Best Practices of Microsoft


Microsoft Chairman Bill Gates has credited his best practices or new rules of how to function in the new digital business infrastructure. They can be applied in other businesses. The rules include:

  1. Insist that communications flow through email
  2. Study sales data online to share insights easily
  3. Shift knowledge workers into high level thinking
  4. Use digital tools to create virtual teams
  5. Convert every paper process to  digital process
  6. Use digital tools to eliminate single-task jobs
  7. Create a digital feedback loop
  8. Use digital systems to route customer complaints immediately
  9. Use digital communication to redefine boundaries
  10. Transform every business process into just-in-time delivery
  11. Use digital delivery to eliminate middlemen
  12. Use digital tools to help customers solve problems for themselves.

My Consultancy–Asif J. Mir – Management Consultant–transforms organizations where people have the freedom to be creative, a place that brings out the best in everybody–an open, fair place where people have a sense that what they do matters. For details please visit www.asifjmir.com, and my Lectures.

Managerial Accounting


Managerial accounting refers to the internal use of accounting statements by managers in planning and directing the organization’s activities. Perhaps management’s greatest single concern is cash flow, the movement of money through an organization over a daily, weekly, monthly, or yearly basis. Obviously, for any business to succeed, it needs to generate enough cash to pay its bills as they fall due. However, it is not at all unusual for highly successful and rapidly growing companies to struggle to make payments to employees, suppliers, and lenders because of an adequate cash flow. One common reason for a so-called “cash crunch” or short fall is poor managerial planning.

Managerial accounting is the backbone of an organization’s budget, an internal financial plan that forecasts expenses and income over a set period of time. It is not unusual for an organization to prepare separate daily, weekly, monthly, and yearly budgets. Think of a budget as a financial map, showing how the company expects to move from Point A to Point B over a specific period of time. While most companies prepare master budgets for the entire firm, many also prepare budgets for smaller segments of the organization such as divisions, departments, product lines, or projects. “Top-down” master budgets begin at the top and filter down to the individual department level, while “bottom-up” budgets start at the departments or project level and are combined at the chief executive’s office. Generally, the larger and more rapidly growing an organization, the greater will be the likelihood that it will build its master budget from the ground up.

Regardless of focus, the major value of a budget lies in its breakdown of cash inflows and outflows. Expected operating expenses (cash outflows such as wages, materials costs, and taxes) and operating revenues (cash inflows in the form of payments from customers and stock sales) over a set period of time are carefully forecast and subsequently compared with actual results. Deviations between the two serve as a “trip wire” or “feedback loop” to launch more detailed financial analysis in an effort to pinpoint trouble spots and opportunities.

My Consultancy–Asif J. Mir – Management Consultant–transforms organizations where people have the freedom to be creative, a place that brings out the best in everybody–an open, fair place where people have a sense that what they do matters. For details please visit www.asifjmir.com, and my Lectures.

Knowledge Engineering


In the traditional approach to systems design, a system analyst, together with the ultimate end-users, or clients, for the project, will complete a functional specification of the system. At that point, the project is essentially in the hands of professional project management and programming staff, because that group possesses the knowledge and skill required to deliver the agreed upon features and functions. In the development of knowledge systems, this is simply not the case. Following the specification of function, a new problem arises. This is because it is not an algorithm that is being developed but knowledge that is being encoded for machine use.

 

The immediate problem is that traditional applications developers do not have sufficient knowledge of the applications area to complete the project from the starting point of a functional specification. This information generally exists in a variety of forms, depending on the application area. In some cases an individual or group of individuals may uniquely possess the relevant knowledge. In other cases, the knowledge may exist in the form of published materials like manuals or textbooks. In still other cases, the knowledge does not presently exist at all, and must be created and developed along with the system itself. This is an extremely difficult circumstance. Further compounding this problem is a critical factor: Regardless of the form in which the knowledge currently exists, it is not in a form that is ready for use by a knowledge system. Someone must decide what knowledge is relevant and desirable for inclusion, acquire the knowledge, and represent it in a form suitable for a knowledge system to apply. In all but trivial applications the task of representing the knowledge requires not only coding individual “chunks” of knowledge, but also organizing and structuring these individual components.

