to adapt to the ever changing needs of your clients.

Source: ConsultingFact.com

The Balanced Scorecard – Measurement and Management in the Information Age

Measurement and Management in the Information Age

In the information age, company’s success depends largely on its ability to invest and manage intellectual assets. Functional specialization must be integrated into customer-based business processes. Mass production and service delivery of standard products and services must be replaced by flexible, responsive, and high-quality delivery of innovative products and services that can be individualized to targeted customer segments. Innovation and improvement of products, services, and processes will be generated by skillful employees, superior information technology, and aligned organization procedures.

As organizations invest in acquiring these new capabilities, their success (or failure) cannot be motivated or measured in the short run by the traditional financial accounting model. This financial model, developed for trading companies and industrial age corporations, measures events of the past, not the investments in the capabilities that provide values for the future.

The Balances Scorecard is a new framework for integrating measures derived from strategy. While retaining financial measures of the past performance, the Balanced Scorecard introduces the drivers of future financial performance. The drivers, encompassing customer, internal business processes, and learning and growth perspectives, are derived from an explicit and rigorous translation of the organization’s strategy into tangible objectives and measures.

The Balances Scorecard, however, is more than a new measurement system. Innovative companies use the scorecard as the central, organizing framework for their management processes. The real power of the Balanced Scorecard, however, occurs when it is transformed from a measurement system to a management system. Companies see how it can be used to:

  • clarify and gain consensus about strategy
  • communicate strategy throughout the organization
  • align departmental and personal goals to the strategy
  • link the strategic objectives to long-term targets and annual budgets
  • identify and align strategic initiatives
  • perform periodic and systematic strategic reviews, and
  • obtain feedback to learn about and improve strategy

Management processes built around the scorecard enable the organization to become aligned and focused on implementing the long term strategy. Used in this way, the Balanced Scorecard becomes the foundation for managing information age organizations.

Originated by Dr. Robert Kaplan (Harvard Business School) and David Norton, the innovation of the balanced scorecard is described as follow: “The balanced scorecard retains traditional financial measures. But financial measures tell the story of past events, an adequate story for industrial age companies for which investments in long-term capabilities and customer relationships were not critical for success. These financial measures are inadequate, however, for guiding and evaluating the journey that information age companies must make to create future value through investment in customers, suppliers, employees, processes, technology, and innovation.”

The Balanced Scorecard

Perspectives

The balanced scorecard suggests that we view the organization from four perspectives, and to develop metrics, collect data and analyze it relative to each of these perspectives:

The Learning & Growth Perspective
This perspective includes employee training and corporate cultural attitudes related to both individual and corporate self-improvement. In a knowledge-worker organization, people – the only repository of knowledge – are the main resource. In the current climate of rapid technological change, it is becoming necessary for knowledge workers to be in a continuous learning mode. Metrics can be put into place to guide managers in focusing training funds where they can help the most. In any case, learning and growth constitute the essential foundation for success of any knowledge-worker organization.

Kaplan and Norton emphasize that ‘learning’ is more than ‘training’; it also includes things like mentors and tutors within the organization, as well as that ease of communication among workers that allows them to readily get help on a problem when it is needed. It also includes technological tools; what the Baldrige criteria call “high performance work systems.”

The Business Process Perspective
This perspective refers to internal business processes. Metrics based on this perspective allow the managers to know how well their business is running, and whether its products and services conform to customer requirements (the mission). These metrics have to be carefully designed by those who know these processes most intimately; with our unique missions these are not something that can be developed by outside consultants.

The Customer Perspective
Recent management philosophy has shown an increasing realization of the importance of customer focus and customer satisfaction in any business. These are leading indicators: if customers are not satisfied, they will eventually find other suppliers that will meet their needs. Poor performance from this perspective is thus a leading indicator of future decline, even though the current financial picture may look good.

In developing metrics for satisfaction, customers should be analyzed in terms of kinds of customers and the kinds of processes for which we are providing a product or service to those customer groups.

The Financial Perspective
Kaplan and Norton do not disregard the traditional need for financial data. Timely and accurate funding data will always be a priority, and managers will do whatever necessary to provide it. In fact, often there is more than enough handling and processing of financial data. With the implementation of a corporate database, it is hoped that more of the processing can be centralized and automated. But the point is that the current emphasis on financials leads to the “unbalanced” situation with regard to other perspectives. There is perhaps a need to include additional financial-related data, such as risk assessment and cost-benefit data, in this category.

