Essential Steps in Building a Data Driven Culture

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Data is the key to unlocking business insights and improving our decision-making, but how many of us can actually say that our business is pulling useful insights from the data it has available? Not many: Nearly a third of senior business leaders say they don’t have enough data to get insights they need, or that the quality of the data they have access to is poor.

Also, how many of us can say that we are satisfied with the outputs of our data and analytics strategies in saving or making money for our businesses? Again – not many as you would imagine: in a report by Eckerson, only 36% of respondents gave their BI program a grade of good or excellent.

It’s a shame, because never before have we had so much data available to us. Today, the global production of data is set to continue to grow year on year at a seemingly unstoppable rate and it’s important that senior information and analytics managers prepare today for the data challenges of tomorrow.

The growing surge of big data and the wealth of new software solutions is promising to act like a virtual Swiss-army knife that has added an extra-layer of complexity in building a data-driven culture.

It’s important to bear in mind that building a data-driven culture is more than just having access to the right data and technologies. Involving your workforce, especially the front-line and business users – the ones who have a direct involvement with the data, analysis, insights and decision-making is absolutely essential to achieve success in breeding a data-driven culture.

Setting Realistic Expectations

To get the most out of your analytics strategy, the first step should be to properly plan how you are going to transform your data first into insight, then into outcomes.

Understanding the key challenges the organisation is facing, what insight is needed, and then finally what data sources are available will help solve these challenges.

Strategy leaders need to get creative with the data available to them; the growing wave of big data has brought with it an influx of unstructured data that has yet to be utilised. If applicable to your organisation, the potentially unprecedented benefits achieved by tapping into the large volumes of unstructured data such photos, videos and audio clips cannot be understated.

Other factors are also important; determining access speeds to certain data sets is required to the ensure data still has value when analysed, also plays a part. The ‘best before date’ on data is constantly shortening thanks to the constant stream of new data being generated across the world. This means that strategy leaders need to understand what data sets are vulnerable to this shortened shelf-life and take the appropriate measures to get timely or real-time access to this data.

It’s not uncommon to see organisations who have deployed analytics solutions across their organisation become disappointed and disillusioned with the results achieved. Putting in the ground-work to properly plan the scope of your analytics project will go a long way to managing these expectation and ensure that KPI’s and targets set at the start of the project are realistic.

Infrastructure and Resources

So, expectations have been set and potential outcomes formulated. Now it’s time to look at the IT infrastructure and resources within your organisation to understand whether they align with the strategy put in place.

Legacy technologies that aren’t capable to cope with the demands of big data are simply no good and are becoming obsolete. Ensuring your IT infrastructure is built with modern technologies, capable of bringing in data from any source, storing it in a quickly accessible format (real-time), and integrating all organisational data (structured and unstructured) into one centralised repository is critical.

Further to this, without the right mentality engrained into the heart of the organisation, any analytics project is destined to fail. Employees’ skill sets and mind sets need to be reviewed so that necessary changes can be made. For example, you may discover that a number of your employees don’t have the analytical mind-set required to contribute to a data-driven culture. In this instance, your option would be to look at hiring new staff or training existing ones so that they have the right mind-set and necessary skills to contribute to the overall success of the strategy.

Enabling front-line employees and business users

Once you’ve built the necessary infrastructure and ensured staff have the correct mind-set in achieving a data-driven culture, the last step is the execution of the strategy.

An underpinning factor contributing to successful outcomes is ensuring that the analytics platforms chosen are able to be used by all of the relevant front-line employees and business users. Often these types of users aren’t the most technical and the strategy can thus fail if you haven’t taken this into account

Providing them with a self-service solution that is both easy-to-use and intuitive to prevent them relying on the IT department for support or the organisation investing in expensive consultancy days enabling them to complete their jobs quicker and easier is essential.

Finally, and most importantly, strong leadership from the decision-makers responsible for pushing forward the organisation is needed to convert the insight garnered from the analysis into deliverable action.

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