It seems that everywhere you go, consumer data is being harvested, packaged and analysed to provide insight for more effective marketing campaigns:
- in the US, large cable and telecoms groups are lobbying for diluted privacy laws to allow them to sell data on their customer’s phone habits; and
- in London, even the Rubbish Bins are watching you…
Growing Interest Amongst SMEs
Whilst ‘Big Data’ is a concept typically associated with larger corporates, smaller organisations in areas like retail, healthcare, manufacturing and government are beginning to see the potential benefits of getting to grips with the volumes of data they’re already gathering but aren’t necessarily exploiting. Recent research by SAP shows that 76% of the interviewed senior executives of SMEs view Big Data as an opportunity.
Overcoming the Key Challenges
However, there are a number of challenges to building an effective Big Data solution for SMEs. What can be done to overcome them?
- Limited Data? – SMEs can aggregate their own structured (transactional) and unstructured (social media, web traffic and customer sentiment) data with data sourced from suppliers, vendors or public sources to build a more complete data set for more detailed analysis.
- Expensive? – companies often cite the lack of storage capacity and the growing cost of storage within traditional databases. However, SMEs can now turn to increasingly affordable big data storage solutions, such as Apache Hadoop, which are available on premises or in the cloud. IBM has also committed to provide $5bn of global financing to SMEs that want to leverage Big Data and analytical technologies, so far helping over 8,500 companies.
- Maintaining Data – maintaining data on a large number of SKUs is time-consuming and companies often cite more pressing demands on IT’s time. This will always be a challenge for a resource-constrained SME without dedicated data-personnel, but the more the analytical process becomes a routine part of operations, the more powerful it becomes.
- Insight – The analysis must also make sense in the context of your business. There is little point limiting locational analysis to revenue trends if your key metrics focus on profitability. Also, just because a statistical result is the product of a complicated algorithm, doesn’t mean it is relevant for your business.
- Data management solutions are becoming more affordable and SMEs can sometimes underestimate the value and potential of the data at their disposal;
- The most effective data analytics processes are continuous, not one-off exercises;
- Working backwards from the questions you would like answered will help to structure more effective analysis;
- High quality and actionable data can be a key driver of value.
SMEs may have to get more creative to efficiently engage with Big Data. But there are fewer and fewer reasons why it should be limited to the larger corporates.