How to make more money with big data and predictive analytics

Asavin Wattanajantra
Asavin is a seasoned business writer and SMB expert at Sage, with a passion for explaining, analyzing, reporting, and providing advice on the latest business technology and innovation trends.
Using Big Data and Analytics

Your business needs to consider using big data and predictive analytics if it isn’t already. But why?

The recent US legislative changes are changing the way businesses operate in a global marketplace. Globalization is increasing – and so are the reactions against it. Negotiating the tailwinds of financial uncertainty has never been so tough.

However, by implementing the use of big data analytics – the examination of massive amounts of data to uncover patterns, trends and insights – not only will your firm be able to stay on track; as a result, it could do more business and make more money.

Research by Aberdeen shows there are clear business reasons – cutting costs without hurting growth or customer relationships. Meanwhile, 58% of senior finance executives want to increase operational efficiency with data. The move is well underway.

Aberdeen says the top five areas of investment are traditional business intelligence (reporting and dashboards), interactive data visualization, integration and data preparation, traditional data integration, and predictive analytics.

Peter Sondergaard, an executive vice president at Gartner, explains the value of big data. He says: “Information is the oil of the 21st century and analytics is the combustion engine. Pursuing this strategically will create an unprecedented amount of information of enormous variety and complexity.”

Big data competitive advantage

No conversation about making money from data analytics would be complete without a discussion of the “3 V’s” of big data: variety, velocity, and volume. (Or, to be more specific: high-variety, high-velocity, and high-volume.)

“Variety” expresses the idea that data spans countless mediums and formats. Examples range all over the technological map, such as photos, audio or video files, text files, tweets, email attachments, and others.

“Velocity” describes the speed at which the data can be collected, processed, and analyzed; or in other words, how fast the data produces insights a business can act on. Put simply, velocity measures how quickly data is being gathered.

Finally, “volume” refers to the amount of data available. With almost endless sources of data to draw from – such as social media, online purchases, and other transactions made by companies or consumers – the existing volume of data is constantly (and rapidly) increasing.

Interpreting big data in the right way can be beneficial for your business.

What are the benefits of using big data?

Big data as a technology concept has been hyped up for many years in technology and business circles, like the cloud. However, there’s a reason for this – big data works.

It brings speed, efficiency and the ability to use data to make short and long-term decisions. It is important – and if your business uses that big data well, it will have a competitive edge.

Machine learning, where computers can learn without being explicitly programmed, is already having a major impact as it allows value to be extracted from huge sources of data in a way not previously possible.

Handling and making the best use of big data has never been so important – and there are several reasons why using big data in the right way can provide you with a competitive edge in tough markets:

  1. It allows you to predict the future by looking at past data

Analytics provides information for scenario planning, allowing finance departments to synthesize historical financial information and uncover trends to see where a business is going. It can also make use of real-time financial data to reveal valuable insight. Tools such as dashboards also allow CFOs to develop, report and share critical business information throughout the business.

  1. You can make better, data-driven business decisions

Reliance on gut feeling is not good enough when it comes to making business decisions – data should be at the heart of your strategic decision making, especially in key areas such as finance and operations. Once you have worked out the questions you need to answer, you can focus on finding the data that will answer those questions.

  1. Without big data, you are in danger of being left behind

Big data is now seen to be a competitive advantage. The better decision making it offers can aid growth, enhance productivity and create significant business value. You can use data to innovate, compete and capture a share of your market.

  1. It allows your finance team to become more agile and responsive

Your finance team has always been called to use its skills to guide business decision making. With big data, it can become more agile and responsive when it comes to adapting to changes in supply, demand and global changes in the business environment. Big data provides more accurate forecasts and increases the value of advice your finance team offers to your business.

You can use big data to analyze to cost of shipping your firm’s delicious cupcakes

 Making money out of data

Making money from big data depends on a company’s ability to effectively leverage the data that is available for analysis. Here are five examples of ways companies can use big data to their financial advantage.

  1.  Make time to compare different variables to see which perform or convert better. Details as minor as color or font can influence consumers.
  2.  Obtain data from the broadest range of sources possible to get a clearer understanding of the customer experience.
  3.  Process data in real-time, enabling rapid innovation that meets shifting demands.
  4.  Remember to adapt to trends. Continue to test for optimization to see where performance could be improved.
  5.  Utilize a combination of qualitative research and quantitative research, rather than relying too heavily on one or the other, to get a more complete picture.