Strategy Mapping

Strategy maps are communication tools used to tell a story of how value is created for the organization. They show a logical, step-by-step connection between strategic objectives (shown as ovals on the map) in the form of a cause-and-effect chain. Generally speaking, improving performance in the objectives found in the Learning & Growth perspective (the bottom row) enables the organization to improve its Internal Process perspective Objectives (the next row up), which in turn enables the organization to create desirable results in the Customer and Financial perspectives (the top two rows).

 Strategy Map

References:

  1. The Balanced Scorecard: Translating Strategy Into Action by Robert S. Kaplan, David O. Norton.
  2. https://balancedscorecard.org

See What’s Next in this series:

  • Why Does Business Need a Balanced Scorecard?
  • Financial Perspective
  • Customer Perspective
  • Internal Business Process Perspective
  • Learning and Growth Perspective
  • Strategy Map In the Balanced Scorecard
  • Implementing a Balanced Scorecard Management Program

Professional Services Organizations

Understanding How They Work


What type of organization sells no products, and yet charges some of the highest prices anywhere? Where can the ‘items’ a company sells simply walk out the door? And what kind of company finds it almost impossible to achieve economies of scale on the ‘cost of goods sold’?

The answer: professional services firms.

The unique nature of these organizations creates management and leadership challenges that many other companies do not have to deal with.

In this article, we look at some of the characteristics of professional services firms – and some of the common management challenges they face.

The Typical Work Model

Professional services firms exist in many different industries. They include lawyers, advertising professionals, architects, accountants, financial advisers, engineers, and consultants, among others. Basically, they can be any organization or profession that offers customized, knowledge-based services to clients.

In his influential book “Managing the Professional Service Firm,” David Maister compares the professional services organization to a medieval craftsman’s shop. Today, just as in the Middle Ages, there are “apprentices” (junior managers or new hires), “journeymen” (mid-level managers or experienced professionals), and “master craftsmen” (senior partners or upper management). Some call these levels the “grinders,” “minders,” and “finders” of a firm, respectively.

Most professional services firms use a leveraging system to maximize profitability. For instance, junior employees usually earn a relatively low salary. They accept lower pay because they want to gain experience, and have the opportunity to work closely with senior partners (“finders”) to acquire their valuable knowledge.

When clients hire a firm, they generally do so because of that firm’s credibility and reputation. But clients don’t necessarily get the direct expertise of the senior managers. It’s the lower-paid juniors who often perform most of the hands-on work. Clients then meet for a limited time with higher-paid senior managers, who oversee quality and offer advice. This allows the firm to charge a high fee to clients, and still keep a high profit margin. This way of working is typical of the partnership model, where the senior professionals are managers as well as producers. Not all professional services organizations operate this way, but many – particularly the larger firms – do.

The Unique Challenges of Intangible Products

Unlike other types of organizations, professional services firms sell knowledge and expertise – not tangible, physical products. So these firms have different needs, and face different challenges.

For example, consider a manufacturing plant. Once a product has been designed, mass production can create units 24 hours a day on machinery that’s monitored by low-wage workers. Manufacturing managers emphasize the importance of standardization, quality, and productivity in their teams.

But how does this compare with an accounting firm? While managers should still stress quality and productivity, they can’t standardize or ‘mass-produce’ their services. Their profitability comes from ‘face time,’ or billing hours, with clients – all of whom have different needs and demands. If team members don’t meet with clients or work on specific projects, they don’t earn money for the firm.

If you’re a manager at a professional services firm, it can be difficult to balance high productivity, personalized service, and knowledge management. And one of your primary tasks is to maintain your ‘human capital’ – in other words, keep your staff motivated and productive. Manufacturing plants spend a lot of effort maintaining their machinery and warehouses. Services firms must spend time and energy coaching their teams – and actively ensuring that the most talented workers stay with them (more on this below). Without expert professionals and a strong reputation, the firm may fail.

This is a simplistic comparison, but it shows just how different professional services firms are from other types of businesses – and why managing these firms needs a different approach in order to succeed.

Staff Motivation

Motivation can be a major problem, especially for a team of junior professionals, and it’s becoming tougher for many firms to retain their top talent.

In the past, the goal of most junior managers was to become a partner. This usually created a competitive environment that, in turn, led to high-quality work. As time passed, the ‘stars,’ or strongest workers, were promoted – and the weaker team members either left or gave up.

These days, however, partnership is not always the ultimate reward. Younger professionals sometimes question whether the extra work is worth it. Long hours, heavy workloads, and difficult clients are often unappealing to people who are seeking work-life balance.

And today, young professionals in the services industries have far more options than they used to. It’s no longer considered unethical for a young lawyer or financial adviser to change firms every few years in pursuit of better opportunities.

Because of this motivation challenge, professional services firms must create ways to attract – and keep – the best and brightest workers. After all, their people are what they sell. So if those people aren’t fully motivated and producing top-quality work, then the firm is at a competitive disadvantage.

