Transform Your SME with AI: A Comprehensive Profit and Growth Framework

Introduction

The rapid growth of artificial intelligence (AI) is transforming business landscapes, with large enterprises often leading the way. However, small and medium-sized enterprises (SMEs) can also leverage AI to drive profitability and growth.

This article provides a practical framework for SMEs to leverage AI capabilities. While it focuses on profitability and growth , the framework is adaptable to any other strategic objective a company may pursue.

I.?Develop Vision to Harness AI to Achieve Company’s Strategic Objectives

This step involves a deep assessment of the company’s current market position, operational challenges, and long-term strategic objectives to pinpoint where AI can deliver the most value.

If the priority is profitability improvement, the company may focus on using AI to automate repetitive tasks, streamline supply chains, optimize inventory levels, and improve cost efficiency in operations.

Alternatively, if the strategic focus is on growth , the company might leverage AI to enhance customer acquisition strategies, drive product innovation, implement dynamic pricing models, and personalize marketing efforts. AI’s predictive analytics can uncover new market opportunities, optimize cross-selling, and improve customer retention.

Sample Vision: “To lead our SaaS target segment by harnessing AI to deliver unmatched value for our customers. Through deeper insights into customer needs, we will continuously innovate our offerings to stay ahead of industry demands and deliver the best value in the fastest way possible. We will also leverage AI to become price leaders by using advanced AI and no-code solutions to accelerate our time to market and cut IT development costs”.

II. Understand the Business Case for AI

After developing a Vision aligned to the company’s strategic imperatives, the company needs to identify specific areas where AI capabilities will need to be introduced. Some key areas where AI can immediately have an impact include:

Profitability Improvement

AI can drive down costs across various business functions, enhancing efficiency and reducing operational expenses:

Process Automation

AI and machine learning can automate repetitive, time-consuming tasks, such as data entry, invoicing, and customer inquiries, freeing employees to focus on higher-value activities. For example, AI-powered chatbots can handle customer support, significantly reducing labor costs while maintaining high service quality.

Potential Solutions:

• UiPath: An RPA (Robotic Process Automation) platform that enables businesses to automate various back-office tasks, such as data processing, invoicing, and email responses.
• Zoho Desk: An AI-powered customer support platform with an integrated chatbot, Zia, which automates customer interactions and provides instant support, reducing the need for a large customer service team.

Process Redesign & Optimization:

AI can optimize supply chain management by predicting demand, monitoring inventory levels, and automating order processing. Machine learning algorithms can forecast sales trends, helping to minimize overstocking or stockouts and reducing inventory holding costs. Additionally, AI-driven analytics can streamline logistics by identifying the most efficient shipping routes, reducing transportation costs, and improving delivery times.

Potential Solutions:

• Llamasoft: A supply chain optimization platform that uses AI and machine learning to model, analyze, and predict demand, optimizing inventory levels and reducing holding costs.
• Shipwell: An AI-driven logistics platform that automates shipping processes, selects optimal carriers, and identifies efficient routes to lower transportation costs and improve delivery times.

IT Development Acceleration and Cost Reduction

AI-based tools can provide affordable, scalable alternatives to traditional IT development and support. For example, automated coding assistants can speed up software development, reducing the need for a large, expensive in-house IT team. Similarly, AI-driven cybersecurity solutions offer real-time threat detection and mitigation at a fraction of the cost of conventional methods, protecting critical business data while lowering IT security expenditures.

Potential Solutions:

• GitHub Copilot: An AI-powered code-completion tool that assists developers in writing code faster and with fewer errors, reducing the time and cost of software development.
• Darktrace: An AI-driven cybersecurity solution that provides real-time threat detection and response at a lower cost than traditional cybersecurity methods, helping SMEs safeguard their data effectively.

Energy and Resource Efficiency

AI-powered systems can monitor and manage energy usage in facilities, adjusting lighting, HVAC, and equipment operations to optimize energy consumption and reduce utility costs. This capability helps SMEs implement cost-saving measures while promoting sustainability.

Potential Solutions:

• BrainBox AI: An AI-powered HVAC optimization solution that adjusts heating, ventilation, and air conditioning systems in real-time, significantly reducing energy consumption and costs.
• GridPoint: A platform that uses AI and IoT sensors to monitor energy usage across facilities, providing actionable insights to minimize utility costs and improve sustainability.

