Introduction to Matrix Management

A leader is responsible to empower his people and get the best out of them. Yet an organisational structure can either help or hamper performance. Worst, it can make or break success.

Looking at the fast-changing world of the global economy, whatsoever slows up and obstructs decision-making is a challenge. Hierarchical management is rather unattractive and functional silos are unlikable. Instead, employees desire to create teams equipped with flexibility, cooperation and coordination.

Recognising that companies have both vertical and horizontal chains of command, the matrix model is created. The concept of this principle lies in the ability to manage the collaboration of people across various functions and achieve strategic objectives through key projects.

Consider this scenario:

Ian is a sales executive of a company. His role is to sell a new product under the supervision of a product manager. The manager is expert about the product and she is accountable to coordinate the people across the organisation, making sure the product is achieved.

Moreover, Ian also reports to the sales manager who oversees his overall performance, monitors his pay and benefits and guides his personal development.

Complicated it may seem but this set-up is common to companies that seek to maximise the effect of expert product managers, without compromising the function of the staffing overhead in control of the organisation. This is a successful approach to management known as Matrix Management.

Matrix Management Defined

Matrix management is a type of organisational management wherein employees of similar skills are shared for work assignments. Simply stated, it is a structure in which the workforce reports to multiple managers of different roles.

For example, a team of engineers work under the supervision of their department head, which is the engineering manager. However, the same people from the engineering department may be assigned to other projects where they report to the project manager. Thus, while working on a designated project, each engineer has to work under various managers to accomplish the job.

Historical Background

Although some critics say that matrix management was first adopted in the Second World War, its origins can be traced more reliably to the US space programme of the 1960’s when President Kennedy has drawn his vision of putting a man on the moon. In order to accomplish the objective, NASA revolutionised its approach on the project leading to the consequent birth of ?matrix organisation?. This strategic method facilitated the energy, creativity and decision-making to triumph the grand vision.

In the 1970’s, matrix organisation received huge attention as the only new form of organisation in the twentieth century. In fact it was applied by Digital Equipment, Xerox, and Citibank. Despite its initial success, the enthusiasm of corporations with regards to matrix organisation declined in the 1980’s, largely because it was complex.

Furthermore, the drive for motivating people to work creatively and flexibly has only strengthened. And by the 1990’s, the evolution of matrix management geared towards creation and empowerment of virtual teams that focused on customer service and speedy delivery.

Although all forms of matrix has loopholes and flaws, research says that until today, matrix management is still the leading approach used by companies to achieve organisational goals.

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Energy efficiency- succeed and benefit

Energy is neither created nor destroyed; it is only transformed. This being the law of conservation of energy, and given that the process of transforming energy is inefficient resulting in loss of usable energy in the process of transforming one form of energy into another form, Energy Efficiency finds a home.
Talking of Energy efficiency, think of how much useful energy can be obtained from a system or a particular technology. It is also about the use of technology that requires a lesser amount of energy to carry out the same task.

Energy efficiency is the responsibility of both demand side and supply side. Supply-side energy efficiency refers to a set of actions taken to ensure efficiency through the electricity supply chain. Supply side efficiency measures are about efficiency in electricity generation; be it operation and maintenance of existing equipment or upgrading existing equipment with state-of-the-art energy-efficient generating equipment.

The demand side energy efficiency on the other hand refers to the actions taken to use less/demand less energy. Think of less energy usage in relation to improvement of energy efficiency in buildings, solar water heaters, energy efficient lighting systems such as Compact Fluorescent Lamps, conducting energy audits to identify potential energy saving opportunities, efficient water heating systems and the list is endless.

Success of energy efficiency is a win ? win to YOU-ME-US – the energy consumers, to THEM the energy producers and suppliers and to our precious ENVIRONMENT.
Gain to energy suppliers: – Less energy usage and better energy usage patterns among consumers consequently reduces the customer load which reduces losses on the supply side. Less energy loss creates capacity on the system to serve more customers.

Gain to you-me-us: – Less energy usage and better energy usage patterns Benefits the customer through reduced Electricity bills / $ savings through lower bills.

Benefits to the environment: – Usage of less energy reduces use of fossil fuels, hence reduction in GHG emissions hence conserving our environment. Companies look at means to make rational use of their least efficient generating equipment. The objective is to improve the operation and maintenance of existing equipment or upgrade it with state-of-the-art energy-efficient technologies. Some companies have on-site electricity generation alternatives and thus tend to consider the supply side in addition to demand-side energy efficiency.