 

Historically, owing to the remoteness and enigmatic quality of artificial intelligence technologies, the person doing the actual systems development and the “expert,” or source of knowledge, were not the same. The availability of tools, in place of enigmatic technologies, has had an impact on reducing this problem. Even if one can imagine the case in which the “expert” whose knowledge is to be modeled is also an “expert” with the use of artificial intelligence development tools, there still remains a sizable problem.

 

In case where knowledge resides with some practitioner or expert, it does not exist explicitly as a series of IF …THEN rules, ready to be encoded. Most practitioners and experts find it difficult to explain explicitly what they are doing while solving problems. They are not cognizant of the underlying rules they are applying. Their expertise has been developed from numerous experiences and involves highly developed pattern recognition skills and heuristics.

 

In the case where the knowledge to be included is contained in text material like manuals, regulations, procedures, and the like, the information is still not in a form ready for inclusion in an expert system. It must be remembered that one of the most often cited advantages of expert systems is that they make explicit the knowledge that is most often implicit and unavailable for review, evaluation, dissemination, and modification. The task of making knowledge both explicit and available for systems application is that of knowledge engineering. Most literature on the development and application of knowledge systems has identified the need for individuals skilled in knowledge engineering as a critical factor to widespread use of technology.

 

Knowledge engineering involves acquiring, representing, and coding knowledge. The representation and coding aspects of systems development have been greatly impacted by these newly available tools. The speed with which prototyping can be accomplished has also helped reduce some of the difficulty in acquiring or refining knowledge. The knowledge engineer now finds it much less costly in time and effort to represent, code, and test early approaches to systems development, providing a more efficient feedback loop. This feedback loop is critical in the development of knowledge systems. The end-user/client for the project is, by nature, going to be much more involved in the systems design process. The “programmer” often is incapable of deciding if the system is behaving properly, owing to a lack of fundamental knowledge about the application area. This is simply not as strong a factor, where the programmer is capable of evaluating the accuracy and efficiency of algorithms. When the product is actionable knowledge rather than algorithms, the ability to evaluate project progress shifts to the end-user/client. This creates the increased emphasis on the feedback loop.

 

My Consultancy–Asif J. Mir – Management Consultant–transforms organizations where people have the freedom to be creative, a place that brings out the best in everybody–an open, fair place where people have a sense that what they do matters. For details please visit www.asifjmir.com, Line of Sight

Closed-loop Teams


For years, banks have taken several days, and even weeks and sometimes months to get a decision to a personal loan applicant. The application would be passed around the various departments, traveling at its own pace. A series of supervisors, clerks, and internal mailpeople handled it. Today, aggressive banks take the application directly into a focused, coordinated group—a credit analyst, a collateral appraiser, and a senior personal banker—who decide and respond to the customer sometimes in thirty minutes and always inside a day. This is a small closed-loop team.

 

A closed-loop team includes everyone who is necessary to make the deliverable flow. The team includes all the needed functional people and decision-makers and is self-scheduling. Everyone the team is working for the same objective—to provide the deliverable on time. The team is empowered to make decisions and to act. It has all functions inside it with short lines of communication. Its leader is responsible for its overall performance and for seeing that it gets all the capability, both technicall and human, it needs. All of these are essential to flexibility.

 

The old bank loan approval process was open loop. There was no continuity in the process, no visible standard, little learning between the principles, only occasional feedback on the process, and no one responsible for making it better.

 

In order for the loop to close on a process it must be tightly organized around the deliverable; the same core group must be involved in the process every day; and there must be a working leader on the team.

 

Small teams work better than large ones because large groups create communication problems of their own. It’s best to include only essential functions and to exclude people whose job is peripheral to the deliverable. For example, the bank loan team excludes accounting and records people. Teams have to be self-managing and empowered to act because referring decisions back up the line wastes time and often leads to poor decisions. So the team ioncludes a bank officer because if the officer were not on the team, he or she would be prone to second-guess the group’s decisions. Its better if all the questions are asked and answers are exchanged just once.

 

Closd-loop teams handle variety better than open-loop teams because they can create new information and flexibility.

 

My Consultancy–Asif J. Mir – Management Consultant–transforms organizations where people have the freedom to be creative, a place that brings out the best in everybody–an open, fair place where people have a sense that what they do matters. For details please visit www.asifjmir.com, Line of Sight