Scheduling and Billing

Professional services firms are profitable only when their team members bill hours to clients. Therefore, new work is often assigned to the person who’s currently not working billable hours. Although this maximizes revenue in the short term, it can often lead to a decline in quality and client service.

For example, imagine that your law firm has a ‘superstar’ who is particularly skilled at tax fraud cases. If the firm gets a new tax fraud case, and your superstar is involved in another case, then chances are high that the new case will be assigned to someone who isn’t busy. Keeping everyone productive, billing their time to clients, is extremely important. But if you don’t schedule people in the right way, it can have a negative impact on client satisfaction.

The future holds even more challenges for professional services firms. Due to the impact of retiring older professionals, and an increasing number of younger professionals choosing work-life balance, firms will have to compete more to keep the best staff. Because their ‘human assets’ are limited, these firms must develop strategies to attract, motivate, and retain key talent.

Key Points

Professional services firms have many unique challenges. They must focus on creative ways to keep staff motivation and morale high, and they should develop strategies to attract – and keep – the best and brightest professionals. Without talented human capital, firms are not likely to survive in this competitive field.

Source: http://www.mindtools.com

The McKinsey Way Of Working To Solve Business Problems

In the previous article, we knew the way McKinsey thinks about business problems and uses fact-based, structured analysis and hypothesis-driven to arrive at solution for the Firm’s clients. In this part, you will see how the Firm implements its problem-solving model on a day-to-day basis. The content is divided into the following parts:

  • Selling a Study
  • Assembling a Team
  • Managing Hierarchy
  • Doing Research
  • Brainstorming

4. Selling a Study

About The Selling Process At McKinsey

The selling process at McKinsey differs from that of most organizations, because the Firm doesn’t sell. So, how to sell without selling?

Business problems are like mice. They go unnoticed until they start nibbling your cheese. Just building a better mouse trap will not make the world beat a path to your door. People who don’t have mice won’t be interested – until the mice show up; then they need to know you have the mouse trap. Sometimes the right way to sell your product or service is not to barge into your customer’s home with a bunch of free sample. Just be there, at the right time, and make sure the right people know who you are.

It may sound strange how could a company grow to the size of McKinsey without selling? But it is true. This curious aspect of McKinsey’s culture stems from the roots of the Firm’s founders. Times may have changed, but the no-selling legacy persists at McKinsey because it works very well in the consulting business. No senior McKinsey director make cold calls at the offices of Bill Gates and Ted Turner asking if they have problems they want solved. The Firm does not run ads in Forbes or Barron’s advertising 50 percent off telecommunications consulting. Actually, the Firm waits for the phone to ring.

It rings, not because McKinsey sells, but because McKinsey markets. It does this in several different ways. The Firms produces a steady stream of books and articles, some of them extremely influential. McKinsey also publishes its own scholarly journal, The McKinsey Quarterly, which it sends gratis to its clients, as well as to its former consultants, many of whom now occupy senior positions at potential clients. McKinsey maintains a vast network of informal contacts with potential clients as well. The Firm encourages its partners to participate in “extracurricular activities” such as siting on the boards of charities, museums, and cultural organizations. McKinsey consultants also address industry conferences. Occasional meetings with former clients allow partners not only to check up on the effects of past McKinsey projects, but to make sure the that the Firm maintains some “share of mind” should new problems arise at the client. The efforts could not be construed as selling, but they make sure that the right people know the Firm is there. That keeps the phones ringing.

Be Careful What You Promise: Structuring An Engagement

When structuring your project, whether you are selling your services as a consultant or have been picked by your organization to solve an internal problem, don’t bite off more than you can chew. Set definite milestones that you can meet. That way, you’ll have targets you can achieve and your clients will be satisfied.

When structuring an engagement, McKinsey faces a lot of pressure to deliver the maximum results in the minimum time. McKinsey bills by the hour, and those hours do not come cheap. A typical project contains a team of four to six consultants work together to produce tangible results in three to six months.

At an organization, McKinsey is extremely good at figuring out how much a team can do over the length of a typical study. The best EDs can balance the competing demands of clients and team to a nicety; they tell the client,” We’re going to do X and Y. We could do Z, but  it would kill the team,” while telling the team, “Look, we’re already promised the client that we would do Z, so we’ve got to deliver.” They then work the team to its limit while simultaneously making the client feel that he is getting value for money and exceeding his expectations.

What lessons does McKinsey experiece give for the way you should structure your problem-solving project? If you are a consultant putting together a proposal for an outside client, then the answer is simple” Don’t bite off more than you (or your team) can chew and know what your end products is going to be. Structuring your project properly at the beginning may not guarantee your success, but it at least gets you off to the right start.

