Strategy, Legal & Operations

How to make more money with big data and predictive analytics

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

Brexit is changing the way UK businesses deal with the world. Changes in US global policy such the renegotiation of the North American Free Trade Agreement (Nafta) will redefine trade in that country. Globalisation is increasing – and so are the reactions against it. Negotiating the headwinds of financial uncertainty has never been so tough.

But 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 will 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 under way.

Aberdeen says the top five areas of investment are traditional business intelligence (reporting and dashboards), interactive data visualisation, 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.”

AI software can make a positive impact for your sales teams

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. But there’s a reason for this – big data works.

It brings speed, efficiency and ability to use data to make short and long-term decisions. It’s important – and if your business uses that use 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 here 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 synthesise 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.

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

Reliance on gut feeling isn’t 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’ve worked out the questions you need to answer, you can focus on finding the data that will answer those questions.

3. Without big data, you’re 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.

4. 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 value of advice your finance team provides to your business.

Split Screen Coffee Company cupcakes

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

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, rationalise 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 analyse 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 drink

Managers can optimise the use of fulfilment channels by using data to analyse critical information, such as the cost to ship food and drinks 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 implement the use of big data for your business

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’s 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.

1. 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.

2. 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.

3. Determine what technology you need to invest in

You will need the right technology to develop the means to pull, handle and analyse 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.

4. 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.

5. 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 organisation 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’re 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, programme 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 optimising the customer’s journey.”

Is your business using big data and predictive analytics? Let us know your stories in the comments below.