How big data is used in different industries

Adrian O’Connor, founding director at Global Accounting Network, says: “In anything product related, for example, big data can help identify significant inefficiencies across production lines or supply chains.

“In such circumstances, even small incremental wins can mount up to significant gains in margins. We have seen clients increase production line performance, rationalize product sets and reallocate investments, all to gain efficiency because of things identified from big data analytics.”

Big data has applications in many industries – if your business is looking to use data to answer important questions about your operations, it can benefit. Think about how these examples can apply to your own business:

Distribution

The way we can collect and analyze data has changed the way the supply chain operates, increasing efficiency, reducing risk and improving customer service.

Big data can provide support to logistics visibility, for example, allowing staff to track and know when supplies are delivered and when products leave for their destination.

It can also allow manufacturers to see whether there are problems with their suppliers, giving them the opportunity to address the problem.

Manufacturing

Big data can provide companies with better insight into supply and demand by providing managers with the means to forecast what products will be in demand and the evidence they need to start building them at the right times.

Projects that use product and point-of-sale data could be extremely valuable in allowing business leaders to adjust production to meet predicted demand.

Automotive

The analysis of historical data can be used to determine when and if a product recall is likely to take place, allowing automotive businesses to make changes in time to change the conditions that created the likelihood of a problem. They can also determine what country-specific services, models and accessories customers are most likely to be interested in.

Food and beverage

Managers can optimize the use of fulfillment channels by using data to analyze critical information, such as the cost to ship food and beverages and which transport services cost are the most effective to use.

With advanced usage, businesses can use data and logic to create models that can drive decisions and inform operations.

Chemicals

Big data can allow companies in the chemicals sector to make better demand forecasts and pricing decisions. Getting pricing right is particularly important as it determines profitability.

However, the nature of the industry and the markets served makes price decisions complex – advanced analysis of data can help make informed decisions.

Consider how to increase your chances of success with big data.

How to implement big data at your business

There’s no argument that big data holds huge potential – but it is also a challenge to get right. It requires time, resources and staff to avoid resulting in data overload and preventing driving business success. Here are five key tips to increase your chances of success.

You need data leadership

Business leaders embarking on their data analytics journey should understand what it can do and how it can increase performance within business unit. The strategy should also be led by a senior executive who has the influence and authority to put the wheels in motion, break down institutional barriers and inspire others into action.

Define a strategy

All business initiatives need a clear and well-thought-out strategy – and big data is no exception. This is where clear responsibilities and the availability of time is crucial. Even with the best will in the world, big data initiatives can die due to a lack of discussion and a failure of business departments to agree on what the priorities are.

Determine what technology you need to invest in

You will need the right technology to develop the means to pull, handle and analyze data, which will mean investment is needed on enterprise-level analytical tools needed to improve performance, as well as the resources to run it.

You need to make sure you have a process in place to pick the best big data tools for what your business needs.

Get the right expertise in

The market for experts with advanced corporate-level data skills is very competitive, which means finding the right people is a challenge and keeping them could be even more difficult.

As well as technical knowledge, they need to have business smarts and the right communication skills to ensure their insights are heard and acted upon.

Use an agile approach

The use of big data may start small – specifying a specific business problem and finding a way to solve it. You may find the needs of your organization evolve once you understand the data. This means an agile and iterative approach based on current needs is a better approach than spending lots of money on a huge project – so start small and think big.

Government services are predicted to be big spenders on big data and business analytics

The future of big data

There’s a perfect storm brewing between the availability of data, impact of new enterprise technology and a shift towards making decisions based on information, rather than simply gut instinct.

There is huge demand and we are only going to see the enterprise analytics market grow – according to IDC, worldwide big data and business analytics revenues will reach more than $210bn in 2020. IDC predicts that banking, discrete manufacturing, government and professional services will be the biggest spenders.

Jessica Goepfert, program director at IDC Customer Insights and Analysis, says: “The three industries that comprise the financial services sector – banking, insurance, and securities and investment services – all show great promise for future spending on big data and business analytics.

“This technology can be applied across key use cases throughout these financial institutions – from fraud detection and risk management to enhancing and optimizing the customer’s journey.”

Is your business using big data and predictive analytics? Tell us about it in the comments below.

Editor’s note: This article was originally published January 2018 and has been updated for relevance. 

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