5. Assembling A Team

At McKinsey, everything happens in teams. McKinsey relies on teams because they are the best way to solve the problems that the Firm’s clients face. More people mean more hands to gather and analyze data and, more important, more minds to figure out what the data really mean.

Getting The Mix Right

You can’t just throw four random people at a problem and expect them to solve it. Think about what sorts of skills and personalities will work best for your project. Then choose your teammates carefully.

McKinsey-ites subscribe to one of the two theories of team selection. The first theory states that intellectual horsepower is everything, then find the smartest people for your team regardless of their experience or personal hygience. The second theory says that what really matters is specific experience and skills; intelligence is a given within the Firm, every McKinsey consultant is smart or he wouldn’t be there. Neither of these theories is completely correct, but neither of them is completely wrong either. Proper team selection varies from problem to problem and client to client. Some problems will yield only to large amounts of analytical firepower.

Another important team selection lesson emerges from the McKinsey assignment process. When an engagement begins, the EM and ED pick their associates from the pool of available resources at the time. The “manager of associate development” or the office manager will tell them who is available and give them a sheet listing each associate’s experience and rating each one on analytical ability, client management skills, and so forth. The biggest mistake in team selection comes from taking those ratings at face value. A smart EM always talks to potential team members before taking them on.

By extension, if you are in a position to pick your team members before embarking on a project, never just accept people who are supposed to be good. Meet them face to face. Talk to them; see what’s behind the recommendations…Just remember, if you are lucky enough to be able to choose whom you will work with, choose wisely.

Take Your Team’s Temperature To Maintain Morale

Maintaining your team’s morale is an on-going responsibility. If you don’t do it, your team will not perform well. Make sure you know how your team feels.

What’s the secret to maintaining team morale? There isn’t one, just a few simple rules to remember.

  • Take your team’s temperature. Talk to your teammates. Make sure they are happy with what they are doing. Find out if they have questions about what they are doing or why they are doing it, and answer them. If they are unhappy, take remedial action quickly.
  • Steer a steady course. Know where you’re going and stay your course. If you need an extra day to figure it out, take it. If you need to make a big change, let your team know, explain why, and let people contribute to, or at least see your thought process.
  • Let your teammates know why they are doing what they’re doing. People want to feel that what they are doing is adding value to the client. There are few things more demoralizing than doing something that you and your team leader know is valueless.
  • Treat your teammates with respect. Respect doesn’t mean politeness. It means remembering that your teammates may have different priorities than you do, and that they have lives outside of work. Respect also means never asking someone to do something you wouldn’t do or haven’t done yourself…

6. Managing Hierarchy

Every organization has it own approach to hierarchy. Your own may look nothing at all like the Firm’s. Still, every McKinsey-ite has learned a few lessons about dealing with hierarchy that should work in any organization. They can help you stay out of trouble and get ahead.

Make Your Boss Look Good

If you make your boss look good, your boss will make you look good. That’s the quid pro quo of hierarchy. Making your boss look good means two things. Firstly, it means doing your job to the best of your ability. Clearly, if you produce high-quality work, it will make your boss’s job easier.  Second, make sure your boss knows everything you know when he/she needs to know it. Make sure your boss knows where are you, what are you doing, and what problems you may be having. At the same time, don’t overload with information. Think about what your boss needs or wants to know. Use well-structured email or voice mail to convey information.

An Aggressive Strategy For Managing Hierarchy

In a meritocratic organization at least, you can assert your equality until shown otherwise, until someone tell you ” No, you have to do what I tell you.” You’ll find it’s rare for that to happen. It sounds extreme, but in a way, to be a successful consultant, you have to assert your self. Very often, you will be in situation where you just have to assume that you can do something, or talk to someone, or get access to some bit of information, even though, you may not have the explicit authority to do so.

This is a risky strategy, and the more hierarchy an organization, the riskier it becomes. In a more rigid organization, be more sensitive of where the limits to others’ authority lie. And be ready to back down quickly; otherwise, someone will stomp on you.

7. Doing Research

The problem-solving process at the McKinsey begins with research. Before a team can construct an initial hypothesis, before it can divide a problem into its components and uncover the key drivers, it has to have information.At the start of a McKinsey-ite’s career, most of his time is spent gathering data, whether form one of the Firm’s libraries, from McKinsey’s databases, or from the internet. Gathering, filtering and analyzing data is the skill exercised most by new associates.
Here are some tips and tricks to help you to find the answer to your business problem.

Don’t Reinvent The Wheel

Maybe other people in your field, in another division or another company, have seen the same problem already. Find out who they are and get to know them. Do research and ask questions; you will save a lot of time and effort. Don’t waste your time to reinventing the wheel.