How SOA can help Transformation

Undoubtedly, today’s business leaders face myriad challenges ranging from fierce market competition to increasing market unpredictability. In addition, the modern consumer is more informed and in control of what, where and how they purchase. Couple these challenges with effects of globalization, and you will appreciate that need for business transformation is more of a necessity than a privilege.

As recent business trends show, top companies are characterized by organizational and operational agility. Instead of being shaken by rapid technological changes and aftershocks associated with market changes, they are actually invigorated by these trends. In order to survive in these turbulent times, business leaders are opting to implement corporate transformation initiatives to develop leaner, more agile and productive operations. In line with this, service oriented architecture (SOA) has emerged as an essential IT transformation approach for implementing sustainable business agility.

By definition, service oriented architecture is a set of principles and techniques for developing and designing software in form of business functionalities. SOA allows users to compile together large parts of functionality to create ad hoc service software entirely from the template software. This is why it is preferred by CIOs that are looking to develop business agility. It breaks down business operations into functional components (referred to as services) that can be easily and economically merged and reused in applicable scenarios to meet evolving business needs. This enhances overall efficiency, and improves organizational interconnectivity.

SOA identifies shortcomings of traditional IT transformation approaches that were framed in monolithic and vertical silos all dependent on isolated business units. The current business environment requires that individual business units should be capable of supporting multiple types of users, multiple communication channels and multiple lines of business. In addition, it has to be flexible enough to adapt to changing market needs. In case one is running a global business enterprise, SOA-enabled business transformation can assist in achieving sustainable agility and productivity through a globally integrated IT platform. SOA realizes its IT and business benefits by adopting a design and analyzing methodology when developing services. In this sense a service consists of an independent business unit of functionality that is only available through a defined interface. Services can either be in the form of nano-enterprises or mega-enterprises.

Furthermore, with SOA an organization can adopt a holistic approach to solve a problem. This is because the business has more control over its functions. SOA frees the organization from constraints attributed to having a rigid single use application that is intricately meshed into a fragmented information technology infrastructure. Companies that have adopted service oriented architecture as their IT transformation approach, can easily repurpose, reorganize and rescale services on demand in order to develop new business processes that are adaptable to changes in the business environment. In addition, it enables companies to upgrade and enhance their existing systems without incurring huge costs associated with ‘rip and replace’ IT projects.

In summary, SOA can be termed as the cornerstone of modern IT transformation initiatives. If properly implemented great benefits and a sharp competitive advantage can be achieved. SOA assists in transforming existing disparate and unconnected processes and applications into reusable services; creating an avenue where services can be rapidly reassembled and developed to support market changes.

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Migrating from CRM to Big Data

Big data moved to centre stage from being just another fad, and is being punted as the latest cure-all for information woes. It may well be, although like all transitions there are pitfalls. Denizon decided to highlight the major ones in the hope of fostering better understanding of what is involved.

Accurate data and interpretation of it have become increasingly critical. Ideas Laboratory reports that 84% of managers regard understanding their clients and predicting market trends essential, with accelerating demand for data savvy people the inevitable result. However Inc 5000 thinks many of them may have little idea of where to start. We should apply the lessons learned from when we implemented CRM because the dynamics are similar.

Be More Results Oriented

Denizon believes the key is focusing on the results we expect from Big Data first. Only then is it appropriate to apply our minds to the technology. By working the other way round we may end up with less than optimum solutions. We should understand the differences between options before committing to a choice, because it is expensive to switch software platforms in midstream. data lakes, hadoop, nosql, and graph databases all have their places, provided the solution you buy is scalable.

Clean Up Data First

The golden rule is not to automate anything before you understand it. Know the origin of your data, and if this is not reliable clean it up before you automate it. Big Data projects fail when executives become so enthused by results that they forget to ask themselves, ?Does this make sense in terms of what I expected??

Beware First Impressions

Big Data is just that. Many bits of information aggregated into averages and summaries. It does not make recommendations. It only prompts questions and what-if?s. Overlooking the need for the analytics that must follow can have you blindly relying on algorithms while setting your business sense aside.

Hire the Best Brains

Big Data?s competitive advantage depends on what human minds make with the processed information it spits out. This means tracing and affording creative talent able to make the shift from reactive analytics to proactive interaction with the data, and the customer decisions behind it.

If this provides a d?j? vu moment then you are not alone. Every iteration of the software revolution has seen vendors selling while the fish were running, and buyers clamouring for the opportunity. Decide what you want out first, use clean data, beware first impressions and get your analytics right. Then you are on the way to migrating successfully from CRM to Big Data.

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