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Realising maximum business value in a data-driven world

Tue, 30th Jan 2018
FYI, this story is more than a year old

Traditionally, organisations have relied on IT specialists to analyse data and generate reports containing actionable insights.  However, this manual approach is no longer viable in an increasingly data-driven business world. It's time-consuming and error-prone, and it can't scale to handle growing amount of data that needs to be analysed.

As organisations strive to achieve an edge over their competitors, making use of the most accurate data in the shortest possible time is critical. To achieve this goal, increasing numbers of organisations are implementing a new breed of data analysis tools.

Designed to be used by people with little or no knowledge of data analytics, these tools can provide insights into data sets without the need for an IT specialist.

Democratising data

Incorporating intuitive interfaces, the tools make the task of analysing data sets and creating reports significantly easier, thereby enabling staff members to run their own queries quickly and easily. Rather than data being accessible only to the analysts, it becomes accessible to anyone who wants it.

The growing sophistication of these tools is allowing organisations to quickly gain significant insights that can drive real business value. These could include accurate reports on sales numbers, performance reports on production facilities, and forecasts of future customer demand.

The tools also act as a democratising force, putting powerful data analysis capabilities into the hands of much smaller organisations than has previously been the case. On-demand, cloud-based tools remove the need for large up-front investments and allow smaller firms to begin analysis activity almost immediately.

The challenge posed by the rising data tide

While these new data analysis tools have proven a boon for many staff and help them undertake a broad range of queries, when it comes to more sophisticated analysis it's a different story.

With data volumes growing exponentially, conducting more complex analysis still requires the assistance of a data expert. This is particularly the case when complex queries need to be run on data sourced and combined from multiple locations.

Unfortunately, this situation is not being helped by the fact that high-quality data analysts are in short supply. Any that are on the market are likely to command significant salaries, putting them out of the reach of all but the larger organisations.

Education providers are racing to offer more training in this area, but the time lag involved means current shortages are likely to remain a factor for some time.

Extracting the most value from the data you have

Faced with these realities, firms need to ensure they have in place a strategy that will maximise the value they can extract from the data available. The steps to take should include:

  • Define the problem: Be very clear on exactly what question you are trying to answer. What is the ROI on a recent marketing campaign? What impact have changes to a supply chain had on overall operations? To what extent is customer churn increasing? Where should new staff be allocated?  
  • Locate the data: Once the question has been clearly identified, determine the location of the data required to answer the question and how it can be readily accessed for analysis. Data sources could be held in a number of different locations within an organisation and also with external third parties. All should be assessed for relevance and value.  
  • Apply appropriate tools: Select the most appropriate tools to carry out the analysis and create the required reports. There is a large range of tools available on the market and it's important to opt for those that can add the most value to the business.  
  • Use experts where required: It's unlikely that most organisations will have all the skills required in-house to undertake complex data analysis. If the resources are available elsewhere, make use of external data experts who can augment internal teams.  
  • Establish a sharing culture: Data is likely to be spread across the organisation, so create a culture where people are happy to share and ensure their data sets are up to date. It could require some time to generate this kind of culture, but the long-term benefits will make the effort worthwhile.

By embracing the potential offered by a data-driven future, organisations will be well placed to improve their performance, overcome the challenge of competition, and enjoy future growth.

Adopting a clear strategy and making use of the new generation of analysis tools will help to reach this goal must faster.

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