5 Ways Big Data & Big Analytics Can Bring Big Results

Big data and big analytics are common buzzwords in multiple fields including sports, governance, banking, investments and more. For more than 7 decades now, companies have known that data can be a source of great insight and competitive advantage. During the early years of using computers, businesses would look at numbers in spreadsheets manually and try to recognize patterns. This was the genesis of modern-day analytics. Companies started hiring statisticians who could develop models to retrieve useful business information from data collected in the day-to-day running of the business.

The term ‘big data’ crept up in the mid-2000s. The term refers to data that is collected in high volumes and at a high frequency such that traditional analytical methods would not be applicable in manipulating it. Such data is also complex in its variety and richness. As such new analytical tools must be developed to draw useful insights from the data.

The large volumes of data available today are a direct result of technologies such as artificial intelligence, machine learning, and the Internet of Things. These technologies make it possible to collect, analyze, and make sense of huge data sets in a short time. According to Statista, the big data market will grow to more than $100 billion in value by 2027.

Here 5 ways that big data and analytics can bring massive results

Customer Acquisition and Retention

Businesses today have the chance to analyze hundreds of data points during interactions with customers. Customers interact with businesses through company websites, social channels, and in stores. All these are opportunities to profile a customer and make predictions about what products they are likely to be most interested in.

Amazon has used big analytics to improve customer shopping experiences by showing them products tailored specifically for them. Content streaming websites such as YouTube and Netflix also use past customer behavior to make recommendations on what to watch. Customers do not even realize this is happening. They just enjoy the customer experience and keep using the brand.

Targeted Campaigns

Marketing budgets are slowly shifting from mass advertising on billboards and mass media to more micro-targeted granular offerings to individual customers. By collecting information through browsing behavior, recent purchases and searches, companies can accurately profile their target customer. They can then show them tailor-made offerings. For instance, a client’s purchases on a website such as Amazon or Alibaba can be used to estimate their age and income level. This can then be used to make offerings that match their taste and purchasing power.

Using Big Data and Big Analytics to Innovate

As stated, big data is rich, and users can draw powerful insight from it. This includes being able to monitor conversations around a brand or a particular class of products. By tracking such conversations, companies can tell when customer tastes and preferences are changing. For instance, an alcoholics beverage brand can tell when new cultural trends are cropping up. The brand can develop products that fit the new trend or find innovative ways to position itself to remain relevant.

Cost Control and Reduction through Big Data and Analytics

Companies today can simulate the impact of changing various variables in the production process. The availability of huge amounts of historical data makes it possible to predict the effect of variations with a large degree of accuracy. For instance, variables such as the number of workers in a plant or number of hours machines are running have a direct impact on the total production costs. Big data and analytics can be used to accurately determine the optimal production level.

Another example is the use of big data and big analytics to identify areas where a company is ‘bleeding’ money. If power costs are running too high, analytics can show areas of wastage. An old machine could be using up too much energy resources. A company would have to run a repair or replace analysis. Inefficiencies could also be because of a mismatch between machines and human resources. Analytics would help highlight all these.

Streamlining Supply Chains and Networks

Big companies that work with tens or hundreds of suppliers from all over the world have a tough balancing act to ensure everything runs smoothly. There is always a risk that a delay or a shortage of a particular item could result in cost overruns and in the worst case a halting of all activity. As such there are numerous points where data is collectible with a view of improving efficiency of the whole process.

For instance, it is possible to determine which suppliers are always on time and therefore the best to work with. You can determine the failure rate of items or parts from different suppliers. You can predict demand shocks and adjust well in time to reduce any associated costs. It is possible to predict the effects of price changes. How will they affect total production costs? Is a price raise necessary or can the company absorb such extra costs?

Big data and big analytics present companies the chance to forge useful relationships with suppliers. By sharing insight from analytics, a company can help their suppliers make optimal manufacturing decisions. For example, it’s possible to communciate faults in a certain batch of products to the manufacturer for investigation. Data on demand predictions can help the supplier plan their production to match the client’s demand.

Getting Started with Big Data and Analytics

Companies have been collecting data for decades and yet not all of them are able to benefit from it. The first step should always involve identifying the problem at hand. An example would be why the business is not converting enough prospects. The next step is collecting the relevant data to help answer this question.

Besides collection, the data needs to undergo a cleaning process so that it is correctly structured. That takes time and resources. While picking a company to work with, it’s best to go for a company that will not simply visualize the data. They need to help you come up with models to give actual useful insight. At Transcendent Software, we help clients collect data into repositories, normalize it, analyze, and develop actionable insight. We not only develop tools for clients, but we also train them and ensure they understand the various capabilities therein. For more information, check out our website.