Last updated on May 2, 2024

What are the best practices for defining the scope and goals of a managed analytics project?

Managed analytics is a service that provides data analysis, reporting, and insights to businesses without the need to invest in expensive infrastructure, software, or staff. However, to get the most value from a managed analytics project, you need to define its scope and goals clearly and realistically. Here are some best practices to help you do that.

1 Understand your business needs

Before you start looking for a managed analytics service provider, you need to have a clear idea of what you want to achieve with your data. What are the main questions you want to answer, the problems you want to solve, or the opportunities you want to explore? How will you measure the success of your project? What are the expected outcomes and benefits for your business? These questions will help you define the scope and goals of your project and communicate them to your potential provider.

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Hitesh Chopra

IT Leadership, Service Delivery, Digital Transformation, Program Leadership, Certified Independent Director, EXECUTIVE MBA INSEAD , Former-Accenture, Atos | PMP| PgMP | PfMP | ITIL Expert, 301 x Top Voice Badge
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From my experience, we have to involve key stakeholders in defining scope and goal of the Project, understanding their requirements, expectation pain points Define business objective outcome that managed analytics project aim to achieve, Identify specific use case, scenarios, business problem that will be addressed, prioritizing based on impact on objectives, urgency, feasibility Define boundaries of scope, what will be included excluded setting realistic expectation around deliverables, timeline Deep dive to perform assessment of current state, analytical capabilities infra to identify gaps, define clear measurable success criteria performance indicator to evaluate impact Set up governance structure to make decision and resolve conflict

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Jeremy Merrell Williams

I help LUXURY Brands Launch 🚀 & Scale. Contact me if you are ambitious and run a Beauty, Fashion, Jewelry, or Tech startup. Serious enquiries only.
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It's also critical to have a clear picture of how we will measure the success of our data analytics project. Identifying key performance indicators (KPIs) beforehand ensures that we and our service provider have a shared understanding of what success looks like. This helps align expectations and facilitates better collaboration. Moreover, it's important to think about the potential impact of the project on our business. What outcomes are we expecting? How will they benefit our operations, strategy, or bottom line? By understanding the expected benefits, we can ensure that our data analytics project will deliver tangible value.

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2 Assess your data readiness

Another important factor to consider is the quality, availability, and accessibility of your data. How much data do you have, where is it stored, and how is it structured? How often is it updated, cleaned, and verified? How easy is it to integrate, transform, and analyze? Do you have the necessary permissions, security, and compliance measures in place? These aspects will affect the feasibility, cost, and duration of your project, as well as the level of support and expertise you will need from your provider.

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3 Choose a suitable delivery model

Depending on your project scope and goals, you may opt for different delivery models for your managed analytics service. For example, you may choose a one-time project, where your provider delivers a specific analysis or report based on your requirements and data. Alternatively, you may choose an ongoing service, where your provider monitors, updates, and enhances your analysis or dashboard regularly. Or, you may choose a hybrid model, where your provider combines both approaches. The delivery model will influence the pricing, contract, and collaboration terms of your project.

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4 Align expectations and responsibilities

Once you have selected a provider and a delivery model, you need to ensure that both parties are on the same page regarding the expectations and responsibilities of the project. This includes defining the scope, goals, timeline, budget, deliverables, quality standards, feedback mechanisms, and escalation procedures of the project. You also need to establish how you will communicate, share data, and coordinate tasks with your provider. A clear and detailed project plan, contract, and service level agreement can help you avoid misunderstandings, delays, and disputes.

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William Klusovsky

Cybersecurity Sage | Speaker, Tech <-> Business Translator, Strategy, GTM, Product, Consulting & MSS
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Review everything with the client "in person." This means laying out what you have defined, what you are agreeing to deliver and not. This gives the client the chance to say "I thought you'd do ABC..." then you can discuss if that should be in scope or how to proceed. With most MSP/MSSP contracts there are always people who "assume" the provider is going to do something and later find out that's not the case. By reviewing the contract and those expectations with them you reduce that risk. The risk exists if you assume the client has read everything on their own and understands it the same way as you do.

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5 Evaluate and improve the results

Finally, you need to monitor and evaluate the results of your managed analytics project and compare them with your initial goals and success criteria. You should also solicit feedback from your stakeholders, users, and customers on the value and usability of the analysis or report. Based on the evaluation and feedback, you can identify areas for improvement, optimization, or expansion of your project. You can also discuss with your provider how to implement the changes and measure their impact.

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