Big data and analytics have rocketed to the top of the corporate agenda. Executives look with admiration at how Google, Amazon and others have eclipsed competitors with powerful new business models that derive from an ability to exploit data.
They also see that big data is attracting serious investment from technology leaders such as IBM and Hewlett-Packard. Meanwhile, the tide of private-equity and venture-capital investments in big data continues to swell.
The trend is generating plenty of hype, but we believe that senior leaders are right to pay attention. Big data could transform the way companies do business, delivering the kind of performance gains last seen in the 1990s, when organisations redesigned their core processes.
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In our work with dozens of companies in six data-rich industries, we have found that fully exploiting data and analytics requires three mutually supportive capabilities. First, companies must be able to identify, combine and manage multiple sources of data. Second, they need the capability to build advanced analytics models for predicting and optimising outcomes. Third, and most critical, management must possess the muscle to transform the organisation so that the data and models actually yield better decisions.
1. Choose the right data
The universe of data and modelling has changed vastly over the past few years. The sheer volume of information, particularly from new sources such as social media and machine sensors, is growing rapidly. But mastering that environment means upping your game, finding deliberate and creative ways to identify usable data you already have and exploring surprising sources of information.
Source data creatively
Often companies already have the data they need to tackle business problems, but managers simply don’t know how the information can be used for key decisions. Operations executives, for instance, might not grasp the potential value of the daily or hourly factory and customer-service data they possess. Companies can impel a more comprehensive look at information sources by being specific about business problems they want to solve or opportunities they hope to exploit.
Managers also need to get creative about the potential of external and new sources of data. Social media are generating terabytes of non-traditional, unstructured data in the form of conversations, photos and video. Add to that the streams of data flowing in from sensors, monitoring processes and external sources that range from local demographics to weather forecasts.
One way to prompt broader thinking about potential data is to ask, “What decisions could we make if we had all the information we need?” Using that logic, one shipping company improved the on-time performance of its fleet by tapping specialised weather forecast data and live information about port availability that it hadn’t realised were available.
Get the necessary IT support
Legacy IT structures may hinder new types of data sourcing, storage and analysis: many were built to deliver data in batches, so they can’t furnish continuous flows of information for real-time decisions.
Business leaders can address short-term big data needs by working with CIOs to prioritize requirements. This means quickly identifying and connecting the most important data for use in analytics, followed by a cleanup operation to synchroniae and merge overlapping data and then to work around missing information.
Such short-term tactics may lead companies to vendors that focus on analytics services or emerging software. New cloud-based technologies may also offer ways to scale computing power up or down to meet big data demands cost-effectively.
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