The opportunity presented by big data goes way beyond the data and the related new technologies that capture and store it. The real benefit is that organisations can derive better business intelligence from far more sources than ever before, and make it available to decision makers at every level.
The keys to success are: Designing your big data analytics to support business goals and enabling decision makers to take action. It’s easy to collect large amounts of data. Knowing what to do with it all - and making changes based on what you learn - is the challenge.
We can liken the task to searching for diamonds in a giant pile of sand. Storing the sand is easy, but sifting through it requires a special set of tools, as well as a sufficient understanding of what you’re looking for, why, and what you’re going to do when you find it.
Historically, data analysis has been a story of complexity, limited capacity, elaborate tools, cryptic results, and poor distribution. Special equipment was required, only a small number of people knew how to use it, and the demand on their time was high. Analysis also required moving data from a database to an analytics server, processing it and pushing it, back. Just moving the data was 80 per cent of the work - akin to trucking our pile of sand 10 miles to sift it.
Today, new, powerful data warehouse systems using in-database analytics can quickly ingest and process big data wherever it resides. What’s more, business users can now sift through data using familiar reporting tools, gaining easy access to powerful on-demand analytics and allowing data scientists to focus on building models instead of running reports. Best of all, these new solutions generally cost around 20 per cent less to build than traditional platforms and perform more than ten times faster. Not only does this keep costs down for the enterprise, this time saving means the data being analysed is, by definition, more accurate.
So how can you ensure the benefits of big data analysis are paying off across your entire organisation?
1. Ask yourself “Why”
Data analysis is more accessible than ever, and it can solve many problems - but not all of them. The key to identifying which problems to tackle is to start with “why.” Why are we analysing Big Data?
First, assess your strategic goals. These could be growing market share, controlling cost and risk, or understanding customer behaviour. Then, determine if using analytics will deliver value.
There are two important questions to answer: Can the company use data models to derive insight, and can it act on the results? Working through this process will help determine where your organisation can realise value from Big Data analytics.
2. Changing company culture
You may have a focused plan, great execution, the right technical platform, and the ability to operationalise the results of analysis; but without accompanying cultural change, those things will only deliver a fraction of the potential value of big data analysis.
Let’s go back to the diamond mine one more time. They have new sifting equipment that tells the miners where the highest-value diamonds are, but the miners aren’t authorised to react to the information.
The best equipment can’t make up for broken culture. Employees should be able to run analytics and see actionable answers on demand: a forecast of how close the sales team is to meeting this month’s numbers, a customer’s credit score, or a report of which advertising keywords to buy today. Armed with information, employees must also be comfortable and confident taking action before the value of the insight diminishes.
Building a culture that encourages constant testing and learning - as well as providing access to a flexible platform that can accommodate new ideas - will greatly improve the value companies can reap from big data.
It’s crucial to create a culture that rewards decisions and encourages analytics innovation, which may require modifying incentive and bonus structures. Not allowing employees to act is the most common point of failure for analytics projects - don’t make that mistake. It’s rarely mentioned in discussions of big data, but it can make or break an analytics initiative.
3. Maximising Results
Many companies are succeeding at their search for value in big data. They have the systems and infrastructure to capture and analyse Big Data; they have operational processes in place; and their employees have permission to act on the results. For these companies, the payoff can be dramatic.
For example, equity traders may need to buy or sell assets during the trading day to balance their portfolios, but one day’s Opera feed can contain data for 500,000 to 1 million trades. If portfolio risk can only be calculated overnight, then institutions are exposed to an unquantifiable amount of risk during each trading day.
Call centres use analytics to better serve customers, reduce churn, and cross-sell new products. By analysing a customer’s history and the actions of customers with similar histories, an analytics engine can recommend actions that will reduce churn, or suggest products or services that will be the customer’s next likely purchase. One call centre leveraged big data analytics and saw a 10 per cent reduction in churn, an 8% per cent increase in per call revenue, and a 12 per cent improvement in cross-sale revenue.
Health care organisations are using big data analytics when evaluating care quality and efficiency. Using traditional methods, analysing more than 700 million lines of claims data can take six weeks and a dedicated team of analysts, and only produce reports twice a year. With big data solutions, risk management teams can now run the models in 22 minutes and take immediate action to improve quality of care, reducing the window during which risk can go unnoticed from six months to less than a week.
Big data analytics are ushering in a new era of predictive insight that is changing how companies operate and engage with their customers, suppliers, and employees. To take advantage of the opportunity, companies must start with the “whys,” align analytics projects with business needs, and quantify the value that can be created. To realise the value, employees must have access to powerful, innovative, and proven technology, participate in the process, understand the results, and be empowered to act.
Get all of this right, and your diamonds will shine bright, creating competitive advantage and financial gain.
Michael Upchurch, Chief Operating Officer, Fuzzy Logix
Image Credit: Tashatuvango / Shutterstock