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The data and analytics landscape is changing fast, but if you can’t demonstrate the business value in AI, data and analytics initiatives it can lead to reduced budget and lack of involvement for these initiatives. A key factor is to quickly find out the current state of maturity. With our Rapid assessment framework, you can clarify your status – within a week.

Leaders need data-driven decisions to deal with today’s increasingly unpredictable world. And most agree that the transformation into a digital business age, where the shift to digital-centric business models for software-powered customer experiences and core processes is central, is highly dependent on infusing AI, data, analytics and other technologies into the company. 

Some companies accomplish this transformation more successfully than their peers.

Winning companies utilize data

What’s the secret behind their success? Based on my experience from several Nordic projects, an organization’s data and analytics maturity is essentially determined by how they utilize their data to get the most out of it. Data-mature organizations generally have more highly esteemed data and more sophisticated techniques for analysis.

Data and analytics mature organizations have the advantage of being able to spot opportunities way in advance whilst they’re still invisible to the human eye. Through leveraging the power of predictive analytics, organizations can use their existing data to anticipate what will happen in the future. Successful businesses are focused on making data accessible, reliable and compliant to empower critical real-time decisions.

What’s stopping businesses?

Others are not as successful. Organizational and technical challenges prevent some from unlocking the value of the data they already have. Some companies struggle to demonstrate the business value that heritages from using AI, data and analytics. This means that they won’t get any buy-in from management. Consequently, business outcomes will suffer. 

Let’s be frank here: we all know that getting investments for a changing landscape is not a happy place. An important component is to get to know the current state of maturity, where some of the key questions include:

-    Are you on the right path with your data and analytics goals and strategy?
-    What is your current data and analytics maturity?
-    Do you have time and investments for big strategy work?
-    Do you have the right capabilities?

Is your data and analytics pulse correct?

To help organizations speed up the assessment of the maturity, the Cognizant consulting team, and its AI and analytics advisory practice (AIA), has come up with a Rapid assessment framework. Recognized by analysts such as Gartner, Forrester and Everest Group, AIA advisory practice helps companies orchestrate capabilities across strategy, design, technology and organization to extract value from data.

The low-effort, quick assessment is an online survey, shared with key stakeholders, that enables your organization to evaluate your data, analytics and AI environment in a structured manner on all important parameters and assess the maturity from multiple dimensions using a statistical model. 

Assessment in core areas

Typically, the Rapid assessment for AI and analytics maturity is done in the following core areas:  

As part of the assessment, Cognizant also conducts interviews with CXO level stakeholders and transformation heads to understand the overall business objectives aligned to the digital strategy. Among other things, the assessment includes a detailed evaluation of stakeholder needs and priorities, analysis of current IT landscape vs. future state with detailed instructions on how to improve, and detailed value stream mapping.

This gives us a high-level understanding of the current state systems and analytics environment/capabilities explored across specified business functions. We will leverage Cognizant reference architecture to foster discussions across all the aspects of the value chain.

Provides a way forward

How can a company use the assessment results then? The results provide a direction of the next steps for the organization, e.g., how to organize themselves in data and analytics areas and how to build strong roadmaps further focusing on the following areas: 

-    AI Strategy
-    Data Strategy
-    Platform Gap Analysis
-    Operating model design
-    Data Governance design
-    Use case planning 
-    Business case development

This is an example of a key maturity assessment view for AI, a result of a Rapid assessment framework project:

Are you ready to take up your organization’s health check in the data and analytics areas? It can be accomplished within a week, including one workshop, and is a project that will truly kick-start your organization’s reality check when it comes to AI, data and analytics. Please send me an email and I’ll be hap

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