Why SMEs need to unlock the potential of big data
It’s never been more affordable or easy for small businesses to take advantage of big data and analytics. A recent Computing survey discovered that SMEs, while confident of their innovation potential, are much less sure about using data and advanced analytics to gain an advantage and insight into their organisations.
However, big data can be a massive advantage for all businesses. The key is understanding and unlocking its potential…
Big data strategies
In a survey of 125 SMEs conducted by Computing, over 75% of respondents said that they did not have a strategy to use more analytics and business intelligence capabilities.
Data volumes are increasing at an incredible rate, with 90% of all data that has ever been created coming into existence over the past few years (according to CompTIA’s SMB and Technology study, March 2015)
The increase is largely attributed to data generated by machines, both industrial and consumer devices (such as health trackers like FitBit).
No matter where the data comes from, its existence provides new opportunities for businesses and their current practices. Big data can help a business find new efficiencies and processes internally, discover potential customers externally, keep on top of new trends in their respective industries, and predict what their current customers might want next.
However, a major challenge for smaller organisations is in finding the potential and moving as quickly as possible to use it before larger competitors do.
Small- and medium- sized businesses that began in the data age (or those that can transform with relative ease) can move quicker to seize new business than those who are using old technology and practices. Many still labour under the illusion that big data technologies are only good for larger enterprises, or that ‘big data’ is a buzz phrase that isn’t really relevant to their business. Others think it will only become relevant to them in the future. Both beliefs are high risk in an economy where big data technology moves incredibly fast.
Making it work for your business
A key issue for small businesses who want to use big data is finding a way to process and store it efficiently and cost-effectively. The technology they need to use to get the full advantage of big data has to be easy-to-use, relatively low cost, and scalable.
The great news is that affordable and accessible systems (including cloud software and analytic tools like Google) for unlocking big data do exist. Any business can be data driven as long as they have the infrastructure for top optimisation, software that can access, manage and analyse data types, and a big data platform that can deliver on business outcomes.
Good data management is key, and there are a number of ways that smaller business can successfully unlock the potential of big data:
- Unify data management
Data should be managed and aggregated in a unified way to allow for easy access to insights for all parts of the organisation
- Take a holistic approach
The business needs to align with a comprehensive big data strategy
- Think of information as an asset
All information has potential and it should be governed for end-to-end in a way that shows this; balancing value, cost, and risk
- Make things agile and scalable
Having a flexible IT investment plan will allow for quick deployment of systems that can work alongside any existing technology and allow for scaling up.
Good data management and a successful strategy is key to unlocking competitive advantages, however, another important element is having skilled people to develop the ability to exploit the information.
While the majority of IT SMEs are currently lacking employees who work in data analysis and business intelligence, the attitude to the value of these roles is changing. Soon it will be necessary for more data analysts to come on board to take advantage of what big data can offer.
To succeed, SMEs need to get over aversions or misunderstandings about the current technology set, update their expertise, and critically, they need to think big when working with big data.