Sherlock Holmes understood the value of data: Do you?
Underutilised data prevents organisations from properly measuring effectiveness and achieving great customer service.
“I have no data yet… It is a capital mistake to theorise before one has data,” said Arthur Conan Doyle’s world-famous fictional detective, Sherlock Holmes, in the story A Scandal in Bohemia.
Published in 1892, Holmes was a data-driven detective, pulling together observations and facts until the motive for a crime was ‘elementary my dear Watson’.
Close to 130 years after Holmes uttered these words, organisations, amazingly, are still trying to puzzle their way out of business challenges without the right data. More amazing still is that these organisations have the data but, without proper data engineering, are unable to access it to discover the insights that could revolutionise their organisations.
Amongst Holmes’ famous turns of phrase, was his use of the word ‘elementary’, defined as dealing with the simplest facts of a subject – which are often rudimentary. It’s these often overlooked simple facts that regularly lead Holmes to both the motive and the killer. In business, these same simple facts about customers and business operations are also regularly overlooked. In my experience, this happens because they’re hard to get to and can quickly build into a body of underutilised data. As a result, an organisation can have a caseload of data but precious little insight. This poses a long-term risk to an organisation.
Enterprise data levels are growing
As recent research revealed, enterprise data levels are growing; the IDC predicts growth of 23%, as cloud computing and increased connectivity from the Internet of Things (IoT) become part of the business norm. This growth and increased connectivity could exacerbate the existing problem of major data levels but poor insight – especially if organisations lack a properly engineered data approach, backed up by a data-centric strategy.
Underutilised data stifles innovation
Without a strategic engineering approach, underutilised data will proliferate, and underutilised data prevents organisations from being effective, which means they’re unable to innovate. A data engineering approach can turn data into insight and transform an organisation’s operations. As the aforementioned whitepaper sets out, data-driven organisations are growing and are now feeling confident about navigating the future.
A business-wide approach
In order to prevent underutilised data building up in an organisation, this strategic and engineering-based approach has to operate right across the business. With data engineering, an organisation can visualise and improve the customer journey and the business processes it operates. With visualisation, we’ve been able to spot bottlenecks in business processes and customer pain points, then use data – as well as next-generation data tools such as machine learning (ML) and artificial intelligence (AI) – to develop new services or business process improvements to rapidly deliver business change.
It’s about more than the tools though…
Data engineering is about more than tools. Engineering, of all types, has innovated through careful planning and an architectural view of how the tools and the commodities they manage (whether that’s data or oil, for example) work. This means that every data engineering process includes the development of a bespoke roadmap for the client, which allows them to create data thought-leadership and develop a data-centric culture. With a roadmap, data engineering processes, and a data-centric culture in place, organisations are then able to realise a return on investment and be assured that the organisation has everything it needs in place to respond to changes in its marketplace.
If an organisation doesn’t have the full understanding and support of the C-suite, it can’t truly implement a data strategy that’s aligned with business goals, whether that’s an increase in revenue per customer, new customers, a reduction in costs to serve a customer, or perhaps to meet additional regulatory requirements.
Partnering to solve the data puzzle
In the development of a data-centric culture, organisations will typically discover gaps in their organisational capabilities. A study in Forbes found that a lack of skilled staff and inadequate business processes were the most common capability gaps. With the pace of change in today’s economy, organisations increasingly need to find partners that can accelerate their development and adoption of data engineering and strategy. Just as London’s Scotland Yard turned to Sherlock Holmes to get a result and fill in the ‘elementary’ skills it lacked, so too must organisations find partners like eSynergy to help them solve the data puzzle.