Why Do Marks And Spencer Uses Big Data

Big data analytics can be used by company to make informed business decision by examining large amount of varied data to get customer preferences, market trends and other useful information. Company can use it to explore new revenue opportunities, improved operational efficiency, better customer service and competitive advantages over rivals.

Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.

Technology has transformed the way companies use data. Companies need more data to streamline their marketing campaigns and target their products for the right audience. But it isn’t just about gathering information – companies also need to be able to use this information and integrate it to their service.

The era that we live in, in the year 2015 is considered the “big data” era. Industries all over the world are analyzing data and determining marketing and business processes to attract consumers. Data analysis which started off on a much smaller scale today can be used in much broader aspects from coupons you receive in your email, to advertisements you see when you use applications on your smart phone data also can be used to determine the frequent of a customer to a particular store or website. These are both processes of data analytics being used and conveyed in a way to attract customers or satisfy consumer needs. Data analysis focuses on finding the specific data to answer your question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating your results to gain optimal results. Data is not a new concept in any form, the technology of today’s world makes obtaining and analyzing data easier. The recent decades have seen a fundamental change in the model of data analysis. IMB Tech Trends Report (2011) identified business analytics as one of the four major technology trends in the 2010s. According to Chen (2012) Business intelligence began its practice in business and IT communities just a few decades ago in the 1990s. In the 2000s business analytics was introduced to represent the key analytical components in business intelligence. The business intelligence and data analytics previously adopted in an

Wolfsen (2013) asserts that it will attract more customers as customers would like to get their service done in less time. To minimize the time of customers spending on purchasing, one of the most efficient way is through big data. Matthew (2014) suggested that the technology of big

Big data is sprouting up everywhere and using it appropriately will drive competitive advantage. Ignoring it will simply put an organization at risk, and cause it to fall behind its competition.

Improvements brought by big data include creating more transparency among stakeholders by making big data more accessible (Manyika, 2011). Having access to and being able to manipulate data sets enables a different way of decision making to bring more science into management. Companies can segment and analyze data in near real time. The analysis improves decision making, minimizes risks, and uncover more insights to enable new innovation.

The way big data is used these days is to gather deep and useful information about people’s behaviour and sentiments. According to Katina Michael and Keith Miller - “Organizations use various analytical techniques— from crowdsourcing to genetic algorithms to neural networks to sentiment

Like the traditional data, big data through a series of steps that contain collection, storage and analysis to form a complete system to help both enterprises and individuals produce an optimum strategy or decision and maximize benefits in their stance. As for traditional data system, it is usually not enough accurate in analyze the phenomenon or the situation due to lack of sufficient data that results from the speed of collecting data is relatively low and the process

Big Data has gained massive importance in IT and Business today. A report recently published state that use of big data by a retailer could increase its operating margin by more than 60 percent and it also states that US health care sector could make more than $300 billion profit with the use of big data. There are many other sectors that could profit largely by proper analysis and usage of big data.

Big data can help you gather pertinent information about your customers. It’s the foundation to acquiring the right customers. Learn more about your customers:

Big data is defined as “large data sets or to systems and solutions developed to manage such large accumulations of data, as well as for the branch of computing devoted to this development.” (“Big Data”) This definition of big data was not added to the dictionary until 2014. The next big thing in business analytics is a relatively new, yet, explosive business practice known as data mining: the collection and analysis of big data. (Fayyad) These large, seemingly random, sets of data are condensed and analyzed for patterns and trends by people with a very broad set of skills. These people are known as data scientists and are considered unicorns in today’s job market.

Presence of big data is a very common phenomenon now days, specially when talking about medium to large size corporation. Manyika et al., in their article (James Manyika, 2011) defined the term big data as “large pools of data that can be captured, communicated, aggregated, stored, and analyzed”. To clarify they suggested that big data refers to data, whose size makes it impossible to be processed by the typical software used for database management. Gartner (Gartner, 2012)defined big data in terms of its characteristics of high volume, high velocity and high variety. By volume, he referred to the size of the data, by velocity he referred to the speed at which the data is created and by variety he referred to the range of types of data.

In today’s turbulent market conditions, supply chain executives are facing huge pressure than ever when the need of coping with a whole range of supply chain challenges is increasing. Survey shows that leaders of successful companies are tailoring their supply chains to customer needs and adopting differential practices such as collaborative planning with customers and suppliers or new technologies which can help to retain and continue their competitive advantage ( PricewaterhouseCoopers LLP, 2013). Big Data is considered as an effective method of information exploration. Supply chain leaders believe that Big Data application is able to provide greater transparency and process automation within supply chains. It can also optimize logistics and distribution operations for businesses and therefore benefits both customers and suppliers.

Transportation and logistics industry gets tons of data each day. Data for these companies will come in different forms and we need all of the data to move ahead from others in this industry. As the technology got advanced we are able to receive huge data from different sources like customer feedback, data from sensors which were installed in vehicles for their movements, positions, weather forecast and GPS to find their locations, recording phone calls from drivers to customers for quality improvement purposes, customer demands, social media and order processing applications.