Chinese version: http://jasmine-action.blogspot.com/2016/12/blog-post_16.html
"BigBoss" is a project management tool which can applied to managing team works in any organization, such as a firm, a government agency, as well as troops, etc. In average, it can improve team work efficiency by 20%.
If a firm or a government agency applies "BigBoss" to manage its teams, projects, and even its employee's salaries, it can improve its revenue or save its cost by 20%!
If Donald Trump applies "BigBoss" to manage the US government, he might increase the GDP of the United States by several points.
BigBoss is a great gift to President-elect Donald Trump, and to any other big bosses in the world.
Here we give a brief introduction and list some dummy examples to show how to apply BigBoss to manage team works. Note that all the data and names in the examples cases are dummies. if you like, you can just change the names or data into any other things.
Definitions
BigBoss: a software tool that manages teams working on a project.
Project: all the tasks that the team works on. A project is divided into M products, where M is an integer greater than 1.
Product: a task or job contains in the project.e For example, if the project is making cars, a product could be making part of the car, such as tires, engines, etc. If the project is developing a software tool, it may contains product to develop Java programming, to develop webs, to design database, etc.
Demand of a product: the amount needed of the specified product.
Production space: there exists M products, thus there are M demands. These M demands composed a vector of an M-dimensional Euclidean space, which is called production space.
Demand vector: the M-dimensional vector in the production space. Sometimes it will be simply called Demand.
Price vector: an M-dimensional vector with its kth component indicating the market price of the kth product.
Intrinsic Price vector: an M-dimensional vector with its kth component indicating the intrinsic price of the kth product.
Intrinsic Price: a price calculated by BigBoss. Intrinsic prices are completely determined by the capability matrix and the demand vector. If each product is sells at its intrinsic price, each producer will get maximum possible salary.
Steps for using BigBoss
Step 1. Input Data: Data needed for BigBoss to calculate the optimal management solution. Input data includes two parts: project information and capability matrix.Project information: Generic information of the project as shown in Fig. 1-1.
Fig. 1-1：Input page for project information. The right side of the table need to be provided by user.
Fig. 1-2：Input page for project information with example data filled in. Once the above table is filled with your project data, click on the "submit" button.
Project Name: the name you want to given to your project.
Objective: a drop-down menu in which you can choose among 3 options: Max Production, Fast Delivery, and Max Revenue. BigBoss applies different models for each objective type.
The "Max Production" model tries to maximize the Supply Vector which meets the requested demand vector.
The "Fast Delivery" model tries to minimize the delivery time ratio for products once the requested delivery time is given for each product.
The "Max Revenue" model tries to maximize the total revenue of the project once the market price vector is given.
Producer Count: Also called "Member Count", which is the number of producers in the team.
Product Count: the number of products in the project.
Budget: The total budget that will be distributed as salary to the producers who will work on this project.
Time Unit: a drop-down menu in which you can choose among some time units, such as Hour, Day, Week, Month, Quarter, Year.
Fig. 1-3. Capability input page.
Fig. 1-4. Capability input page with example data filled in. Then click on the "calculate" button.
Step 2. View Optimal Solution
BigBoss calculates the optimal solution for your project with the data you provided. The optimal solution will be listed in 3 type of tables: Time sheet, Task sheet, and Amount sheet.
Fig. 1-5. Time sheet. This sheet shows the time percentage of each producer working on a product. For example, Xi Jinping should spend 8% of his time to work on wrapper, and spend 92% of his time on wrap up buns, whereas Peng Liyuan and Xi Mingze spend all their times on wrappers.
The last row lists the intrinsic prices calculated by BigBoss.
The row headed by "Optimal delivery time" is the time that the team produce the product with the demand amount.
The row headed by "Budget distribution" is simply the intrinsic price times the demand amount.
The row headed by "Unit time revenue" is the intrinsic price times the demand amount and divided by the optimal delivery time.
The "Demand amount" is simply the demand amount which provided in the input step. It was listed here so that you can compare it with the optimal supply amount.
The last two columns are "Reasonable Salary" for each producer. The Reasonable Salaries are calculated as the sum product of the intrinsic price and the actual product amount produced by a producer.
