If you have a goal to start a big data project this year, you might want to think again. No company should start a big data project right now. But, let me be clear. It’s not because I predict a major downturn in the economy or an incredible innovation that will change the way a data project should be run. It’s really simple. If you plan a big data project, you’re missing the most important aspect. It shouldn’t be about the data; it should be about your business.

While data and analytics are revolutionising our world and changing the way we live and work, it is the insights that they provide that make them powerful. So, unless you know what business questions you need to answer and what business problem you want to be solved, you shouldn’t start a data project.

I still see too many big data projects that haven’t got clearly defined business goals and measurable results, which is why it isn’t surprising that so many big data projects fail. When I help companies identify the most strategic ways how data and analytics can transform their business we link each project to strategic priorities and identify business KPIs that help measure the success of these projects.

Take Citibank as a good example, every data project starts with specific business requirements. Before any data projects get approved it has to be validated through proof-of-concepts and will be monitored using business performance metrics.

The same is true for Caterpillar, where every data project is linked to a business problem and measured using business KPIs, which in turn helps to showcase impressive returns on their data projects.

Key Uses of Data in Business In my new book ‘Data Strategy’ I talk about five key areas where data is used in business. Looking at these can help identify the most strategic applications of data in any business.

Improve decision making

Armed with accurate data, business leaders can make smarter business decisions. They can determine what questions need to be answered to propel their company to success.

Understand customers

When data is collected and analysed properly, it helps businesses understand who their customers are and why they buy as well as what key customer trends are on the horizon.

Improve customer offering

Data also helps companies provide a better product or service to their customers and integrate data and analytics into their customer offerings. Improve operations Data and analytics can help companies to optimise their operations, production and processes.

Create a new revenue stream when data is monetised

Data can create an additional revenue stream for many businesses when they sell their data to other companies who value it. Data is also considered an asset in the valuation of companies.

Start with a Data Strategy

Once companies have identified the areas they want to tackle with data, the first step is to identify the real business problem so they lead data projects with the business concerns rather than the data. A good data strategy is determined by what your business wants to achieve and how data can help you get there.

Develop Measures of Success

You then need to develop KPIs or metrics of success which should link to top level business goals such as growing profits and revenue, or intermediate goals such as gaining market share, driving customer satisfaction, improving capacity utilisation or boosting staff engagement. Here is a list of 25 top level business metrics to use. The power of big data is not how much you gather, but how you use the information you glean from the data you collect. In order to get buy-in from the leaders and employees of your company, you will need to help them understand the tangible business benefits your project can give your organisation and how data will help you get to those benefits. It’s imperative to help your people see how you will use data to work smarter and do better business so they can appreciate rather than fear it.

Don’t make your big data projects about the data or the technology, make sure they are business projects to achieve a strategic goal and measured by business metrics.