Developing Data Analytics: How To Expand Your Use Of BI

Business Intelligence

Being able to gain insight from an increasing pool of customer, market and trend data is a goal for most entrepreneurial companies today. With an ever-expanding amount of information available, we have the potential to know more about our business climate and new market opportunities – if we know how to use that data effectively. So, we are starting to see approaches to data changing within businesses.

As business intelligence capabilities become more distributed, organisations can expand how data is used across business teams. This places a new focus on the way the organisation uses data – the key to successful interrogation of data is knowing what questions to ask, as well as having access to the right data and the right tools.

Some organisations are establishing the role of the Chief Data Officer to shape and manage these new data-driven processes. Organisations like Wells Fargo and CitiBank have already created these roles internally, while Gartner research points to around 25 per cent of large enterprises looking to create CDO roles in the next eighteen months.

Here are some of the ways analytics can advance your insight.

Combine Data In New Ways

Almost all businesses will be doing some form of analytics right now. From standard sales reporting, it is possible to put together information on how a company is performing. This can be used alongside other sources of data like inventory, supply chain information or other business unit reporting to provide a picture of overall performance.

This insight will tend to be historical, and answer questions on how things have changed over time. Example questions here might include “How much more have I sold this quarter?” or “Which channel made the most sales?”

While knowing this kind of information is valuable, it is possible to get more insight by asking more forward-looking questions. This is more advanced analytics, as it relies on combining data in new ways.

A good example here is forecasting – for many companies, sales and operations teams go through what they would like to achieve and then use this to create their numbers. For companies looking at forecasting, data analytics can provide more reliability – for example, on how the forecast is likely to be met and the likelihood of each project or sale being completed. At this point, forecasting can be linked into other business teams’ projections to present an overall picture.

This forward-looking approach is also being applied to new business models; rather than simply looking at sales, businesses are analysing their customer acquisition costs (how much it costs to win a customer) and lifetime values (how much the average buyer spends during their time as a customer). This links together information from sales with customer relationship management systems, service records and digital marketing campaigns.

From Reactive To Predictive

These approaches to analytics tend to be focused on what has occurred, not what can potentially happen. Predictive analytics is one of the buzz phrases of the moment and covers how data can be used to spot new opportunities around specific areas, based on decisions made now. By providing more guidance to the sales, marketing and operations teams through modeling situations, this data can then be varied to show how changes can affect the potential future results.

An example is the cross-over between sales and marketing. When a company works over multiple channels, getting the right mix in place can be a difficult balancing act. Predictive analytics can help by using past sales records and marketing campaign data to gauge which channels were the most successful. More importantly, it can help tell you why.

It’s possible to analyse how each channel was affected by marketing: were sales on the online channel affected more by other online marketing activities, or did partner activity drive more interest? How does this compare to other channels? Ultimately, looking at this data in more detail can tell you which channel brings in the most profitable customers, and therefore where more investment should be made.

The big challenge here is to make sure that data is being used in the right manner. This is where the chief data officer role comes in, providing guidance and expertise around the application of analytics and business intelligence across the business.

Single View Across Organisational Data

Being able to draw information from different data siloes is critical for deeper insight. As data sources are often spread across a business and stored in different ways, bringing them together in one place requires both the tools to do this and the ability to work across business teams where it’s required. This is where distributed business intelligence creates new opportunities.

Making data available and usable to everyone is a key competitive advantage for the future. Cloud-based business intelligence can gather, analyse and then present data faster than traditional BI platforms, fitting the needs of line of business teams that are looking for more agility in their approach.

As companies seek to get more from their data, there is a huge amount of potential for BI. Using new approaches like predictive analytics and cloud-based BI can create new opportunities to make savings, deliver value and exploit new markets.

David Gray

David Gray is Vice President International at Birst and is responsible for leading the company’s strategy and operations in international markets. He has a long history in the enterprise software and analytics markets, having held roles at OpenPages, Business Objects, Sun and IBM.