McKinsey keeps an electronic database called PDNet (Practice Development) containing reports from recent engagement and internal research. You may not have PDNet, but if you work in a large organization you probably have access to much of your company’s ” corporate memory”, databases, files, training manuals, ans coworkers. Even if you’re on your own, there is a huge stream of information out there for you to take advantage of – trade magazines, newspaper, data feeds, and the internet. How about your local library. You should find loads of information and valuable resources there with a few hours’ digging.

Get to know your competitors. Many businesspeople will share some information on the principle that “what goes around, comes around.” If you’re in, say, advertising, find the cafe in your city where other ad execs hang out. Tap into your industry’s “buzzz.”

Whatever you’re doing, chances are someone, somewhere has done something similar. Learn from others’ success and mistakes. Leverage your valuable time and don’t reinvent the wheel.

Specific Research Tips

Here is a grab bag of tips to make your research more efficient and effective.

  • Start with the annual report.
  • Look for outliers
  • Look for best practice

8. Brainstorming

McKinsey offers a new mindset, an outsider’s view that is not locked into “the company way” of doing things. That’s what clients need when problems cannot be solved within the organization, and it starts in a meeting room with a table, some chairs, a bunch of pads, pen and pencils, some markers, and a clean “white board”.

Before the first brainstorming session, McKinsey consultant do their homework. Everyone on the team reads the results of the PDNet and library searches. The associates put together and distribute “fact packs” based on their preliminary research. The ED, the EM, and possibly the more senior associates on the team come up with initial hypotheses that the team will then test to destruction.

Proper Prior Preparation

Although brainstorming has an airy-fairy, college bull session connotation to some, in reality effective brainstorming requires some hard-nosed advance work.

In A White Room

The points of brainstorming is the generation of new ideas. When you get your team into the room, leave your preconceptions at the door. Bring the facts you know, but find the new ways of looking at them.

Here are a few more “rules of the road” for successful brainstorming.

  • There is no bad ideas.
  • There is no dumb questions.
  • Know when to say when.
  • Get it down on paper.

Some Brainstorming Exercises

The key to successful brainstorming is good preparation and proper frame of mind. Here are a few tricks that McKinsey-ites use to get the maximum benefit from brainstorming session.

  • The Post-it exercise
  • The flipchart exercise
  • Bellyaches up front

Source: Ethan M. Rasiel (1999), The McKinsey Way, McGraw-Hill, The United States of America.

The McKinsey Way of Thinking About Business Problems

Foreword

Again, I am a person who has high passion on management consulting. On my own way to learn and experience, I have found and read a lot of books in this interesting area. One of those is The McKinsey Way by Ethan M. Rasiel. This book gives me a lot of practical and useful knowledge, and eventually, teaches me again how to think and solve a problem.

In the next series of articles, I am going to summarize the main points in the content of the book. This is just for personal use and definitely noncommercial. It has about three articles. The first is right after here named The McKinsey Way of Thinking About Business Problem.

McKinsey exists to solve business problems. The consultants who succeed at McKinsey love to solve problems. This article describes how McKinsey thinks about business problems. It shows what it means to be fact-based, structured, and hypothesis-driven. It will tell you the McKinsey way to approach a business problem, and offer you a few choice rules to live by when trying to solve them.The main content is divided into three parts:

  • Building the Solution
  • Developing an Approach
  • 80/20 and Other Rules to Live By

1. Building the Solution

In McKinsey, the process of solving problems has three major attributes. The solution for their client’s problem wil be:

  • Fact-based
  • Rigidly structured
  • Hypothesis-driven

Facts Are Friendly

Facts are the bricks with which you will lay a path to your solution and build pillars to support it. Don’t fear the facts.

Problem solving at the Firm begins with facts. On the first day of an engagement, all members of the team comb through stacks of articles and internal research documents to gather enough facts to illuminate their piece of the problem for the first team meeting. The team then have drawn up an initial hypothesis for the problem, and races to gather the facts necessary to support or refute it.

Facts are so important to the way McKinsey does business because of the following reasons. First, facts compensate for lack of gut instinct. And second, facts bridge the credibility gap. Despite the power of facts, many business people fear them. But, hiding from the facts is a prescription for failure, eventually, truth will out. You must not fear the facts. Hunt for them, use them, but don’t fear them.

