How to use data to drive business success

The more your business uses digital technology, the more data you'll collect. Information on everything from how your customers behave to how your finances are performing can be used to your advantage.

Get good at using your data, and you'll become more competitive and stand a better chance of success. But how do you do that exactly? By making data-driven decisions a key part of your business strategy.

Back your instincts with evidence

As a business leader, you'll have plenty of experience that helps you make important decisions every day. Following your gut is important, but you can gain more confidence that you're making the right call by backing up those instincts with hard evidence.

As the name suggests, data-driven decision-making (DDDM) is the practice of doing exactly that. When faced with a choice on which action to take, you can either use data to:

• back up or contradict what you're already thinking, or

• help you find an initial direction if you're completely unsure

Typically, this leads to better outcomes. But it also helps you quickly react to changing conditions by speeding up your decisions. By looking at the right data, you can spot trends to make predictions, and invest in resources more efficiently.

From marketing activity to inventory management, data can guide you in every area of your business.

Why DDDM matters for SMEs

Businesses of every size can and should be using data to support important decisions. But when it comes to small and medium-sized enterprises (SMEs), there are a few ways it can make a particularly big difference.

Without the financial clout of their larger counterparts, SMEs need to make sure the strategies and resources they're investing in have a high chance of success.

Failing over and over again is too costly when you have a low budget, so you need every assurance that you're making the right choices and spending in the right places.

Some ways you can use DDDM

• Budgeting: By applying DDDM to budgeting, for example, you can identify ways to reduce costs by improving your internal processes and making your operations more efficient.

• Revenue: You can also figure out how to retain and grow revenue from existing customers and spend less on acquiring new ones. And, you might use the huge amount of data your customers have given you to better understand what they need and make sure you're finding ways to fulfil it.

• Growth predictions: A look at your past customer activity also helps you predict what to expect in the future. This can help you decide what to offer and promote, and when.

With so many ways to use data, it's easy to see how it can make you more competitive in the market. Imagine if your main competitors are informing their decisions like this. No matter how reliable your gut may be, you're missing out on a lot of insight if your data is sitting there unused.

When DDDM gets tricky

Thanks to how much data is generated, and the tools available for you to make use of it, DDDM is more straightforward than ever before. But, if it's a new concept to you, there are a few challenges to be aware of.

High volume of data

More data is always better in terms of the potential insights you could find. However, many people faced with a huge amount of data can feel overwhelmed, and it gets harder to make decisions.

Prioritising what your business is trying to achieve is key here. Also, you don't have to use every last data point you have. Start small and gradually incorporate more data into your decisions over time.

Poor-quality data

Sometimes, another symptom of having lots of data is a lack of quality. That's because not all data will be relevant to your business strategy, and this can potentially lead you astray.

The type of data you collect, as well as the methods of collecting it, will affect its quality. This will get better over time as you continually learn which data is most useful and how to keep it clean.

Lack of understanding

Speaking of learning, how well you and your team can understand and interpret data is a skill you need to hone. This will happen naturally as you experiment with using different types to inform decisions.

Just be conscious of how many data points you're using to do this. Again, start with smaller amounts of data, and build up as you learn what works. You can also invest in staff training to help your team get better at this in less time.

Culture clash

If your business is well established and has been doing things the same way for a long time, you might run into some resistance when trying to get people to use data. This is a culture issue, as it can be quite a big change that feels like extra work for many in your team.

Things can also go the opposite way. Eager to embrace this way of working, some people may dip in creative problem-solving, as they start to solely rely on hard evidence before making a decision. You need to strike a healthy balance between the two.

Confirmation bias

Data may present cold, hard facts, but interpretation is still very much a human activity. Confirmation bias is when you're already in favour of taking a particular path and only tend to see the evidence that supports this view.

It's also possible that people (both unknowingly and knowingly) skew the data towards what they want to happen, particularly if they're holding on to old views or ways of working.

Examples of data-driven decision-making

Since tech can feature in pretty much every area of your business, there are endless ways to use the data it provides. Here are five examples to give you an idea of where you could apply DDDM:

Supply chain

If your business spends a lot of time on managing inventory, basing decisions on data can lead to improvements that save you a lot of money.

For example, you could take finer control of stock levels by buying more accurate quantities based on seasonal fluctuations and reliable forecasts of demand. In the warehouse, you could use data to process orders more efficiently with better timing and delivery routes.

Your data can also highlight opportunities to improve workflows with new technology, such as automation.

Customer service

Customers offer a gold mine of useful information that can help you improve your business. From feedback and product reviews to surveys and call centre activity, there are many ways to figure out when customers are happy or dissatisfied.

