Is ‘Big Data’ essential for an organisation to derive meaning and value from its data?
We are increasingly seeing successful businesses seeking to remain competitive, relevant, and driving engagement and sales by focusing on customer insights. These companies have recognised what Forrester has identified as the top two priorities for business: Revenue and Customer Experience.
Forrester states: Businesses are drowning in data but starving for insights. Worse, they have no systematic way to consistently turn data into action. Demanding customers and competitive pressures require firms to treat insights – not just data – as a business asset.”
The rise of data analytics is critical to harnessing the information required to understand customers, right down to the individual.
In the early days of Big Data, Gartner stated all organisations would face similar challenges “… Through 2015, 85% of Fortune 500 organisations will be unable to exploit Big Data for competitive advantage.“
Despite the complexity of the challenge, it is always important to make a start, no matter how modest the start may be.
But what happens when the time or money isn’t available to make the accompanying investment in a big data strategy and execution? What is the alternative to gaining customer insights without the large investment in big data?
Understanding What Big Data is – and Isn’t
The term ‘Big Data’ can be inherently misleading and may result in confusion about what is required to generate clear insights into customer journeys and their experience of your business
Gartner again defines Big Data as “… high-volume, high-velocity and/or high variety information assets.” Gartner has also identified that Big Data has progressed from being hype (lacking substance) to actually adding significant value to organisations in areas such as customer insights.
As Big Data begins to mature and data analytics become ever more important, what is clear is that that organisations that don’t have a strategy for collecting, storing and analysing data (from a wide variety of sources) will be left behind.
Is Big Data Affordable?
Often one of the significant blockers for organisations seeking data insights is the lack of knowledge and perception of the budget required to implement a Big Data strategy. Often an organisation may look at large data projects in train elsewhere and be scared off by the reported price tag and rule out any significant Big Data initiatives of their own.
However, being informed and smart about the approach to data insights means that large budgets for Big Data project up front aren’t always essential.
What is essential is that the business is focused and committed to creating effective strategies and actions that will drive outcomes from its data, with regular review points to gauge the effectiveness of customer insights that are being derived.
So how can organisations achieve this?
Start Small and Get Bigger
Getting quick wins is always a great way to build momentum. Start simple: Identify the areas within the business where data and insights will be useful and drive the team to build and visualise data and information in these areas. Customer data-driven insights may not initially lead to an increase in sales, but could:
- Reshape the marketing and sales strategy
- Drive operational and financial performance improvement
- Improve risk and compliance management
- Help to shape new product and service innovation
Targeting these areas will help focus and chunk down the task at hand, minimising the budget and time risks.
Where is the Data/Information?
The increasing focus on data analytics shows that the value is being derived by combining data from mobile and social media, with new use cases that can be supported by the cloud – what Gartner calls the “Nexus of Forces”.
There are unused sources of data in almost all sectors and business (small or large), generally taking the form of operational data collected in the normal course of business. For example, operational data, externally-sourced data from syndicated data providers and public data and social media data can be blended to track product and service performance sentiment about the business.
Gartner also coined the phrase “enterprise dark data” – the under-utilised information that has been collected for a single purpose, then forgotten or archived. Organisations can capitalise on what is a rich treasure trove of internal emails, contracts, reports and other types of data by looking for patterns, lead indicators and correlations. There are nuggets that exist in this type of data that provide historical sentiment and potential opportunities.
So what skills are required to analyse the data?
The Data Scientist
The emergence of the role of the data scientist is perhaps a natural evolution of trying to derive value from large swathes of data. Often considered a unicorn in Big Data, effective data scientists are rare because they embody are broad range of skills such as:
- Data curation management and preparation
- Analytic modelling
- Business modelling and analysis
Also, many “soft” skills are essential to this role, including:
In establishing and setting up data insights strategy, the right skills is a must particularly if the Big Data strategy is immature. Whether it is an outsourced function, internal hire or bringing in subject matter consultants for this, being aware of and starting with the right skills and experience will be critical to success.
The Rising Influence of the Customer Experience
Understanding customer behaviour and accessing data insights to manage, change, improve and grow business is essential and to be frank, this is a must for a modern business.
What is important to recognise is that you can progress in small steps. Recognising that compiling a variety of data from a range of sources that produce high volumes is in fact “Big Data”. Most organisations do not need to start big: they can start with existing data sets and together with the right strategy, skills and focus, can build affordable and high value repositories that deliver significant insights.
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