Feel Free To Be MECE

To structure your thinking when solving business problems, you must be complete while avoiding confusion and overlap

MECE stands for “mutually exclusive, collectively exhaustive” . MECE gets pounded into every new associate’s head from the moment of entering the Firm. Every document, every presentation, every e-mail and voice mail produced by a McKinsey-ite is supposed to be MECE. MECE starts at the top level of your solutions – the list of issues making up the problem you have to solve. When you think you have determined the issues, take a hard look at them and ask:

  • Is each one a separate and distinct issues? If so, then your issue list is mutually exclusive.
  • Does every aspect of the problem come under one ( and only one) of these issues – that is, have  you thought of everything? If so, then your issues are collectively exhaustive.

A good McKinsey issue list contains neither fewer than two nor more than five top-line issues (of course, three is the best).

Solve The Business Problem At The First Meeting: The Initial Hypothesis

Solving a complex problem is like embarking on a long journey. The initial hypothesis is your problem-solving map.

The third pillar of the McKinsey problem-solving process, the Initial Hypothesis (IH) can be seen into three parts:

  • Defining the IH
  • Generating the IH
  • And, testing the IH

The essence if the initial hypothesis is ” Figure out the solution to the problem before you start”. It is like finding a way when you go to a place. Solving business problem, of course, is more complicated than finding a way to a place, but the IH works the same way. It is the road map to take you from problem to solution.

A hypothesis is merely a theory to be proved or disproved. It is not the answer. If your IH is correct, then, a few months down the road, it will be the first slide in your presentation. If it turns out to be wrong, then, by proving it wrong, you will have enough information to move toward the right answer. By that way, you have set up a road map that you can follow to an eventual proved solution.

2. Developing an Approach

Just knowing the essence of the McKinsey problem-solving process does not mean you can now go forth and conquer the business world by being fact-based, structured, and hypothesis-driven.  No two business problems are identical; you must figure out how to approach each problem in order to devise the best solution for it. Here is the way how McKinsey-ites approach a business problem and apply the Firm’s problem-solving process to maximum effect.

The Problem Is Not Always The Problem

Sometimes a business problem will land on your desk and you will be told to solve it. Fair enough. But before you go rushing off any particular direction, make sure you’re solving the right problem – it may not the one you were given.

Don’t Reinvent The Wheel

Most business problems resemble each other more than they differ. This means that with a small number of problem-solving techniques, you can answer a broad range of questions. These techniques may be somewhere in your organization, either written down or in the heads of your fellow employees. If not, use your experience to develop your own tool kit. For examples, McKinsey has developed a number of problem-solving methods and give them fancy name: Analysis of Value Added, Business Process Redesign, Product-Market Scan, etc…

But Every Client if Unique (There Is No Cookie-Cutter Solutions)

That there are many similarities between business problems does not mean that similar problems have similar solutions. You have to validate your initial hypothesis with fact-based analysis. This will put you in a much better position to get your ideas accepted.

Don’t Make The Facts Fit Your Solution

Avoid the temptation to view your initial hypothesis as the answer and the problem-solving process as an exercise in proving the IH. Keep an open and flexible mind. Don’t let a strong IH become an excuse for mental inflexiblity.

Make Sure Your Solution Fits Your Client

The most brilliant solutions, backed up by libraries of data and promising billions in extra profits, is useless if your client or business can’t implement it. Know your client. Know the organization’s strengths, weaknesses, and capabilities – what management can and cannot do. Tailor your solutions with these factors in mind.

Sometimes You Have To Let The Solution Come To You

The McKinsey rules of problem solving, like all rules, have their exceptions. You will not be able to form an IH everytime. Sometimes, the client will not know what the problem is, just that there is a problem. Other times, the scope of your project will be so large – or so vague – that starting with an IH will be worthless. Still, other times, you will be breaking new ground and nothing in your experience will point to a solution. Don’t panic! If you get your facts together and do your analyses, the solution will come to you.

Some Problems You Just Can’t Solve…Solve Them Anyway

Eventually, you will run into a brick wall that is tougher than your head. Don’t keep pounding; it has no effect on the wall and does your head no good.

3. 80/20 And Other Rules To Live By

Here are a number of rules that McKinsey consultants have found useful when trying to solve problems.

80/20

The 80/20 rule is one of the great truths of management consulting and, by extension, of business. It doesn’t always work, but if you keep your eyes peeled for examples of 80/20 in your business, you will come up with ways to improve it.

Don’t Boil The Ocean

Work smarter, not harder. There’s a lot of data out there relating to your problem, and a lot of analyses you could do. Ignore most of them. McKinsey gathers enough facts to prove or disprove a hypothesis or support or refute an analysis –  and only enough. Anything more is a waste of time and effort when both are precious commodities.

Find The Key Drivers

Many factors affect your business. Focus on the most important ones – the key drivers. It saves you time. It saves you effort. It keeps you from boil the ocean.