This helps you continually improve your products and services, deliver better experiences, and generate more revenue through both customer loyalty and acquisition.

Marketing and sales

DDDM is becoming essential in sales and marketing. This is because you're typically targeting a lot of people, and only a small percentage (relatively speaking) will respond to your activities.

Insights from audience research, marketing testing, brand perception and sales performance can all improve your success rate.

Whether it's figuring out what kind of advertising leads to the most sales opportunities, or which products and services to run a discount on, informing decisions in these areas is proven to drive more revenue.

Human resources (HR)

Like prospects and existing customers, your own people provide a source of valuable data that you can use to your advantage.

Understanding how your recruitment processes are performing, getting feedback to measure employee engagement, and even tracking attendance can help you hit specific HR goals. You can use data to figure out who's ready for promotion, boost retention, and attract the best talent.

Finance

A lot of business decisions are driven by your financial circumstances at any given time. Data can give you a clear indication of your financial health now and in the future, helping you reduce risk across many areas of financial decision-making.

Whether it's deciding how to allocate budget, anticipating cash flow or trying to secure outside investment, having evidence-based figures can keep you in control.

Where to start with a DDDM strategy

If you're ready to balance your instincts with valuable insights, the best places to start are your business strategies. This is where you can articulate when, how and why you'll use data to drive decisions within your teams.

But before you get into the detail, here are six things to keep in mind:

Prepare everyone for the culture shift

Communicate clearly that a data-driven approach is going to be an important element of all business strategies. Make sure that leaders are on board with this first, and then have them demonstrate their support to the rest of the business.

A key aspect to communicate is the purpose of the new approach and the outcomes you're looking for. They need to be crystal-clear. Acknowledge that it will be a challenge, and make sure everyone has the training, time and mindset to develop their skills in using data.

It can also be useful to run an internal survey to get a sense of employees' current level of knowledge. That way, you know which areas they'll need the most support in.

Create systems for managing data

To effectively make sense of all the data your business generates, you need solid systems in place. This includes a plan for how you'll manage and analyse data. The plan should lay out how people should determine whether the information they're using is relevant, accurate and high-quality.

You also need to make all of your data sources accessible to the people who will be using it. Take the time to audit those sources, and make sure people won't be able to use outdated information by mistake.

Choose data tools carefully

There are many types of tools that can help you extract value from the data in your business. From financial reporting to data visualisation, most of them are designed to be very easy to use, which means you won't need an IT expert to benefit from them.

• Business intelligence (BI) tools are great for processing unstructured data from systems inside and outside your business, while automation solutions can strip away the manual work of gaining insights.

• Artificial intelligence (AI) is also being widely adopted. This technology can learn from your data and provide a wide range of uses – from financial projections to spotting anomalies.

Visualise the data

Even the most valuable data-driven insights can be hard to interpret when presented in raw numbers. By visualising the data in graphs, heatmaps and charts, you can very easily spot trends and patterns.

This is also great for communicating insights to people who are less data-savvy, but still have a need for evidence when making their decisions.

Most data tools provide visualisation capabilities, allowing you to present information in an understandable way. For example, dashboards can show you the financial health of your business at any given time.

Connect data and people

To make sure your data retains its quality and integrity, it's best to limit the number of places in which you store it. Ideally, you should be using systems that can integrate easily and share the same information. This reduces how often data will be duplicated and means it will be more consistent and accurate.

You also need to encourage your teams and departments to collaborate as much as possible. Working in silos (i.e. not sharing information about what they're doing) only causes confusion and is inefficient. Sharing data and working together produces the opposite results.

Track and measure progress

Perhaps one of the most powerful uses of data is being able to learn what works and what doesn't. You can compare past and current performance, and even get feedback part-way through projects, allowing you to change course if you need to.

Data also provides you with metrics to help you set targets for the future and gain an understanding of how well the business is doing over a long period of time.

Even data-driven decisions can sometimes be wrong. But with more information at your disposal, you can understand the impact of those decisions and adjust metrics and strategies accordingly.

Before you go…

Yes, there are many advantages of using DDDM, and you'll be passing up countless opportunities if you neglect it. But always remember – it's a way to support your decision-making, not dictate it.

Human experience and instinct still have huge roles to play, and even with data backing you up, things can still turn out differently than you expect.

It's about making use of everything you have in your toolkit to lead to (not guarantee) the best possible outcomes.

Even if you use data sparingly, you'll immediately feel more confident that you're making the right decisions. And if it turns out you're not, the data will always give you the insight to adjust your strategy.

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