Six Steps to an Executable Data Strategy

Six Steps to an Executable Data Strategy

Data has become an essential tool in today’s business landscape. However, taking advantage of your data requires a long-term and – most importantly – an executable strategy. 

The problem that many businesses have is not the lack of data, but how to make proper business sense of it. Data is being collected in myriad ways, yet according to one report, only 32% of data available to enterprises is used.

An executable data strategy seeks to avoid such waste and aims to define the technology, processes, people, and rules required to manage your information assets.

Building a data strategy is vital to remain relevant, competitive, and innovative in today’s ever-changing world. Only by acting on your data will you meet business goals and unlock operational efficiency, process optimisation, and crucially, faster real-time decision-making.

Here are our six steps to creating an executable data strategy for your organisation.

Step 1 Understand business objectives

Instead of gathering data for data’s sake, start by examining your business objectives. Once you understand these, they need to be aligned with your data strategy. Only you can understand your objectives and so it’s a time to reflect on your long-term goals.

Remember, data only has value when it has a function.

Step 2 Discover Current State

Discovery is performed through a series of interviews and documentation reviews. 

The initial discovery sessions are intended to catalogue the current state of data assets, data platform technologies, and any current data use cases. Once this is captured, the next step is to identify any gaps or challenges and then create a prioritised list of potential future use cases. 

Step 3 Data Governance

How you govern your data today, and into the future, is vital. As data platforms, and the ability to extract insights will develop and mature, it’s important to have a data governance program in place to react to their evolution.

Yet a balance has to be struck. Over-engineering such a program may slow down progress and limit business value. Therefore, assessing the core data governance capabilities of your organisation is crucial.

Step 4 Technology

The value which you get from your data is, unsurprisingly, driven by technology. For example, while we all use and depend upon Excel for many data tasks, there is a need to have a central system which ingests all your data and can analyse it properly.

This central system must support detailed analytics, is accessible to key stakeholders, and the data model which is being used can evolve in line with business needs.

Furthermore, where the data does not exist today, thought must be given to how data gaps will be filled e.g., can it be calculated or estimated?

Step 5 Skills and Capacity

A key factor that holds organisations back from becoming data-driven organisations is people. Technology can only go so far without the required human support. A data strategy will only be useful if it reflects the processes related to creating, sharing and governing such data. Also, the strategy will introduce more data and its analysis, and potentially new technology.

This requires a thorough examination and appraisal of the existing skillsets in your organisation and the potential to upskill key resources or hire new staff.

Step 6 The Executable Data Strategy

The above steps will lead to your data strategy and ultimately how your organisation will create a strategic advantage through the use of data. At a high level, the data strategy will detail the data platform architecture and how it is delivered, the data governance model, and the implementation roadmap.

While a data strategy is obviously about benefiting from your data, it’s also about building a culture within your organisation that appreciates the benefits of data-driven analysis and decision-making. 

It’s this cultural shift that will pay dividends in the long run.

For more information, get in touch with ProStrategy via email [email protected]