Fig. 1-6. Task sheet. This sheet shows the percentage of each demand produced by a producer. For example, product "Wrap up" are 100% done by Xi Jinping, while the demand amount of the product "Wrapper" are distributed among the 3 producers with percentage 2.17%, 43.48%, 54.35% correspondingly. All other parts are the same as that in Time sheet.
Fig. 1-7. Amount sheet. This sheet shows the supply amount of each producer made in unit time.
Step 3. Compare the optimal solution with user specified solution
BigBoss also provide a page that can validate the BigBoss solution is optimal for your project. You can provide your solution and then compare it with the BigBoss solution. You can find that the BigBoss solution is always better than your solution, normally will be 20% more efficient than your solution in average.
Example 1：Manage Housework
Our first example shows how to manage housework at home, such as making buns or dumplings.
Bun and dumplings are special Chinese foods for Chinese families during Spring festival. Even the Chinese President Xi Jinping likes buns and enjoys to make buns at home.
Xi Jinping enjoys to making buns.
The processes of making buns can be split into two: "making wrappers" and "wrap up". To make it more efficiency and more fun, Chinese families normally have family members work as a team to make buns.
Lets take Xi Jinping's family as example to show how to apply BigBoss to manage housework. Xi's family has three members and each of them has various capabilities on the two processes as shown in Fig. 1-4. The BigBoss gives optimal solution as shown in Fig. 1-5 to Fig. 1-7.
Fig. 1-4 shows that Xi Jinping should spend 8% of his time on making wrapper and 92% of his time on wrapping up buns, while Peng Liyuan and Xi Mingze should spend 100% of their time on making wrappers. With this type of job assignments, Xi's family can make 184 buns in unit time (i.e., hourly here). Any other arrangements will make less buns.
BigBoss not only gives the optimal job assignments, but also gives intrinsic price, with which each producer will get his or her maximum salary. In other words, if each product has a price as the intrinsic price and each producer tried to get maximum income, then each producer will try to reach the optimal job assignment as given by the BigBoss. So, the intrinsic price is a reasonable price within Xi's family.
Given the intrinsic price and the optimal job arrangements, BigBoss can further calculate the reasonable salary for each producer. In this case, Xi Jinping should get $0.22 for making one bun or $40 per hour, Peng Liyuan should get $0.35 for making one bun or $64 per hour, whereas $0.43 for making one bun or $80 per hour. The daughter get the highest pay rate.
There might exist the same products in the market and the products may have their market prices which might be different from the intrinsic. In that case, the intrinsic price will be an important economic parameter which can help making business strategies. For example, the intrinsic price for one wrapper is calculated as $0.8. Assume the market price of bun wrapper is $0.5, and the materials(here mainly flour) of making one wrapper cost $0.1. Then cost for Xi's family to make one wrapper is $0.9, which is higher than the market price. That tells us that Xi's family can't get profit from making wrapper of buns.
To show how the intrinsic price depends on capability matrix, lets assume the capability matrix changes to the value as shown in Fig. 1-3a.
Fig. 1-4a. Capability matrix of Xi's family in making buns. The capability is slightly different from Fig. 1-4.
Fig. 1-5a. Time sheet. Optimal Time Assignment Sheet calculated by BigBoss using data in Fig. 1-5a. as input.
Fig. 1-6a. Task sheet.
Fig. 1-7a. Supply Amount(in unit time) sheet.
Once the capability matrix changes from Fig. 1-3 to Fig. 1-3a, the amount of buns made by Xi's family reduced from 184 to 133. The intrinsic price of wrapper changed from $0.8 to $0.4705. Xi Jinping changed from the lowest pay rate to the highest.
Example 2：Manage Cabinet
BigBoss can be applied to manage a team as small as a family, but also as big as a government.
China's government is mainly controlled by the so called Politburo Standing Committee of the CCP (PSCCCP). PSCCCP plays most of the roles of a cabinet in other countries. Lets take PSCCCP as example to show how to apply BigBoss to manage a cabinet.
PSCCCP has 7 members and Xi Jinping plays the role of its boss. In recent years, the most important job of the PSCCCP concentrated on is anti-corruption. Lets assume Xi Jinping wants to investigate some corrupted top rank officials, and Xi Jinping already had a list of such potential targets. Now, Xi Jinping wants to assign each of his PSCCCP member to take in charge of some cases. How should Xi Jinping assign cases among his PSCCCP members? Here are his choices:
1. Just assign the jobs randomly among the PSCCCP members. That may not be efficient, some cases might be finished quickly, while some other case may take long time.
