Big data analytics has become a huge concept in 2018, yet many corporations still continue to be puzzled by how to use it and what it means. In short, big data is a potent and advantageous tool for sales and marketing. It utilises intelligence and analytics to steer massive company growth and gain competitve advantage.
The way that big data is utilised forms an essential competitive advantage for many companies to stay competitive. In the majority of industries, both existing as well as new establishments will implement strategies based on big data analytics in order to stay competitive, innovate, grow and seize value.
In this post, I’ll share how big data can help businesses gain a competitive advantage by creating new growth opportunities through the aggregation and analysis of industry data.
*Approx 8 minute read
Who Is This Post For?
- Local business owners small to large
- Multi-unit brands such as franchise groups, dealer networks and national brands with a local presence.
- Any brand, whether you’re just starting in your digital journey or you’re advanced, this post is for you.
Commonly Asked Questions that I will Address:
- What is big data
- What are the 5 V’s of big data
- What are the competitive advantages of big data analytics
- What is the potential of big data for businesses
- How can big data be used in strategy development
What is big data?
Big data is all the information collected through various technological sources and then processed in a way that traditional data mining and handling techniques are unable to analyse.
Information collected via big data is scrutinised to diagnose behaviours, patterns and any other marketplace trending information. It is then used to make informed decisions on marketing, business, and promotion.
Big data is often characterised by 5 V’s: volume, variety, velocity, value and veracity.
This refers to the expansive amounts of data generated every moment. Data collected from various sources such as messages, photos, emails, video clips etc. we create and share on a daily basis. Big data volume is rising exponentially and by 2020, the accumulated volume of big data will increase from 4.4 zettabytes to roughly 44 zettabytes. On Facebook alone users send roughly 31.25 million messages and watch 2.77 million videos each and every day. That is A LOT of data being generating on a continuous basis.
As a result of IoT, we now have access to many various types of data. Traditionally, the emphasis was on structured data that would squeeze into tables or relational databases, however, these days the majority of data is unstructured, and cannot simply be put into tables for analysis (eg. videos and photos).
Velocity refers to the speed at which new data is being generated, which is super fast. Social media messages are posted in seconds, photos shared in a heartbeat and credit card transactions processed within moments.
It’s one thing to generate all this big data but until we can turn it into value it is pretty much futile. This makes ‘value’ probably the most important V of big data. There are various methods to determining the ultimate value of data, including data warehouses, business intelligence systems, and analytics sandboxes and solutions.
Big data can be murky, incomplete and misleading. Because there are so many types of big data, it makes it difficult to control the quality and accuracy. However, the sheer volume collected often is a trade if for the lack of quality or accuracy.
Competitive Advantages of Big Data Analytics
The importance of big data does not revolve around how much data a company has but how a company analyses the collected data.
As it stands, many large companies are utilising the potential of big data in gaining competitive advantage. Big Data Analytics has enabled businesses to zoom into their captured data and look for the most relevant information and analyse it to make important business decisions. Here are some of the benefits of Big Data Analytics:
Wikipedia defines predictive analysis as “encompassing a variety of statistical techniques from data mining, predictive modelling, and machine learning, and that analyse current and historical facts to make predictions about future or otherwise unknown events.”
This powerful tool opens up vast opportunities for corporations as now businesses can foresee events as well as behaviour, based on historical data. The trick here is to look in the past to know what will be in the future.
Most businesses depend on evaluating their risks and then acting on those insights. Risks can come from various sources and thus strategies need to be in place to manage any potential threats.
By using big data, the model of risk management can be enhanced majorly in part thanks to a quite comprehensive amount of information. Thus, management decisions are derived based on the data collected.
Here a few ways in which risk can be handled:
- Fraud Detection
By implementing pattern recognition, big data can be used for more precise and faster fraud detection. Any change in usual business patterns may indicate malicious activities.
The analysed data can include but is not limited to location, device type and any transferred amounts. The main value here is that with real-time processing, this ‘transaction’ can be stopped before any major damage is done, hence minimising the risk.’
- Scenario Simulation
Scenario simulations based on vast data amounts allow for an efficient realisation of risk assessments and faster new market growth responses. In today’s fast data climate, the challenge is to achieve a sort of stability with the sheer volume of simulations. One of the most useful tools for this job is the Monte Carlo simulation, powered by parallel computing over distributed file systems. The result gives the value at risk for a portfolio within a given timeframe.
- Develop new business models
Risk management has evolved from audits and due diligence to vast amounts of data points per application to measure trustworthiness. Big data is transforming the way companies measure risk and spawn new business models. Some companies now use more than 10K data points per application to measure creditworthiness, and they take into consideration much more than credit history.
Customer Behaviour Insights
Big data, especially from social media has the power to shed light on always changing consumer trends. The amount of data gathered grows larger by the second and customer behaviour on social media represents a major driver of the phenomenon. The number of social media users worldwide in 2018 is 3.196 billion, up 13 percent year-on-year. That is A LOT of data coming in on a daily basis.
The data gathered here has the potential to illustrate in detail all stages of the consumer decision-making cycle, such as customer interests, purchase behaviour and frequency as well as location. Thus big data presents a huge opportunity for understanding each stage in the consumer decision-making process. However, it is imperative that companies are respectful of consumer privacy concerns that result from big data collection and utilisation.
A major competitive advantage of Big data is the fact that it is a very precise way to identify what is working well within certain elements of your company and then make strategic decisions based on this information. It’s like a roadmap to your company’s success.
Big data with its advanced analytics potential is providing great value across all industry sectors. The motivation for implementing this new technology is having the ability to conduct an analysis of big data to achieve cost reductions, business process improvements, faster and better decisions and new offerings for customers.
To discuss how using big data can provide your business with a competitive advantage as well as specific solutions I have developed, contact me today for a confidential discussion.