1. Field of the Invention
The present invention generally relates to a methodology of determining optimal targets for goals of an organization. In an exemplary embodiment, a computer tool allows the user to determine optimal target revenues for a business entity.
2. Description of the Related Art
Strategic planning is fundamentally important to any business entity. Its impact is pervasive throughout the organization as a key driver of financial success. One of the critical steps in strategic planning is determining revenue targets for different products/services, offered by the business entity, revenue targets for different organizations within the entity, and even structure of the organizations within the entity relative to strategic planning. So far, no formal methodologies exist to support or optimize strategic planning, particularly for the end results of an entity, such as determining an optimal revenue target for the entity.
The present inventors have recognized this problem and have developed a tool and method that can be used to optimize strategic planning for an organization, such as determining an optimal revenue target.
Although the following discussion is exemplarily oriented toward the goal of determining optimal revenue targets for a business entity, the concepts and the tool can be used for determining other types of goals and for other types of organizations, including, as nonlimiting examples, such entities as nonprofit organizations, government agencies, social organizations, and so on.
In view of the foregoing, and other, exemplary problems, drawbacks, and disadvantages of the conventional systems, it is an exemplary feature of the present invention to provide a structure (and method) in which optimal targets are calculated for a different subcomponents of an organizational entity, given an overall target for the organization to achieve, a variety of quantifiable resources available, and one or more quantifiable demands.
It is another exemplary feature of the present invention to provide a tool to allow an organizational entity to calculate an overall target for the organization, as based upon such inputs as market conditions, business environment, best practices of competitors.
It is another exemplary feature of the present invention to provide a structure and method for, in one exemplary embodiment, calculating optimal revenue targets for different sectors of an organization, given an overall organizational revenue target and the resources and demands for that organization.
It is another exemplary feature of the present invention to provide a tool and method that can be used recursively, so that each subcomponent or sector of that organization can then calculate its own optimal revenue targets.
It is another exemplary feature of the present invention to provide a tool and method that can be used to calculate optimal revenue targets for an organization for a distant point in time by successively calculating optimal revenue targets for a sequence of business cycles.
It is another exemplary feature of the present invention to provide a tool and method that can similarly calculate optimal targets for any desired measurable result of an organization, given an overall organization target and a description of resources and demands.
It is another exemplary feature of the present invention to provide a tool and method that can calculate optimal targets for different offerings of an organization.
It is yet another exemplary feature of the present invention to allow an organization to determine an optimal mix of offerings, given one or more potential new offerings.
Therefore, in a first exemplary aspect, the present invention discloses a computerized organization optimization tool, including an input port to receive one or more of: characteristics of at least one offering of the organization; characteristics of resources of the organization; and characteristics of constraints of at least one of the resources and the at least one offering; and a calculator receiving the characteristics to calculate one or more optimal targets for the organization.
In a second exemplary aspect, the present invention also discloses a method of managing a portfolio of offerings/organizations, including: identifying a business opportunity; evaluating each business opportunity with respect to one or more business objectives; evaluating minimum business requirements for including the business opportunity into a business portfolio; and combining the business opportunity into an optimal portfolio, based upon the evaluating minimum business requirements, wherein the business opportunity comprises one or more of a product, a service offering, a line of business, and an organization.
In a third exemplary aspect, the present invention also discloses a method for determining an optimal revenue target for each offering or organization of a business entity based on business objectives and constraints, including defining one or more of: characteristics of at least one offering of the business entity; characteristics of resources of the business entity; and characteristics of constraints of at least one of the resources and the at least one offering; and calculating, from these characteristics, one or more optimal targets for the business entity.
Thus, the present invention provides a tool and method that can be used by almost any type of organization that can quantify and measure its output to determine optimal targets for each subcomponent of that organization, as well as the overall targets for the organization. Continuing further along these lines, even a government can apply the methods of the invention to an entire industry composed of many organizations, and so on.
The application of this invention (either stand alone, or as a part of a business-intelligence suite) will provide numerous benefits, including better responsiveness and adaptation to market changes, decreased cost of instituting new offerings, increased revenue growth through better alignment with customer needs and market conditions, better planning accuracy and therefore more tuned execution of product/service/organizational delivery.
The foregoing and other exemplary purposes, aspects and advantages will be better understood from the following detailed description of an exemplary embodiment of the invention with reference to the drawings, in which:
Referring now to the drawings, and more particularly to
The co-pending application identified above is somewhat related to the present invention in that it also relates to optimizing activities for an organization, including such optimizing such as how many people and skills to provide for a goal and operational activities related to achieving the goals provided as an input such as a target revenue.