2. Let the members to select the cases. This may not work out, since everyone wants to take the easy case and no one wants to do the tuff cases. It could also results conflicts among the PSCCCP members.
This is always a headache problem. BigBoss can solve the problem easily and gives the optimal solution as shown in the following figures.
Fig. 2-1. Project information of Xi Jinping's PSCCCP.
Fig. 2-2. Capability data of Xi Jinping's PSCCCP.
Fig. 2-3. Time sheet. Optimal job assignment solution for Xi Jinping's PSCCCP.
Fig. 2-4. Task sheet. Optimal job assignment solution for Xi Jinping's PSCCCP.
Fig. 2-5. Supply amount sheet. Optimal job assignment solution for Xi Jinping's PSCCCP.
Once Xi Jinping provides the input data as shown in Fig. 2-1 and Fig. 2-2, the BigBoss will solve all the problems including:
1. Who should do what?
2. How much time should each of his members to spend on each job?
3. How much should be paid for each of his members?
4. What is the cost on each case?
That is pretty much what Xi Jinping needs to be done to manage this project and get the best output.
Example 3. Manage Court
One of the most important management works in a Court is assigning cases among Judges. BigBoss can be applied to this type case assignment problems. In Example 1, just treat each of the PSCCCP member as a judge, and the corrupted Chinese officials as a case name to be tried by the court, then Fig. 2-1 to Fig. 2-5 will give a concrete example of BigBoss for case assignment in a court.
Example 4. Manage Government Agencies
Similar to the Court, case assignment is also one of the most important management work in some government agencies. For example, FBI, CIA, Police Bureau, Department of Homeland Security, etc. all have detectives. Their employee's major jobs are working on some cases. BigBoss can be applied to this kind government agencies and provide the optimal solution for case assignment problems. In Example 1, just treat each of the PSCCCP member as a team member in such kind government agencies, then Fig. 2-1 to Fig. 2-5 can be considered an application example of BigBoss in Government agencies.
Example 5. Manage Law Firms
A law firm normally has many lawyers and each of them may work on various cases. BigBoss can be applied to give optimal solution for case assignment problems in a law firm.
Example 6. Manage Warfare
BigBoss can also be applied in military, such as managing troops, warfare, etc. Now lets apply BigBoss to manage anti-terrorist warfare.
President Bush used to list some terrorist group as Axis of evil or terror states, such as Iraq, North Korea, Taliban，Al-Qaeda, Hezbollah, and Cuba.
Assume President Bush started anti-terrorist war against the above mentioned Axis of evils and see what BigBoss can help in this war.
Normally, modern warfare starts with bombard first, whereas bombard can have various types, such as Tomahawk Missiles, B-52 Bomber, cruiser fire, rocket launcher, Navy seals, etc.. Each type of bombard method may have various efficiency or capability on various targets. How should President Bush or his Generals assign bombard weapons on these targets?
BigBoss can be applied to provide the optimal solution for such kind "weapon assignments", as shown in the following figures.
Fig. 6-1. Anti-terrorist warfare information.
Fig. 6-2. Capability data of Bombard weapons.
Here capability represents the number of HQs can be destroyed by that bombard method in unit time if all that type weapons launched to the target. For example, Tomahawk Missiles can destroy 0.5 Al-Qaeda head quarter in a month. HQ stands for terrorist head quarter.
Based on the above capability data, BigBoss gives the following optimal solution for weapon assignments.
Fig. 6-3. Time sheet. Optimal bombard weapon assignment solution for anti-terrorist warfare.
Fig. 6-4. Task sheet. Optimal bombard weapon assignment solution for anti-terrorist warfare.
Fig. 6-5. Supply amount sheet. Optimal bombard weapon assignment solution for anti-terrorist warfare.
The BigBoss optimal solution tells that 41.86% of B-52 Bomber should be targeting at Hezbollah, and 58.14% of of B-52 Bomber should be targeting at Cuba HQ. With the BigBoss optimal solution, the bombard process can be finished in about 20 days (0.6515 month), which is 10 days ahead of the requested deadline.
