Realize the Full Potential of your Data Science Investment | Insight

What can you expect to learn from this article?

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In this article, we define the four main obstacles for companies to realize the value of their data science team.
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We visualize the Data Science Lifecycle as a toolbox for turning your data science team into an asset rather than an expense.
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We help you ask the right questions to identify the underlying issues with your data science team and provide you with the first step to realizing the full value of your investment.

Companies generate huge amounts of data, but a small percentage is being transformed into information that could potentially be used to drive business. Why? Because your data science team is busy with maintenance, and often, only 20% of data scientists' time is spent on actual data science tasks. Having the right approach is key to giving your data science team the optimal conditions to deliver value, and this brief provides the what, why, and where to start.

Are you getting value from your data science?

Research shows that most data scientists spend 80% of their time on locating and organizing data – a time-consuming process that is not contributing to the bottom line. Imagine that a seamstress had to locate a needle in a haystack before being able to patch a pair of pants. The same logic applies to your data science investment that spends 80% of their time preparing to do the intended job. Their time, efforts, and talents are poorly spent. Taking a closer look at the Data Science Lifecycle can help you steer clear of obstacles ahead.

Four main obstacles

If you want to transform your data science team into a powerhouse that converts data into actionable information, there are four main obstacles to overcome.

Not delivering the expected value

Since your data science team is spending 80% of their time on preparing and organizing massive amounts of data, they simply do not have the time to analyze and transform data into something valuable.

Little control over your data

Without tools that can help your data science team do the time-consuming work of structuring data, anonymizing, and preparing it for use, it is easy to lose track and overview of your data. Losing overview can lead to solutions that are built on flawed or incorrect data sets or simply overwhelm the team with tasks that take up all their time to think of a solution.

Lack of governance and documentation

Without the right tools, it is difficult to track your actions and, therefore, difficult to evaluate and improve in the future. Without governance, you often have to loop back and redo parts of a project if not the entire thing

Data not utilized to drive your business

Your data is such a big mess that your data science team is trying to keep track instead of being used to make vital business decisions. Often doing proof of concept that ends up not working or not focusing on what drives business.

Getting it right

So, what to do next? Below is a visualization of the Data Science Lifecycle. To overcome the challenges of getting from data science, it is important to understand the lifecycle, which in many cases could be depicted as a spiral, as we continue around the loop once we have new information. Underlining the importance of getting the steps right.

Below, we present the ways in which we can assist you in transforming your data science department into an asset instead of an expense.

The challenges are all a common part of the stages in the Data Science Lifecycle and are presented in some stages more than in others. Depending on the scope, the use of tools can vary, but most projects will involve an analysis of all six stages of the Data Science Lifecycle.

As an example, Data Preparation & Exploration should take up around 30% of a team's time but often comes out at 50-60% time spent, based on previous projects.

Utilizing the right tools i.e. Grace AI to optimize your business and provide your team with the right tools is one way of improving the ROI of a data science investment.

We can assist you every step of the way, supported by the right tools. With the help of AI, you can free data science teams' time to tasks that move the needle – not just spending hours trying to prepare, clean, and structure data.

We help you answer questions like:

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Where can I optimize the business' artificial intelligence?
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Why can't we get a live data/overview/dashboard?
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Why are we not using data to make decisions?
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We hired a data scientist (team) a year ago, why are they not delivering any value to the organization yet?

At 7N, we help clients define and locate the potential outcome of AI with the right tools. One of the tools is the 2021.ai Grace AI platform that helps us build out your data science team's capabilities in your organization. We can ensure that your data science work stays a valuable asset within your organization, should a data scientist leave your organization. Thereby, you do not risk losing the ability to continue to run and enhance your data science projects.

We can help you...

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Create a strategy to optimize your data science department
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Free up data scientists' time by providing the right tools and strategies
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Get access to an overview of your data/model
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Get your documentation right and be on top of governance
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Use data to drive business impact and make decision

The first step

Across the span of digitalization, there are many potential issues, but also substantial gains. The future is characterized by digital products and services that are delivered through modern core architecture, digital platforms, and agile fragmented organizations.

We can help you ask the right questions and find the answers. We offer objective and data-driven advice by enabling technology throughout the solution.

Typically, a project starts with an as-is assessment with the help of Grace AI – a first-class tool for development, operations, and governance of data science, machine learning, and AI. Grace can help manage your data, so your data scientist can spend their time on what is important – turning data into valuable information that can drive your business forward.

Learn more

Across the span of digitalization, there are many potential issues, but also substantial gains. The future is characterized by digital products and services that are delivered through modern core architecture, digital platforms, and agile fragmented organizations.

We can help you ask the right questions and find the answers. We offer objective and data-driven advice by enabling technology throughout the solution.

Typically, a project starts with an as-is assessment with the help of Grace AI – a first-class tool for development, operations, and governance of data science, machine learning, and AI. Grace can help manage your data, so your data scientist can spend their time on what is important – turning data into valuable information that can drive your business forward.