The Elevator Test

Know your solution so thoroughly that you can explain it clearly and precisely to your client (or customer or investor) in 30 seconds. If you can do that, then you understand what you’re doing well enough to sell your solution.

Pluck The Low-Hanging Fruit

Sometimes in the middle of the problem-solving process, opportunities arise to get an easy win, to make immediate improvements, even before the overall problem has been solved. Seize the opportunities! They create little victories for you and your team. They boost morale and give you added credibility by showing anybody who may be watching that you’re on the ball and mean business.

Make A Chart Every Day

During the problem-solving process, you learn something new every day. Put it down on paper. It will help you push your thinking. You may use it, or you may not use, but once you have written it on the page, you won’t forget it.

Hit Singles

You can’t do everything, so don’t try, Just do what you’re supposed to do and get it right. It’s much better to get to first base consistently than to try to hit a home run – and strike out 9 times out of 10.

Look At The Big Picture

Every now and then, take a mental step back from whatever you’re doing. Ask yourself some basic questions: How does what you’re doing solve the problem? How does it advance your thinking? Is it the most important thing you could be doing right now? If it’s not helping, why are you doing it?

Just Say, ” I Don’t Know”

The Firm pounds the concept of professional integrity into its associates from their first day on the job, and rightly so. One important aspect of professional integrity is honesty – with your client, your team members, and yourself. Honesty includes recognizing when you haven’t got a clue. Admitting that is a lot less costly than bluffing

Don’t Accept ” I Have No Idea”

People always have an idea if you probe just a bit. Ask a few pointed questions – you’ll be amazed at what they know. Combine that with some educated guessing, and you can be well along the road to the solution.

Source: Ethan M. Rasiel (1999), The McKinsey Way, McGraw-Hill, The United States of America.

How and Why to Be a Leader (Not a Wannabe)

We need a new generation of leaders. And we need it now.
We’re in the midst of a Great Dereliction — a historic failure of leadership, precisely when we need it most. Hence it’s difficult, looking around, to even remember what leadership is. We’re surrounded by people who are expert at winning — elections, deals, titles, bonuses, bailouts, profit. And often, we’re told: they’re the ones we should look up to — because it’s the spoils and loot that really matter.
But you know and I know: mere winners are not true leaders — not just because gaming broken systems is nothing but an empty charade of living; but because life is not a game. It isn’t about what you have, and how much — but what you do, and why — if you’re to live a life that matters.
Leadership — true leadership —is a lost art. Leaders lead us not to a place — but to a different kind of destination: to our better, truer selves. It is an act of love in the face of an uncertain world.Perhaps, then, that’s why there’s so little leadership around: because we’re afraid to even say the word love — let alone to feel it, weigh it, measure it, allow it, admit it, believe it, and so be transformed by it.

Wannabes — who I’ll contrast leaders with in this essay — are literally just that: wannabes. They want to be who leaders are, but cannot: they want the benefits of leadership, without the price; they want the respect, dignity, and title of leadership, without leading people to lives that matter; they want the love leaders earn, act by painful act, without, in return, having the courage, humility, and wisdom to love.

When you think about chiefs, presidents, and prime ministers that way, I’d suggest that most of our so-called leaders are wannabes: those who want to be seen as leaders, without leading us anywhere but into stagnation, decline, fracture, fear, apathy, and comfortable, cheap pleasures that numb us to it all. Leaders — true leaders, those worthy of the word — do the very opposite: they lead us to truth, worth, nobility, wonder, imagination, joy, heartbreak, challenge, rebellion, meaning. Through love, they lead us to lives that matter. Wannabes impoverish us. Leaders enrich us.

So here are my six ways to start being a (real) leader — and stop being just another wannabe.

Obey — or revolt? Are you responding to incentives — or reshaping them? Here’s the simplest difference between leaders and wannabes. Wannabes respond dully, predictably, neatly, to “incentives,” like good little rational robots. They do it for the money and end up stifled by the very lives they choose. Leaders play a very different role. They don’t just dully, robotically “respond” to “incentives” — their job is a tiny bit of revolution. And so they must reshape incentives, instead of merely responding to them. They have principles they hold dearer than next year’s bonus — and so they think bigger and truer than merely about what they’re “incentivized” to do. If you’re easily bought off from what you really hold dear with a slightly bigger bonus, here’s the plain fact: you’re not a true leader.

Conform — or rebel? Are you breaking the rules or following them? The rules are there for a reason: to stifle deviation, preserve the status quo, and bring the outliers right back down to the average. That’s a wonderful idea if you’re running a factory churning out widgets — but it’s a terrible notion if you’re trying to do anything else. And so leaders must shatter the status quo by breaking the rules, leading by example, so that followers know the rules not just can, but must be broken. If you’re nail-bitingly following the rules, here’s the score: you’re not a true leader.