?Revenue Growth:

AI has the potential to drive substantial revenue growth by enabling several key activities:

Product Innovation

AI can help identify market gaps by analyzing customer feedback, market trends, and competitive products, providing insights that can guide the development of innovative products tailored to meet unmet customer needs. This capability allows SMEs to innovate and diversify their product lines, driving additional revenue streams.

Potential Solutions:

• IBM Watson Analytics: A comprehensive AI platform that allows businesses to analyze market data, customer feedback, and trends, helping identify opportunities for new product development.
• Crimson Hexagon (Brandwatch): An AI-powered consumer insights platform that analyzes social media, reviews, and other customer data to uncover market needs and inform product innovation strategies.

Advanced Pricing Strategies

Dynamic pricing algorithms powered by AI can optimize pricing in real-time based on factors like demand, competitor pricing, seasonality, and customer segments. This helps SMEs maximize revenue by adjusting prices to market conditions, ensuring they remain competitive while enhancing profitability.

Potential Solutions:

• Pricemoov: An AI-driven pricing platform that enables SMEs to implement dynamic pricing strategies, taking into account market conditions, competition, and customer behavior to maximize revenue.
• BlackCurve: An AI-based pricing optimization tool that allows businesses to set data-driven prices, continuously monitoring market dynamics to ensure pricing remains competitive while maximizing profitability.

Enhanced Cross-Selling

Machine learning algorithms can identify patterns in customer behavior, enabling businesses to recommend products that align closely with individual customer preferences, thereby boosting sales.

Potential Solutions:

• Shopify's Product Recommendations: An AI-driven feature that analyzes customer interactions on the website to suggest relevant products, enhancing the shopping experience and increasing sales.
• Dynamic Yield: An AI-powered personalization platform that offers personalized product recommendations, dynamic content, and tailored experiences based on individual customer behavior.

Improved Customer Acquisition

AI can analyze customer data to create more personalized and effective marketing campaigns, increasing customer engagement and conversion rates.

Potential Solutions:

• HubSpot: An AI-powered marketing automation platform that enables SMEs to segment their customer base and create personalized marketing campaigns based on customer behavior and preferences.
• Salesforce Einstein: An AI layer within Salesforce's CRM that provides predictive insights to personalize marketing efforts, optimize customer interactions, and drive sales growth.

Improved Customer Support and Retention

AI-powered chatbots and virtual assistants can provide 24/7 customer support and streamline the buying process, opening up new digital sales opportunities.

Potentials Solutions:

• Drift: An AI-driven conversational marketing platform that uses chatbots to engage website visitors, answer queries, and guide potential customers through the sales funnel.
• Intercom: An AI-powered customer communication platform that includes chatbots to provide instant responses to customer inquiries, enhancing support and facilitating sales 24/7.

Enhanced Decision-Making

Data-driven insights enable better strategic planning and operational adjustments, reducing guesswork. AI provides predictive analytics that helps forecast market demand, optimize inventory levels, and make informed financial and operational decisions.

Potential Solutions:

• Tableau with Einstein Analytics: Tableau, integrated with Salesforce's Einstein Analytics, provides AI-powered data visualization and predictive insights. SMEs can use it to analyze large datasets, forecast market demand, and optimize inventory management. It enables businesses to identify trends, track key performance indicators, and make data-driven decisions that enhance operational efficiency and profitability.
• Microsoft Power BI with AI Builder: Power BI, combined with AI Builder, allows SMEs to create data models and use machine learning algorithms to forecast market trends, predict customer behavior, and identify areas for process optimization. It provides advanced analytics and easy-to-understand visualizations, empowering businesses to make more informed strategic decisions and improve operational performance.

III. Lay the Foundation for AI Adoption

To successfully implement AI, SMEs must first build a solid foundation. This involves careful planning, preparation, and alignment across various aspects of the business. The initiatives presented below are not exhaustive.

Step 1: Data Readiness

Objective: Ensure the business has high-quality data to fuel AI systems.

Conduct a Data Audit

Review current data sources, storage systems, and data quality.

• Action: Inventory all available data sources (e.g., customer databases, sales records, website analytics). Identify gaps in data collection, inconsistencies, and areas requiring improvement.
• Example: A retail SME analyzes its sales data and finds that it is scattered across various systems (e.g., POS, e-commerce, CRM). The company consolidates this data into a single database, cleans up duplicate entries, and standardizes data formats.

