What is a MIP and Do You Need One?

An executive's guide to Managed Intelligence Provider (MIP) Solutions

What is a MIP?

As your organization moves from digital transformation to AI transformation, building and maintaining a complete internal data science and ML team has become increasingly risky. With AI capabilities doubling every 6-12 months, technical skills are depreciating faster than ever. Even if budget isn't a constraint, attracting and retaining top data talent at the pace your business demands is often impossible in today's competitive market.

A Managed Intelligence Provider (MIP) is to data and AI/ML what a Managed Service Provider (MSP) is to IT - a flexible, subscription-based service that gives you an expert team on demand to augment your existing data capabilities.?

A MIP follows the same proven engagement model as traditional managed services, offering immediate access to high-performance data teams that work alongside your current team. Just as MSPs have simplified IT operations, MIPs streamline your journey to becoming an AI-driven organization while maximizing your existing team's effectiveness through complementary skills and scalable resources - all while reducing costs by 40-60% compared to building internally.

What Services does a MIP Provide?

A Managed Intelligence Provider (MIP) offers a comprehensive solution for organizations navigating their journey from digital transformation to AI transformation. Think of it as having an entire data science department at your fingertips, but without the overhead and complexity of building one from scratch. A MIP provides:

• Complete data lifecycle management - from warehousing to advanced analytics
• High-performance team on demand - no recruitment or training needed
• Seamless integration with your existing staff and systems
• Faster path to AI transformation without the traditional risks

What sets a MIP apart is its breadth of capabilities and expertise. An on-demand MIP team includes:

• Strategic leadership - Chief Data Officers to guide your data initiatives
• Technical expertise - ML scientists, data engineers, and BI specialists
• Operational excellence - DataOps and CloudOps experts
• Infrastructure management - Database administrators and DevOps specialists

This integrated team handles everything from foundational data work to advanced AI solutions:

• Data clean-up and governance
• Pipeline development and workflow automation
• Advanced analytics and dashboarding
• Machine learning model development
• AI decision intelligence and data products

By combining strategic oversight with hands-on technical expertise, a MIP enables you to accelerate your data initiatives while maintaining focus on your core business growth.

Comparing MSP to MIP

The Managed Services Provider (MSP) and Managed Intelligence Provider (MIP) models are fairly similar in form but differ in terms of skill gaps and focus, as the table below outlines.

?Why Consider a MIP Now?

?Economic Uncertainty Demands Flexibility

• Building internal teams requires 6-12 month recruitment cycles
• Top AI talent commands premium compensation packages
• Training and productivity lag time affects ROI

Long-term staffing commitments pose significant risks

• ?Global / complex BI Challenges Need Immediate Solutions
• Multiple failed attempts to standardize BI tools across regions
• Low organizational adoption of existing data platforms
• Inconsistent reporting across business units
• High costs of managing multiple BI systems

?Accelerating AI Changes Everything

• Traditional BI skills are becoming automated
• Internal teams struggle to keep pace with AI advancements
• Training costs are escalating as technology cycles shrink
• Universities can't update curricula fast enough to match market needs

?Signs You Need a MIP

Operational Red Flags

1. High costs in data operations maintenance
2. Manual data processing consuming valuable staff time
3. Delayed / missing BI analysis cycles affecting decisions
4. Inability to scale data operations with growth

Strategic Challenges

• Departments creating unofficial data analysis systems
• Critical decisions made on gut feel despite available data
• Multiple versions of "truth" across teams

Excel-based analysis dominating decision-making

Resource Constraints

• Significant investment in underutilized data tools
• Multiple redundant systems & data debt
• High fixed costs in data analysis BI/AI/ML infrastructure
• Rising training and retraining costs

?Executive Decision Framework for CEOs, CFOs, CIOs & COOs

Deciding on whether a MIP is a good solution for your company depends on your leadership role and current challenges. The table below helps leaders think through these aspects.

MIP Versus Building Out Internal Data Team

Engaging a MIP offers several cost advantages over hiring employees to augment your data team, per the table below.?

MIP versus MSPs versus Consulting Firms

OK so you're pretty sure you don't want to or have the time / bandwidth or expertise to hire build out an internal data platform team. What are our other options? Here's how engaging a skilled MIP compares to fulfilling your data platform needs via an MSP or hiring an IT consulting firm / SI that is not an experienced MIP.

Implementation Strategy & Planning

Here’s your 90-Day Quick Start guide to assessing, integrating and optimizing a MIP engagement in your organization.?

?Learn More About MIP Solutions

Accelerate your AI transformation with Paragon's comprehensive MIP solution. Visit paragoncto.com/mip or email [email protected] to schedule a complimentary initial workshop.

Ariel Jalali is CEO of Paragon Tech , an CIO-led advisory firm helping mid to upper mid-market companies through their journey from digital transformation to AI transformation. He is a world expert in applied AI/ML, lecturer and author.