Example 7. Manage Transportation
We continue the above example. Once the bombard process successfully finished, the war may continue with ground war. To start ground war, it might be necessary to send troops to the targets. BigBoss can also be applied in transportation management, such as troop transportation.
Suppose there are 3 transportation methods for sending troops to the in the requested number of troops to be sent to the terror states: Air various targets as shown in the following tables.
Fig. 7-1. Troop transportation information.
Fig. 7-2. Transportation capability data for sending troops to evil states.
Fig. 7-3. Time sheet. Optimal transportation assignment solution for sending troops to evil states.
Fig. 7-4. Task sheet. Optimal transportation assignment solution for sending troops to evil states.
Fig. 7-5. Supply amount sheet. Optimal transportation assignment solution for sending troops to evil states.
With the transportation capability as shown in Fig. 7-2., BigBoss gives optimal solution for sending troops to the evil states as shown in Fig. 7-3 to Fig. 7-5, which can transport requested number of troops to the targets in 4 weeks, right on schedule for this case.
8. Manage Trump's Projects
Mr. Donald Trump was elected the President of the United States. Mr. Donald Trump is not only a politician, but also a successful business man. He might have many projects to be managed. This example shows how to manage Mr. Trump's projects.
Assume that Mr. Trump had a plan to renovate some of the his Trump Tower. He planed to have each of his family members to take in charge some of the renovation projects and he gave 60 days deadline to finish each of the renovation. Here are the assumed project data for Trump Tower renovation.
Fig. 8-1. Trump Tower renovation project information.
Fig. 8-2. Capability data for Trump Tower renovation project.
Fig. 8-3. Time sheet. Optimal job assignment solution for Trump Tower renovation project.
Fig. 8-4. Task sheet. Optimal job assignment solution for Trump Tower renovation project.
Fig. 8-5. Supply amount sheet. Optimal job assignment solution for Trump Tower renovation project.
With the capability data given as in Fig. 8-2., BigBoss gives optimal solution for Trump Tower renovation project as shown in Fig. 8-3, which shows that the optimal delivery time is 66 days, which is 6 days delayed. In order to finish this project within the requested deadline, one choice is to outsource one of the renovation to external teams. It would be better to cut one of the renovation with the highest cost(or intrinsic price), which is the renovation of the Trump Tower in Toronto.
With the renovation of the Trump Tower in Toronto cut off, BigBoss get the following optimal solution.
Fig. 8-3a. Optimal job assignment solution for Trump Tower renovation project with Trump Tower in Atlantic excluded.
With the new plan, all the listed 7 Trump's Towers can be renovated in 54.7 days, which is 5 days ahead of the requested 60 days deadline.
9. Manage High Technology teams
BigBoss can be used to manage high technology teams, such as software developer teams.
Most people use computer on daily basis, and most companies may have software developer teams or computer support teams. This example shows how to apply BigBoss to manage as software developer team.
Assume Bill Gates plans to develop a new Windows operation system, and given the name Windows888. An operation system is a complicated software and needs many software programmers to work as a team to develop it. It may need Computer Architectures to do the high level design, Java programmers to do GUI or user interface, C++(Cpp) programmers to do the back-end calculations, Database Administrators(DBA) to maintain database, testers to test the software, etc. Lets further assume that Bill Gates plans to split the Windows888 project among his teams in various locations, including Beijing, Mumbai, Seattle, New York, London, and Tokyo. The following two tables list the assumed project information data and the capability data for Windows888 project.
Fig. 9-1. Windows888 project information.
Fig. 9-2. Capability data for Windows888 project.
Fig. 9-3. Time sheet. Optimal job assignment solution for Trump Tower renovation project.
Fig. 9-4. Task sheet. Optimal job assignment solution for Trump Tower renovation project.
Fig. 9-5. Supply amount sheet. Optimal job assignment solution for Trump Tower renovation project.
The optimal job assignment solution will have the Windows888 project finished in 8.46 months, which is 3.54 months ahead of the requested deadline. It also shows that the Mumbai team get 19.68% of the planed budget, which is the highest.
Estimate the Possible Improve Efficiency by BigBoss
The improved efficiency of BigBoss solution is mainly come from the collaboration among team members.
Lets use making bun example to explain the collaboration efficiency in more detail. To make things simplified, lets assume the team just has two members: Xi Jinping and Peng Liyuan. And assume the capability matrix as shown in the following table.