Clean and Organize Data

Address data quality issues by removing duplicates, correcting errors, and filling in missing information.

• Action: Use data cleaning tools like OpenRefine or Trifacta to process large datasets and ensure they are accurate, complete, and formatted consistently.
• Example: A healthcare SME uses Trifacta to standardize patient records, making them ready for AI-powered analytics to predict patient visit patterns and optimize staffing.

Establish Data Collection Processes

Implement processes to continuously capture relevant data.

• Action: Set up data collection methods using tools like Google Analytics for website data or HubSpot CRM for customer interactions, ensuring a steady flow of structured data.
• Example: An e-commerce company installs Google Analytics on its website to track customer behavior, feeding real-time data into an AI-driven recommendation engine to improve customer targeting.

Step 2: Cultural Shift

Objective: Create an AI-friendly mindset throughout the organization.

Educate Leadership and Staff

Begin with educating leadership on AI’s potential impact, followed by company-wide training sessions.

• Action: Organize workshops or seminars with AI experts to demonstrate AI's benefits and applications.
• Example: A logistics SME invites a consultant from a top-tier consulting firm to conduct a workshop on how AI can optimize route planning, showcasing real-world success stories.

Communicate the Vision

Clearly articulate how AI will benefit both the company and employees, reducing resistance to change.

• Action: Share the AI strategy during internal meetings, emphasizing how it will automate mundane tasks, allowing employees to focus on more valuable activities.
• Example: A marketing SME explains that implementing HubSpot’s AI-powered marketing tools will reduce manual data analysis, enabling the team to focus on creative strategies.

Foster a Data-Driven Culture

Encourage data-driven decision-making at all levels by incorporating data insights into daily operations.

• Action: Introduce dashboards and reports generated by tools like Tableau or Power BI, helping employees make informed decisions based on real-time data.
• Example: A restaurant chain regularly reviews Power BI dashboards to analyze customer preferences and adjust menu offerings accordingly.

Step 3: Technology Stack Assessment

Objective: Identify and integrate the right technology stack compatible with AI tools.

Evaluate Existing Infrastructure

Assess current IT systems (e.g., data storage, analytics platforms) to identify what needs upgrading or replacing.

• Action: Review current software for compatibility with AI platforms. Determine if a cloud-based solution, such as Microsoft Azure or AWS, is necessary to support AI capabilities.
• Example: A small manufacturing SME assesses its on-premises data storage and migrates to AWS, facilitating integration with AI-powered supply chain optimization tools.

Select Appropriate AI Tools

Choose AI tools and platforms that suit the business’s size, needs, and budget.

• Action: Explore solutions like Google Cloud AutoML for easy model training, UiPath for process automation, or Zoho Analytics for AI-driven data analysis.
• Example: A retail SME selects Zoho Analytics for its AI capabilities, allowing it to visualize customer purchasing patterns and predict future trends.

Implement a Scalable Infrastructure

Adopt flexible, cloud-based solutions that allow for easy scaling as AI needs evolve.

• Action: Use cloud services like Azure Machine Learning or Google Cloud AI Platform, which provide scalability and integrated AI tools.
• Example: A real estate SME implements Google Cloud AI Platform to analyze market trends and property values, ensuring the infrastructure can scale as its data processing needs grow.

Step 4: Skill Development

Objective: Build internal AI expertise through hiring, partnerships, or upskilling.

Assess Current Skills

Evaluate the existing workforce's capabilities and identify skill gaps in data science, AI, and machine learning.

• Action: Conduct a skills assessment survey to determine employees' proficiency levels in data analytics, coding, or AI-related tasks.
• Example: An SME in the financial sector identifies a lack of data analytics expertise and decides to upskill its team in tools like Python and Tableau.

Upskill Existing Employees

Provide training in data analysis, AI tools, and basic programming.

• Action: Enroll employees in online courses through platforms like Coursera or Udacity to learn AI basics, data analytics, and machine learning.
• Example: A retail SME's marketing team takes an online Coursera course on AI-driven marketing to leverage insights from customer data effectively.

Hire or Partner for AI Expertise

If internal upskilling is insufficient, consider hiring AI specialists or partnering with external vendors.