In contrast, the present invention addresses the problem of actually determining target goals, such as revenue targets, and thus it will permeate the entire organization's attempts for optimization. Thus, the present invention provides a tool and method so that an organization can determine optimum revenue targets, and all of the subcomponents within the organization will likewise be able to determine its own optimum revenue targets, given an overall target received from a next higher level.
As briefly mentioned previously, the tool and method is also capable of providing a target for the overall organization (e.g., the highest level of the organization) by receiving inputs that describe the environment of the organization, competitor practices, etc., and calculating targets for the overall organization.
Again, it is mentioned, that although revenue targets are the output of the tool and method for purpose of discussing the concepts of the invention, there are other types of targets that the tool and method can calculate, based on the type of organization for which the tool is being used. For example, an organization might be more concerned about target market shares or customer satisfaction. A nonprofit organization might be more concerned about determining optimal targets for benefits provided by that organization.
Moreover, as previously mentioned, even a government can apply the methods of the present invention to an entire industry composed of many organizations or to an entire economy composed of many sectors and parts.
In each instance, the targets determined by the methods of the present invention will be focused on the objectives of the entity, its components, its environment, and the scope of the problem at hand.
In one exemplary embodiment, the tool 101 performs optimization by converting the inputs 102, 103, 104 into a nonlinear programming problem, by using the methods of the invention to determine an optimal solution of this problem, and by using a commercial or open source package incorporated into the tool to compute the results of this optimal solution.
As used herein, “sector” refers to an area within a unit of a business entity or other organization. The organization could be a business unit, a solution line, a service area, a sector, or any other type of organization, such as a non-profit group or government agency, as long as the organization can quantity its outputs and its resources/constraints. An “offering” is a service or product sold by the company or organization, or possibly something more intangible, such as a brand or other abstraction related to the organization's output.
“Business objectives” can include such quantities as revenues, costs, market share, etc. “Business constraints” can include such quantities a market share, demand, supply, lead times, etc. “Revenue target” is intended in a generic sense as directed to any business metric, regardless of whether it relates to revenues or profits, since some organizations, such as government or non-profit organizations, may be oriented to service or other outputs having at least some metrics other than financial.
Strategic planning on the sector level includes estimating the optimal revenue targets for each sector among existing sectors, given skill availability, solution templates, costs, offering types, market share data, market demand for offerings, etc. All previously mentioned constraints could significantly limit maximum achievable revenue, especially scarce skill availability. Setting revenue targets too high in that case could potentially lead to many lost engagements, which could significantly reduce companies' popularity on the market, and produce many other negative effects.
In the example above, even though solution templates may be the same for each sector, certain parameters, such as skill availability per each sector could be significantly different yielding a specific (sub) optimal split of revenue targets per sector. There could be devised certain myopic rules (regime specific), optimal over long time intervals or in a highly capacitated system, suggesting a desirable revenue target split.
An exemplary risk-based stochastic optimization calculation processing that can be used in tool 101 is illustrated by the following equations, as the tool is used, given revenue demand and supply analysis, for determining optimal revenue targets:
where λi represent arrival rates of specific offering types, xi s represent the proportion of selected (accepted) offerings for each type, revi is a revenue rate per each offering of type i, riski represents the probability of losing a selected offering of type i due to insufficient staffing. Furthermore, cs is a cost rate per unit of a particular resource type s and Cs is the amount of available resources of type s.
The above analytic approach includes a combination of advanced probabilistic methods and advanced nonlinear (but including linear as a special case) optimization methods. An objective is to find offering selection policies that will maximize expected profit rate. Constraints contain mutual relationships between system parameters, such as offering arrival rates, capacities of available resources and induced risks of losing specific offerings. Risks are subject to given tolerances.
Possible alternatives to the nonlinear (with linear being a special case) approach include stochastic loss networks, stochastic queuing networks, stochastic programming models, stochastic dynamic programming models, deterministic dynamic programming models, stochastic optimal control models, deterministic optimal control models and stochastic programming. However, the present invention is not limited to these alternatives and can incorporate any probabilistic and optimization models relevant to optimal assignment.
The calculations of specific results of an optimal solution obtained from the methods of the present invention can be done by using solvers called from C/C++ programs. Details of the result calculations itself is not considered particularly important to the present invention, since such result calculation is well known in the art. In an exemplary embodiment, the IPOPT solver, which is an open source software, very convenient, and fast in search for results in an optimal solution of large scale problems, is specifically used. Specialized and proprietary solvers can also provide such results for large scale problems.
