Our bodies can handle a certain level of toxins in our blood. Our liver, for example, helps breakdown these toxins. Too much toxicity in our bloodstream and our organs start shutting down.

The data generated from business processes, will need cleaning and conforming before business units can safely use it. Leaving this task to the data consumers will have a direct impact on their productivity. It will cause them to be less effective at making informed decisions and driving business process improvements.

A company I worked for had a small finance department who received daily excel files containing transactional history from several systems. The team of three would spend upwards of 15 days per month, collating the records into the ledger system and manually reconciling the figures. Monthly management reports were compiled from the master spreadsheet and distributed as excel tabular reports at their earliest opportunity, generally by working day six of the following month. The sales team had a very similar approach when submitting their monthly sales targets.

Their direct competitor was able to provide the business with consolidated management information reporting from across the organisation by the first working day with a considerably fewer FTE. This allowed them to react to market conditions with speed and efficiency. As the company's data maturity evolved, they started predicting market changes, proactively enabling them to grow their business strategy from these insights.

The single most crucial element in the success of an enterprise initiative is in the treatment of your data as a strategic asset. This mindset shift, driven from broad leadership agreement, will help to steer the company towards a cultural change in its view of data and how to utilise this valuable resource best.

You will need to create a strategy to advertise how data will benefit your company and the steps you need to take to deliver short, medium and long term business value to reach your goal. This plan must align with your broader business strategy to ensure you are focusing your efforts where results are needed most. The message your data strategy portrays, the tone used, and the story it delivers, must resonate with the whole organisation to gain buy-in to your data initiatives.

Your approach will evolve, as new information is made available to you. It's essential to review your plan frequently and pivot your strategy with your business needs and priorities. Delivering small incremental improvements to achieve your short, medium and long term goals will give you the flexibility to change course with the least impact on IT and the business.

Avoid the temptation to buy a big shiny new solution from a technology vendor until you know the problem you're trying to solve. Such solutions, although they may offer great promises to fix your data issues, rarely deliver on their pledge, in isolation. It's your data strategy that should drive your technical requirements. Your short term goals are unlikely to need any significant technology changes, so hold off pulling on the purse strings until you need to.

You're unlikely to inspire your stakeholders with a "data lake" or "machine learning". The business whats to know what problems you plan to solve through the data initiative and how you plan to address them in business terms. For example, the opening to your data strategy statement may read;

"We seek to deliver brilliant customer engagement by providing powerful data insights into the products and services we offer. This will allow our sales team to focus on the market segments that resonate most with our brand values."

By focusing on the real aims of the initiative, you are far more likely to resonate with your intended audience.

Creating a data strategy and delivering benefit to your stakeholders can seem a daunting task. The key is to think big but start small. Allow your data initiative to evolve with the business needs. Break the delivery down into small incremental releases and expect to pivot your strategy often. Fully engage the business in your feedback loops to ensure you stay relevant to their needs. Harness the power of new technology where appropriate, but avoid letting it dictate your data initiative.