Value — or values? Why do people follow true leaders? Because leaders promise to take them on worthwhile journeys. The wannabe creates “value” for shareholders, for clients, for “consumers”. But the leader creates what’s more true, more enduring, more resonant: lives of real human worth. And they must do so by evoking in people values that matter, not merely “value” which is worthless. Which would you choose? In a heartbeat, most people choose the latter, because value without values is what reality TV is to a great book: empty, vacant, narrow, arid. If you’re creating value — without setting values — you’re not a leader: you’re just a wannabe.

Vision — or truth? The wannabe sets a vision. With grandiloquent gesture and magnificent panorama, the vision glitters. The leader has a harder task: to tell the truth, as plain as day, as obvious as dawn, as sure as sunrise, as inescapable as midnight. Vision is nice, and many think that a Grand Vision is what inspires people. They’re wrong. If you really want to inspire people, tell them the truth: there’s nothing that sets people free like the truth. The leader tells the truth because his fundamental task is that of elevation: to bring forth in people their better selves. And while we can climb towards a Grand Vision, it’s also true that the very act of perpetually climbing may be what imprisons us in lives we don’t really want (hi, Madison Ave, Wall St, and Silicon Valley). Truth is what elevates us; what opens us up to possibility; what produces in us the sense that we must become who were meant to be if we are to live worthy lives — and one of the surest tests of whether you’re a true leader is whether you’re merely (yawn, shrug, eyeroll) slickly selling a Grand Vision, or, instead, helping bring people a little closer to the truth. And if you have to ask what “truth” is (newsflash: climate change is real, the global economy is still borked, greed isn’t good, bankers shouldn’t earn a billion times what teachers do, CEOs shouldn’t get private jets for life for running companies into the ground, the sky really is blue) — guess what? You’re definitely not a leader.

Archery — or architecture? Wannabes are something like metric-maximizing robots. Given a set of numbers they must “hit,” they beaver away trying to hit them. The leader knows their job is very different: not merely to maximize existing metrics, which are often part of the problem (hi, GDP, shareholder value), but to reimagine them. The leader’s job is, fundamentally, not merely to “hit a target” — but to redesign the playing field. It’s architecture, not mere archery. If you’re hitting a target, you’re not a leader. You’re just another performer, in an increasingly meaningless game.

love — or Love. Many of us, it’s true, choose jobs we “love” over those we don’t, readily sacrificing a few bucks here and there in the process. But this isn’t love as much as it is enjoyment. Love — true love, the real thing, big-L Love — is every bit as much painful as it is pleasant. It transforms us. And that is the surest hallmark of a true leader. They have a thirst not merely for love — but to love; a thirst that cannot be slaked merely through accomplishments, prizes, or honors. It can only, only be slaked through transformation; and that is why true leaders must, despite the price, through the pain, into the heart of very heartbreak itself, lead.

And yet.

We’re afraid, you and I, of this word: love. Afraid of love because love is the most dangerously explosive substance the world has ever known, will ever know, and can ever know. Love is what frees the enslaved and enslaves the free. Because love, finally, is all: all we have, when we face our final moments, and come to know that life, at last, must have been greater than us if we are to feel as if it has mattered.

The old men say: children, you must never, ever believe in love. Love is heresy. Believe in our machines. Believe in operation and calculation. Place your faith in being their instruments. Our perfect machines will bring you perfection.

I believe lives as cold as steel will only yield a world as cruel as ice. I believe cool rationality and perfect calculation can take us only a tiny distance towards the heart of what is good, true, and timelessly noble about life. Because there is no calculus of love. There is no equation for greatness. There is no algorithm for imagination, virtue, and purpose.

Even a perfect machine is just a machine.

If we are to lead one another, we will need the heresy of love. We must shout at yesterday in the language of love if we are to lead one another. Not just to tomorrow, but to a worthier destination: that which we find in one another.

It’s often said that leaders “inspire”. But that’s only half the story. Leaders inspire us because they bring out the best in us. They evoke in us our fuller, better, truer, nobler selves. And that is why we love them — not merely because they paint portraits of a better lives, but because they impel us to be the creators of our own.

Source: This article was originally published by Harvard Business Review by Umair Haque.

About the author: Umair Haque is a London-based consultant, author, and economist.  He is also a contributor at the Harvard Business Review, where he focuses on capitalism and creating prosperity in the 21st century (wikipedia). He is now the Director of Havas Media Labs and author of Betterness: Economics for Humans and The New Capitalist Manifesto: Building a Disruptively Better Business. He is ranked one of the world’s most influential management thinkers by Thinkers50.

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