This application of the tool shown in
In this strategy, a business entity would identify a potential business opportunity, where a business opportunity could be a product, service offering, line of business, organization, etc. Each business opportunity is evaluated with respect to the entity's business objectives. By sorting through the minimum demand requirements 304, and combining as appropriate, an optimal offering/organization portfolio can be developed.
In the non-limiting three exemplary embodiments shown in
“Revenue target” is only one example of a business metric that might be optimized, since the method of the present invention applies equally to any generic business metric or combination of metrics. An “offering” can be any of a product, service, brand, etc. An organization can be any of a business unit, a solution line, a service area, a sector, etc. A business objective can include any of revenue, cost, market share, etc. Business constraints can include market share, demand, supply, lead times, etc.
Thus, from the discussion above, it can be seen that the present invention is able to provide targets for an organization such that the overall objectives and targets of the organization permeate the targets of all levels within the organization.
Moreover, from the above four exemplary embodiments and the recursive feature described in
In addition to the aspects of the tool used to perform the risk-based optimization calculations described above, the present invention includes the aspect of optimal strategic planning for an organization, by taking into account an overall objective perspective of the organization's mix of available skills/resources to determine an optimal mix of revenue targets today, as well as assist in determining the actions/policies/portfolios that should be taken to move the organization to a truly optimal mix.
As new “offerings” or “organizations” are presented for evaluation, the present invention includes the determination of the minimum demand that would justify including the new offering/organization into the current portfolio, as well as evaluation of a set of new offering proposals, which would drive the most revenue/profit and to what extent they should be pursued.
The CPUs 611 are interconnected via a system bus 612 to a random access memory (RAM) 614, read-only memory (ROM) 616, input/output (I/O) adapter 618 (for connecting peripheral devices such as disk units 621 and tape drives 640 to the bus 612), user interface adapter 622 (for connecting a keyboard 624, mouse 626, speaker 628, microphone 632, and/or other user interface device to the bus 612), a communication adapter 634 for connecting an information handling system to a data processing network, the Internet, an Intranet, a personal area network (PAN), etc., and a display adapter 636 for connecting the bus 612 to a display device 638 and/or printer 639 (e.g., a digital printer or the like).
In addition to the hardware/software environment described above, a different aspect of the invention includes a computer-implemented method for performing the above method. As an example, this method may be implemented in the particular environment discussed above.
Such a method may be implemented, for example, by operating a computer, as embodied by a digital data processing apparatus, to execute a sequence of machine-readable instructions. These instructions may reside in various types of signal-bearing media.
Thus, this aspect of the present invention is directed to a programmed product, comprising signal-bearing media tangibly embodying a program of machine-readable instructions executable by a digital data processor incorporating the CPU 611 and hardware above, to perform the method of the invention.
This signal-bearing media may include, for example, a RAM contained within the CPU 611, as represented by the fast-access storage for example. Alternatively, the instructions may be contained in another signal-bearing media, such as a magnetic data storage diskette 700 (
Whether contained in the diskette 700, the computer/CPU 611, or elsewhere, the instructions may be stored on a variety of machine-readable data storage media, such as DASD storage (e.g., a conventional “hard drive” or a RAID array), magnetic tape, electronic read-only memory (e.g., ROM, EPROM, or EEPROM), an optical storage device (e.g. CD-ROM, WORM, DVD, digital optical tape, etc.), paper “punch” cards, or other suitable signal-bearing media including transmission media such as digital and analog and communication links and wireless. In an illustrative embodiment of the invention, the machine-readable instructions may comprise software object code. The present invention can be used either stand alone, or as a part of a business-intelligence suite. It can provide numerous benefits, including better responsiveness and adaptation to market changes, decreased cost of instituting new offerings, increased revenue growth through better alignment with customer needs and market conditions, better planning accuracy and therefore more tuned execution of product/service/organizational delivery.
While the invention has been described in terms of a single exemplary embodiment, those skilled in the art will recognize that the invention can be practiced with modification within the spirit and scope of the appended claims.
Further, it is noted that, Applicants' intent is to encompass equivalents of all claim elements, even if amended later during prosecution.
The present Application is related to the following co-pending application: U.S. patent application Ser. No. 11/375,001, filed on Mar. 15, 2006, to Lu et al., entitled “Method and Structure for Risk-Based Workforce Management and Planning”, having IBM Docket YOR920050557US1, assigned to the present assignee, and incorporated herein by reference.