Data Strategy Consulting

The businesses of the 21st century have an invaluable resource to exploit – data. As they are available in abundance and huge volumes, organisations often lose sight on how to utilise their potential fully. 

Formulating a big data strategy can help businesses overcome such challenges and gain a competitive advantage. A data-driven approach will also aid in unlocking the full potential of big data and make the utilisation process more efficient.

Any big data strategy must be embedded in the organisation’s process for maximum return-on-investment (ROI). Here are five crucial steps a business can follow in developing a data strategy and becoming a data-driven organisation.

If you want to formulate a big data strategy for your organisation, leave the hard work to us. Discover how we can support your organisation in achieving your data goals. Get in touch with our experts today.

1. Establish Your Data-Driven Objectives

The first step towards creating a big data strategy is to comprehend the corporate objectives of your organisation. Learn what the organisation is trying to achieve with the power of big data. 

Of course, increased sales and revenue will probably be the primary intentions, but they are essentially the results of meeting specific key performance indicators (KPIs). The key is to understand how specific KPIs add to the business’ success and how employing big data technologies can further enhance their performance.

Along with complementing corporate objectives, a big data strategy must also address critical business obstacles. The involvement of primary stakeholders, right from the start, can enhance the process of identifying business objectives and barriers.

Key stakeholders will include executive sponsors, the right talents, and potential troublemakers. The reason why it’s critical to spot the troublemakers is that you will be aware of the hindrances they might cause down the road.

2. Measure Your Current Data Maturity Level

Assessing the current business state is a form of a gap analysis, analysing current business processes, capabilities and policies, technological assets, data assets, and data sources. By doing so, you’ll have a firm idea of how the existing state differs from the future desired state.

For example, the motive behind formulating a data strategy could be to mitigate security risks. Then the current state assessment would include evaluating the IT department capabilities and policies, data infrastructure, and data security features.

Along with assessing the current state, it is vital to identify and promote the data evangelists of your organisation. Evangelists are the resources who are fully aware of the potential of big data and are already capable of using analytics to make data-driven decisions. Including these people will enhance the scope of the data strategy.

3. Identify and Prioritise Data-Driven Business Cases

In this step, you need to conceive how different types of data analytics, namely descriptive, diagnostic, predictive, and prescriptive, can help the organisation nurture. For that, you need to create use cases, which are detailed documentation of how big data can assist in achieving a specific business objective.

Once the use cases are defined, the next step is to prioritise them based on their resource requirements, budget, and business impact. By doing this exercise, organisations can quickly identify the big data initiatives that will offer the utmost business value and channel their efforts accordingly.

Techniques such as business case discovery are useful for this purpose. A discovery workshop is a structured approach to stimulate discussions and ideas among the primary stakeholders of various business units. Such a system will help in recognising the use cases with the highest business value and success rate. 

4. Develop a Big Data Blueprint

Developing a big data blueprint will be the most time-consuming part of formulating the strategy. The roadmap considers the current state assessment and the prioritisation of use cases. The sponsors and primary stakeholders will have a critical role in tracing the roadmap.

The big data roadmap will outline how the desired future state will be attained. It will define the order in which the use cases will be executed and the capabilities that will be expanded in the coming years.

The roadmap must also focus on identifying the weaknesses of the infrastructure, technologies, and tools used and suggest means to improve them. It must also enhance the current business processes and recommend how individuals can be trained to attain the desired levels of skill set.

Combining the information acquired from the current state assessment and use cases will help in identifying the big data initiatives that have the maximum potential. A well-defined roadmap will contain big data initiatives that will be implemented.

5. Orchestrate a Data-Driven Change Management

Prepare, support and help individuals, teams and organisations to create a successful data-driven transformation. Change management is an integral part of a big data strategy, and its effectiveness will have a significant impact on its success.

Along with organisational-level changes, a data-driven change management will seed cultural, technological and business procedural reforms. Since big data would mean the volume of data being dealt with is enormous, strict policies revolving data governance should also be established.

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