Data Science Roadmaps

Effective data science starts with clearly defined business questions. With a clear roadmap you can quickly generate clear insights that bring immediate business value. A roadmap sets out a clear path from high-level vision to detailed technical and staff planning.

Positive and easy to engage with, helped us to develop a simple and clear data science plan that added significant value to our thinking and approach

Joanne FairCo-Founder FutureWork Studio

How it Works

Define the target.

We work with you to define the stakeholders in your business ecosystem, and the value that you provide to each of them. Using our methods drawn from Agile Development, we help you define how you can take your business to the next level by leveraging Data Science in a way that provides immediate impact.

From data, to insights, to action.

Based on your company’s Data Science Vision, we use quantitative methods and psychological theory to define which of your stakeholders you can target to have the highest impact on your bottom line. Strategy is about what you are going to do as much as what you are not going to do, and your Data Science Roadmap helps you understand which is which.

Get the rubber on the road.

With your Data Science Vision and Strategy defined, it’s time to put it into action. We work with you to determine a set of Data Science products that will leverage your data to maximise your company’s value to your prioritised stakeholders, as well as helping you understand the people and resources you’ll need to build them.

Where to Start

Align data with your larger goals.

Move data science from a niche side project to a core part of the business.
Develop, test, and deploy the top technologies.
Avoid analysis paralysis.
Align data science with business vision.

1. Define the organisational vision and where data could be integrated to best effect.

2. Prioritise existing and new business processes that could be optimised with current and new data.

3. Translate between analytics and business impact.

4. Ensure that data science outcomes will be integrated into core business strategy.

Demonstrate the impact of decisions.

Demonstrate how data science priorities contribute to business priorities.
Assess business opportunities for cost savings, new revenue, and process optimisation.
Identify early wins and big-impact items.
Structure, store, and access data as an asset.

1. Take a data inventory and assess the potential for a structured data asset.

2. Establish the business value of the most critical data and algorithms.

3. Assess the optimal data science workflow and provide approximate costs, timeline, and technical requirements.

Include data in business processes.

Build human capability to use data.
Create a digital talent recruitment strategy.
Leverage existing internal data sources to optimise current business processes.
Consider data transparency, privacy, and ethics.

1. Link the structured data asset to business operations.

2. Create technical documents that communicate the roadmap information to data specialists.

3. Assess need for data protection in collecting, processing, and utilising user data.

3. Identify core metrics and evaluation strategies for the data science strategy.

Successful execution starts with a fully committed leadership.

Create an effective environment for using data in the organisation.
Set data-relevant organisational, governance, and cultural goals.
Communicate in leadership-ready language.
Optimise data for the business end-user.

1. Clearly communicate what is needed for the transition.

2. Identify shoestring, lean, and high-end options for implementation.

3. Give business decision-makers tools to communicate the roadmap information to non-data specialists.

4. Build in considerations for transparency, trustworthiness, and inclusion.

Frequently Asked Questions

What if I don’t have a lot of data?

You don’t need to have a lot of data right away to start thinking about how you will use the data you collect as your business grows. Even if nothing you do is online, we can help you dig into your business operations and make sure you get the most out of all your record keeping.

How much time will building a Data Science Roadmap take?

Our process is developed for remote settings and specifically aimed at leadership team members who are already very busy running their business. We use quantitative methods and targeted conversations to minimise the time required to get you from start to finish within around six hours of meetings over six weeks.

I already have a company vision - why do I need a vision for my Data Science?

A Data Science vision complements your business vision, and defines how data specifically contributes to bringing your operations to the next level. The vision you develop forms the beginning of your Data Science journey – you need to know where you want to go before working out how to get there.

Isn’t Data Science really expensive? Only for really big tech companies?

Data Science is for everyone, and can be as cheap or advanced as you wish. While it’s true that Data Science plays a central role in major tech companies like Google or Amazon, its impact can be felt for even the smallest of companies. In fact, developing a Data Science roadmap early can be one of the easiest and fastest ways to make sure your business grows as fast as you know it should.

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