• Action: Recruit data scientists, AI engineers, or collaborate with AI consulting firms to bridge the expertise gap.
• Example: A logistics SME hires a data scientist to build and implement machine learning models for optimizing delivery routes, reducing fuel costs.

Establish an AI Champion or Team

Designate an internal AI lead or create a cross-functional AI team responsible for driving AI initiatives.

• Action: Assign a project manager or form a small team that collaborates with various departments to identify AI opportunities and oversee implementation.
• Example: A mid-sized healthcare SME creates an AI task force to explore using predictive analytics for patient care and optimize appointment scheduling.

By following these structured steps, SMEs can lay a strong foundation for AI adoption, setting the stage for successful implementation and long-term growth.

IV. Implement AI Solutions

Step 1: Define Clear Objectives for AI Capabilities Introduction

Start Small: Identify high-impact, low-complexity use cases that align with business goals, such as customer segmentation, predictive maintenance, or inventory management. By focusing on immediate wins, SMEs can build momentum and demonstrate the tangible benefits of AI.

Set Measurable KPIs: Establish specific targets for each AI initiative, focusing on measurable outcomes like cost savings, revenue growth, or customer satisfaction. KPIs should be used to track progress and guide further investment in AI capabilities.

Step 2: Build or Buy AI Solutions

Buy: Many AI tools are designed for SMEs, offering features like automated customer support, personalized marketing, and supply chain optimization. Off-the-shelf solutions can provide quick wins and are cost-effective.

Build: For more complex or unique needs, SMEs can use low-code AI development tools or collaborate with AI-focused service providers to create custom solutions.

Hybrid Approach: A mix of in-house development and third-party solutions often provides the flexibility needed to tailor AI implementations to specific business requirements.

Step 3: Implement Pilot Projects

Start with Pilots: SMEs should begin by implementing small-scale pilots to test AI applications in real-world scenarios. This approach allows businesses to gather insights, refine processes, and measure the benefits without significant investment.

Iterative Feedback Loop: During the pilot phase, feedback is crucial. Use data and user experiences to continuously optimize AI models, improve data quality, and address unforeseen challenges. This iterative process ensures the AI solution is fit for larger-scale implementation.

Step 4: Scale Up

Post-Pilot Expansion: After successfully completing pilot projects, SMEs can gradually scale AI adoption across other business units or processes. By expanding based on pilot results, businesses can systematically realize AI's full potential.

Change Management: Scaling AI requires careful change management. Employees buy-in, training, and aligning existing processes with new AI capabilities are essential for smooth scaling. Clearly communicate the benefits of AI to the workforce to minimize resistance.

Step 5: Continuous Improvement, Monitoring, and Adaptability

Ongoing Analysis: Regularly monitor AI performance against the KPIs established in Step 1. Use analytics to refine AI strategies, improve models, and identify new opportunities for enhancement. Analyzing the outcomes helps in making data-driven adjustments to the AI deployment.

Stay Current: SMEs must be prepared to incorporate ongoing advancements in AI technology to remain competitive. Establish a process to stay updated on AI innovations, including:

Scalability Planning: Design AI implementations with modularity in mind, allowing for the integration of new capabilities quickly and without disrupting current systems.

Agile Mindset: Cultivate an agile organizational mindset that embraces experimentation, rapid iteration, and flexibility to pivot strategies as new AI technologies emerge. This adaptability will enable SMEs to continue leveraging AI for profitability and growth in the long term.

V. AI Use Case for a SaaS company - Illustrative

Background

A SaaS company specializing in project management tools for small to medium-sized businesses seeks to enhance profitability and growth.

Vision

Enhance Customer Value: Use AI to analyze customer usage patterns, identify pain points, and deliver personalized product recommendations to improve user experience and retention.

Accelerate Product Innovation: Employ AI to rapidly identify market trends and customer preferences, enabling the company to develop new features faster and more efficiently.

Reduce Costs: Implement AI-driven no-code tools to automate routine IT tasks, accelerate product development cycles, and reduce support costs.