Fig. 10-1. Capability data of the Xi's couple in making buns.
The capability data shown in Fig. 10-1 defined the Maximum Production Frontier(MPF) for each of the member. To distinguish the MPF of a team member from the MPF of the whole team, let's call the former as micro-MPF and the later as the macro-Frontier.
Fig. 10-2. The micro-Frontiers are flat curves, instead of convex curves.
All the points below the MPF composed a region called Feasible Production Region (FPR), as shown in the highlighted region.
Without collaboration, Xi Jinping can managed himself to produce 33.33 buns in unit time, and Peng Liyuan can managed herself to produce the same amount in this case. In total, Xi Jinping and Peng Liyuan can make 66.66 buns in unit time, which corresponds point U.
Once they worked as a team, the team will have a macro-MPF and a macro-FPR, as shown in the following figure.
Fig. 10-3. Once Xi Jinping and Peng Liyuan work as a team, the team has the blue curve XAY as its macro-MPF, and all the highlighted region OXAYO as its macro-FPR.
Any point in the FPR represents a feasible status for the team, while any point outside the FPR are infeasible. Then, for any point inside the FPR, say U, we can always find a point on the MPF, say A, which has all production amounts enlarged by the same ratio. We can say point A is always more efficient than point U.
Collaboration can, but not necessarily improve efficiency. For example, if the team manager manages Peng Liyuan to make wrapper and Xi Jinping to wrap up buns, then the team production status reaches point B and makes 50 buns, which makes the efficiency worse by 25% than point U. However, if the manager manages the other way, the team production status reaches point A and makes 100 buns, which improve the efficiency by 50% than point U.
The optimal solution is defined as the point meets the following requirements:
1. On the macro-MPF.
2. Each producer get the maximum possible income.
3. Supply-demand equilibrium, i.e. the supply vector is the same to the demand vector.
In Fig. 10-3, point A is the optimal solution point.
BigBoss tries to find the optimal solution point. It is always improve efficiency compared with any other points.
Lets estimate the the improved efficiency by BigBoss. As shown in Fig. 10-3, BigBoss reaches point A, which is on macro-MPF. The macro-MPF can be approximated by an M-dimensional ellipsoid in the following format:
where r is a real number, S represents a point in M-dimensional space, C represents the macro capability vector. It becomes M-dimensional hyperplane, as the yellow curve shown in Fig. 10-3. It will be a convex curve if r > 1 and a concave curve if r < 1.
In most cases r = 2 is a good approximation for macro-MPF. For simplicity, we choose r = 2.
If each of the producers has reached his micro-MPF, then the macro supply vector S would be in the region BXAYB. If the team has a good manager, S could be in the region CXAYC. In average, a good manager could manage his team to reach point D, which is the average of C and A. By comparing the production amount of the point A with point B, the improved efficiency by BigBoss can be estimated as:
The above function can be listed as a table as:
Fig. 10-4. The estimated improved efficiency (E) by BigBoss varies with the number of products(M).
Based on the above estimations, we can say that BigBoss can improve efficiency by 20% in average.
Limitations of the BigBoss
The above examples show that BigBoss applicable to manage team working on multiple products or jobs, and can improve efficiency for most of the cases. However, BigBoss is also have limitations. BigBoss may not improve efficiency for the following cases:
1. The team has only one member, then there is no collaboration and no room for BigBoss to improve efficiency.
2. The team works on only one job or task, then all members have to work on the same job and there are no other solutions to improve efficiency.
3. All team members have the same capability except by a scale, for example, team member 1 has capability on job 1 as 3, on job 2 as 5, while all other team members have the same capability time by a constant. Then, the maximum production frontier will be a flat plane instead of a convex polyhedron.
Capability data are required input for BigBoss. So, to make the BigBoss applicable, the capability for each team member working on each product has to be predictable，stable，and measurable in numbers. Otherwise, BigBoss is not applicable. For example, a soccer player, such as Diego Maradona, capability or performance is not predictable, the number of goals he can score in a game not only depends on his skills, but also depends on many other factors, such as the weather, fortunate, or even depends on the hand of the God. So, BigGame is not applicable to teams in games, sports, elections, etc..
Contact us
For those who are interested in BigBoss, please send email to:
Email: gang.liu.1989@gmail.com
Gang Liu
December 20, 2016
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