Introduction & literature on leadership style
Title : Management
Leadership Style after Mckinsey 7s Framework
The model developed by McKinsey illustrates most suitable way through which one can systematize a given organization. It’s based on seven key elements where all of them should be synchronized and work together to achieve the desired goals. These elements are either grouped into two as soft or hard. Hard elements; this refers to the physically tangible elements when put in place in a given institution (Burns 1978).
Strategies put in place to improve the organization including the objectives and any environmental related factors affecting the business , Structure of the given organization, its hierarchy and reporting mechanism and various systems implemented where the main systems supporting the business are identified , are examples of the hard elements in the organization. Soft elements are those that cannot be physically seen and include shared values within the organization skills within the organization which should be in line with the strategy and vision, its staff and the style used in implementation of the system.
With this kind of leadership style one is able; to understand a system transformation and its impact on the organization. One can be a bale to establish a process change that brings about a new change in balancing of the seven elements model. Allows easier arrangement of the various departments and processes when acquiring data.
For a more successful change the leadership style implements’ the model in the following sequence; analysis of the current state, examining of the future state , development of model view of both current and future states and finally comparing them.
Technological development has been enhanced in current days to handle various amounts of data. In our research we are concentrating on the big data analytics.
Resource based view is a theory which explains the way in which resources are utilized in a firm can enable obtain the required competitive advantage of the other producers or suppliers in the market. It’s designed on the following assumptions diversification of the resources where it’s defined whether a given resource is fully owned by the company or by other competitors too. Immobility of the resource which defines how difficult competitors can access given resource due to economic constrains. Dynamic capabilities are aimed at improving the innovations in the company.
Organizational structure and data this is a process that involves collective vital decisions being made. The organization has to plan how it will handle the large data deployment. It has to distribute data across various functions be able to prioritize forthcoming opportunities and equal spreading of time allocation to data. This can be done by implementation of models such as business unit led model and fully centralized model.
The purpose of our study is due to three reasons; currently in our modern world the topic of big data and analytics is the main talking point in the real time applications. People are interested in how to utilize it ensuring maximum utilization of collected information essential in decision making .Companies can find a competitive advantage through it: this is so because when in use it gives optimum conditions for selection of the best decision that allows producers meet the specific customer demands in time. Complexity of the system in nature really got our attention to research on it
In our goal is to make out and analyze different practices in the organization of internal data analytics. Research question was to know company organization around analytics. The key interests are embedded on the organizational aspect rather that strategic and technological aspects of individual organizations.
In our research work will illustrate big data analytics in the following stages data collection it’s processing of the data involving all the necessary computations. Storage of the processed data and finally analysis of the stored data that will be essential in the decision making process: The main objective identifies and examines various carried out activities in the organization of internal data analytics. Analyzing and criticizing the organizational structure in the firm and finally targeting of the various areas of key interest within the organization relatively than basing on strategically positioned technological aspects of individual organization elements (Burns 1978). These three components when combined form the skeleton of the whole research work study. Then optimize on the available information generating best decision models possible. Carry out research that will enable come up with more efficient conventional equipment that can fully handle the big data, with the optimum efficiency possible.
Data Collection : this involves collection of data from the required source with a target of collecting maximum amount of data .This will be done by use of several methods such as interviews, recording of the data , and use of well positioned sensors and sensory devices.
Data processing: this involves carrying out of related computations on the collected raw data transforming it into useful information, data integration correcting linking all the required data which is consistent and reliable in nature
Data storage; this involves safely keeping of the processed data, awaiting the next stage in the cycle which is the data analysis stage.
Data analysis: involves carefully examining the processed data obtaining the relationships and seeing how the various functional elements relate to each other. Several operations that may be carried out during this stage to improve the system in our research include linking of external and internal parties in the organization to improve optimization efficiency.Levering newly discovered technologies
Finally the findings of our research will be presented in the paper and discussed
During our research we were able to find the following from collected data.
Approximately 80 % of organizations that are not willing to implement the big data strategy are likely to loose bargain power to other competitors in the following year.
About 90 % of organizations have the big data analytic as one of the prime priorities in implementation if not the main.
About 84% of the companies feel that with implementation of the big data analytic they shall be able to elevate their competitive powers to a better level within a period of one year.
Approximately 92 % of the organizations feel that with introduction of new entries make big data analytic strategy as a key distinguishing factor as to who stands out in terms of performance.
Almost 4/5 of our respondents are specific to monitor several assets with keen interest on the related operating issues associated with them
From our findings it was beyond reasonable doubt Bid data is far much better than market propaganda. This is because it has the capacity to remodel and revolutionize the markets, elevating competitive platforms. It could be evident that most organization believes that indeed using big data analytic are confident of registering better profits and results by a span of one year down the line. Organizations which are not willing to implement the system may end up losing their competitiveness in the market. This is attributed to the better efficiency and optimization opportunities that the system gives to its users. Some of the organizations that were not willing to implement the big data analytic are due to the high cost of acquiring installing and maintaining it. Despite such constrains if successfully implemented it gives desirable benefits to the firm.
Using of big data handling methods in analytic has proved to be a successful way of collecting more data from a given platform accurately and also ensuring optimization of use of data to come up with better decision. Its every essential in situations of complexity, requiring large quantities of data. Efficient use of the data allows pharmacies identify possible treatment targets transforming them into medicine quickly. Though the implementation of such a system is challenging the fruits at end of the process are worthy investing into.
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