Key Initiatives to Leverage AI for Enhanced Profitability & Growth

Customer Behavior Analysis - Increases Value to Customer, Helps Identify New Improved Features and Upselling

• Implementation: The company leverages Salesforce Einstein to analyze customer interactions within the SaaS platform. This AI tool provides actionable insights into how customers use the product, identifying features that are underused or problematic.
• Outcome: By gaining a detailed understanding of customer behavior, the company can personalize user experiences. For instance, if a user isn't utilizing a key feature, the AI can automatically recommend tutorials or offer in-app guidance to increase adoption.
• Example: If data shows that customers are not using the advanced analytics feature of the platform, Salesforce Einstein can trigger an automated campaign suggesting relevant guides, reducing customer churn by improving product adoption.

AI-Driven Customer Support - Improves Customer Satisfaction and Retention, Reduces Cost to Serve

• Implementation: The company integrates Intercom's AI-powered chatbots to provide 24/7 customer support. These chatbots can handle common queries, troubleshoot issues, and provide personalized solutions based on user behavior data.
• Outcome: By automating responses to routine inquiries, the company can significantly reduce support costs and free up customer success teams to focus on complex, high-value interactions. The chatbot's continuous learning capability ensures that it evolves based on new customer queries and patterns.
• Example: When users encounter an issue, the chatbot automatically suggests a solution based on past interactions or opens a ticket with detailed context if human intervention is required, reducing resolution time.

Market Trend Analysis - Accelerates Product Innovation aligned to Customer Needs

• Implementation: Using IBM Watson Analytics, the company analyzes market trends, customer feedback, and competitor product releases. The AI can scan social media, forums, and industry news to identify emerging customer needs and market gaps.
• Outcome: These insights help prioritize new feature developments that align with customer demand. The company can innovate faster by introducing features that not only enhance user value but also keep them ahead of industry trends.
• Example: AI identifies a growing demand for integration with remote work tools. The company then uses this insight to launch a new integration feature, marketed directly to existing customers who are already using remote work solutions.

AI-Powered Product Development - Accelerates Time to Market, Product Reliability, Reduces IT Development Costs

• Implementation: To accelerate product development, the company uses GitHub Copilot, an AI-powered code-completion tool, alongside Bubble, a no-code platform, to develop new product features and streamline updates.
• Outcome: GitHub Copilot assists developers in writing code faster and with fewer errors, speeding up the development cycle. Simultaneously, Bubble allows non-technical teams to create and test new app functionalities, reducing reliance on the development team and lowering IT costs.
• Example: When building a new feature for real-time collaboration within the SaaS platform, developers use GitHub Copilot to generate code, reducing the time-to-market by 30%. Additionally, the marketing team uses Bubble to quickly build and test new UI elements, ensuring rapid deployment of updates.

Dynamic Pricing - Optimizes Profitability, Aligns Pricing to Customer Behavior and Competitive Dynamics

• Implementation: The company implements Pricemoov, an AI-driven pricing platform, to dynamically adjust subscription prices based on market conditions, customer segments, and competitor pricing.
• Outcome: AI analyzes customer data to identify willingness to pay, demand elasticity, and the competitive landscape. This allows the company to implement a tiered pricing model, offering discounts or promotions to specific customer segments to maximize revenue without sacrificing profitability.
• Example: If the AI identifies a drop in demand due to a competitor’s promotional offer, Pricemoov can automatically adjust the SaaS pricing for specific segments, maintaining competitiveness while protecting margins.

Expected Benefits and Outcomes

• Enhanced Profitability: By automating customer support, optimizing product development, and implementing dynamic pricing, the company reduces operational costs and maximizes revenue.
• Accelerated Growth: AI-driven insights into customer behavior and market trends enable faster innovation and improved customer satisfaction, leading to higher retention rates and customer acquisition.
• Reduced Time to Market: AI and no-code tools streamline the development process, allowing for rapid iteration and deployment of new features in response to market demands.
• Leadership in the Market: Leveraging AI capabilities enables the company to stay ahead of competitors in terms of product features, pricing strategies, and customer experience, aligning perfectly with the company’s vision.

VI. Overcome Common Barriers to AI Adoption

Cost Constraints

SMEs often operate on tight budgets. Opt for budget-friendly AI adoption strategies, such as cloud-based AI solutions and pay-as-you-go models, to avoid large upfront investments.

Data Privacy and Security

Address data privacy concerns by ensuring compliance with data protection regulations (e.g., GDPR) and implementing robust data security measures.

Lack of Expertise

If in-house expertise is limited, consider tapping into external AI expertise through consultants, partnerships, or AI-as-a-service providers to fill the gap.

