How data can help SMBs with digital transformation
Improve collaboration, enhance customer insights and more by making data a key part of your digital transformation strategy
We are living in an increasingly data-driven world, with access to unprecedented amounts of information. The incremental nature of the digital economy is showing no sign of slowing. A company's ability to compete will increasingly depend on it's ability to make faster, more informed decisions. Here, data can be the difference between keeping above water, and sinking.
The challenges for large enterprises with digital transformation undertakings are well documented, and many have implemented tools to make use of much of the data they generate. But how are SMBs coping with digital transformation?
According to a study from SMB Group, 48% of small and medium businesses are planning to engage in activities to help them adapt and transform their businesses for a digital future, with 36% already implementing plans. SMBs are most likely to put the money towards improving employee productivity, streamlining the customer experience, and improving decision making.
This final point is an increasingly important one. The more information and data a business has, the more able it is to make wise decisions and investments in technology and people. But information and data alone don't offer the full picture; so how can small and medium businesses use the information they have and turn it into actionable insight for digital transformation?
If you've recently invested in tools to aid collaboration, data can help you establish what is being used effectively and what is redundant, the type of staff need more of. Even with small teams, data can highlight opportunities for improved ways of working, or whether additional support is needed for processes that are working well.
Data can also be used to gather information on current projects, for example marketing campaigns or internal workflows. When the data is collected across a project and has been analysed by the teams, it is much easier to identify methods for improving ways of working, which in turn can offer insight across different parts of the business.
An important part of this is educating employees about what data analytics is, and what business problems it can be used to solve. This, in turn, will help transform the working culture from being one of seeing known facts, to focusing on the unanswered questions and using data to drive those decisions based on the answers.
Collaboration is not limited only to employees. Analytical insight deduced from data will increase the value of the wider business in the eyes of potential partners. Collaboration across businesses could result, with benefits offered in return from the sharing of data. Alternatively, data can be viewed as a commodity, and once it is centralised and analysed, it can be sold to raise profits.
An extra degree of caution should be exercised when using data as a tool to increase collaboration across businesses. Data spread across disparate digital applications can make it more vulnerable to cyber threats. The use of different defences from business to business can even detract from overall security, with IT departments having to navigate software they may not be familiar with. Moreover, issues regarding intellectual property rights have been known to arise.
Smaller businesses can't afford to spend lots of money on suboptimal campaigns in the same way as larger organisations, and that means that identifying areas where cost and time savings can be made has a tangible value. Data can be used to highlight projects and tools that are working well, as well as ones that aren't being used to their full capacity, such as cloud storage or software licences. Using data in this way can add up to bigger savings in the long term.
Data showing usage patterns for software or tools in the business can also be a good way to identify ways to scale. It can be used to highlight periods of high demand for resources, and in turn where investment is needed in the future.
Digital transformation itself is a constant process, and therefore there will always be new efficiencies that data analysis can identify as the business and the technology within it evolve.
Data can help identify areas where routine tasks can be automated in a business, however large or small. One of the advantages of introducing automation as part of a digital transformation strategy is that it can be used in just a few small areas without needing significant investment, and then scaled up across different parts of the business as and when it's needed.
Artificial intelligence (AI) applications that feed on data are increasingly found at the heart of digital transformation. Simply, the greater quantities of data that are channelled into AI applications, the more information that can be processed, producing business-insight and subsequently helping to induce wider digital transformation.
Enhanced customer insights
Data can provide insights into customer behaviour that will enable even small businesses to identify how they can optimise a customer's experience, whatever industry the business may operate in.
Being able to deliver recommendations and special offers to customers based on factors like location and purchase history is much more likely to cultivate loyalty. Even simple data gathering tools can help improve the customer experience for small businesses without needing a costly big data system.
In the long term, data is also valuable for predicting trends and identifying new business opportunities, whether that be economic trends or customer spending patterns.
A study from Econsultancy and Adobe found that data was a key area of investment for companies, with 65% of respondents saying that this would help them to better understand customer experience requirements. This was a more popular priority than optimising internal collaboration, or optimising workflows within the business, showing how important data can be in identifying points of friction and improving customer experiences.
None of the strategies above require huge investments in expensive software or hardware. Often, simple data analytics tools that integrate with existing technology can draw together enough data to be able to inform decisions in an SMB without needing to spend lots of money on all-singing, all-dancing systems designed for larger businesses.
What is vital, however, is that the data is of sufficient quality so that it can be understood and easily used by analytics programs and applications. Good business decisions will only be made on the back of good data.
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