VII. Measure Impact of AI vis-à-vis the Vision

Key Metrics

Assess the impact of AI initiatives using metrics such as ROI, operational cost reductions, sales growth, customer acquisition, and retention rates. Track these metrics to ensure the AI strategy aligns with overall business objectives.

Case Studies

Examine brief case examples of SMEs that successfully leveraged AI to transform operations, drive growth, or enter new markets, illustrating how strategic AI adoption can result in tangible benefits.

VIII. Adapt Company Vision to Evolving AI Developments

AI is constantly evolving, and to stay competitive, companies must refine their AI vision in line with the latest advancements. This isn’t a one-time setup—it’s an ongoing process that directly fuels growth and profitability.

1. Regularly Reassess the AI Vision

• Action: Conduct quarterly or semi-annual reviews of the AI vision. Ensure it aligns with the latest tech and market shifts. Involve cross-functional teams to bring fresh perspectives.
• Example: A SaaS company might review its AI-driven product strategy quarterly, quickly integrating new AI tools like generative models to enhance its product lineup.

2. Invest in Continuous Learning

• Action: Create a culture of learning. Invest in employee training to keep them up-to-date with cutting-edge AI technologies and trends.
• Example: Use platforms like Coursera to train data science teams in advanced AI techniques, ensuring they're equipped to leverage the latest advancements.

3. Monitor Industry Trends

• Action: Stay on top of industry reports, attend AI conferences, and join forums. Be proactive in identifying AI trends and best practices.
• Example: Follow Forrester or Gartner insights to see how top SaaS companies use AI for customer personalization and process automation.

4. Implement a Scalable AI Infrastructure

• Action: Use flexible, cloud-based AI platforms like Microsoft Azure or Google Cloud AI. This ensures you can integrate new AI capabilities as they emerge without disrupting operations.
• Example: Start with basic AI chatbots for support, then easily add advanced features like sentiment analysis or voice recognition as your needs grow.

5. Build Strategic Partnerships

• Action: Partner with AI vendors, research institutions, and industry consortia to get early access to emerging technologies.
• Example: Collaborate with companies like OpenAI or IBM Watson to test and integrate the latest AI tools, ensuring you stay ahead in your market segment.

6. Gather and Analyze Customer Feedback Continuously

• Action: Use AI tools to constantly monitor customer feedback and identify changing needs. Stay tuned to what your customers want.
• Example: Utilize Qualtrics XM for sentiment analysis on support tickets and social media. Use these insights to refine your product and AI strategies.

7. Incorporate AI into Strategic Planning

• Action: Use AI-driven insights for real-time strategic planning. Forecast market trends, adjust pricing, and spot new growth opportunities.
• Example: Leverage Tableau with Einstein Analytics to visualize market data and customer behavior, pivoting your AI vision to capitalize on new trends quickly.

Staying Competitive with a Dynamic AI Vision

Adaptability is key. By staying informed, continuously learning, and leveraging new AI capabilities, your AI vision remains sharp and relevant. It’s this proactive approach that will set you apart, delivering unmatched value to your customers and securing your place as an industry leader.

Conclusion

AI is redefining how SMEs operate, compete, and grow. This framework provides a clear roadmap for harnessing AI to reduce costs, drive revenue, and make data-driven decisions, offering a sustainable competitive edge.

The foundation is simple but crucial: ensure data readiness, embrace a data-driven culture, and build a robust tech stack. Upskill teams or partner with AI experts to implement this vision effectively.

Adopting AI means setting measurable objectives, piloting solutions, and scaling up based on real results. Continuous improvement and agility are key to staying ahead in the evolving AI landscape. From marketing to finance, AI isn’t just automation; it’s a strategic growth driver that personalizes customer experiences, optimizes pricing, and unlocks new market opportunities.

Barriers like cost, data privacy, and skill gaps are manageable with the right tools, security measures, and external expertise.

The future belongs to those who act now. SMEs must prioritize AI as a strategic asset for ongoing innovation, profitability, and growth. Start small, scale quickly, and keep evolving. This is your blueprint for transforming your business and thriving in an AI-powered world. Embrace AI today to secure your company’s success.

If you need to better understand the potential role of AI in Business Strategy, Operations or Finance or would like to discuss the benefits of a CFO on Fractional basis contact us

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