Author: Pawel Dadura, Chief Technology Officer, Revenue.AI
As organizations increasingly recognize data as a strategic asset, the conversation has shifted from ‘we need data-driven operations’ to ‘how to scale them sustainably’. Yet, despite advances in data management and AI (Artificial Intelligence) tools, many businesses struggle to realize the full potential of their data to implement more effective Pricing and Revenue Management strategies.
The Challenge: Bridging the Gap Between Data and Decision-Making
Based on our experience working with multiple companies in Consumer-Packaged Goods (CPG), Retail, and Commodity Trading (CT), data silos are a common blocker for decision-making. The traditional workflow, where data is only understood, or worse – only accessible for a given department and isolated for the rest of the organization, creates misalignment within the company.
Artificial Intelligence (AI) is advancing at an incredible pace. According to Revenue.AI’s whitepaper,[MD1] the rising trend of AI continuing into 2024 highlights a shift towards the democratization of AI across multiple industries.
AI has been applied to resolve challenges across multiple business processes. As powerful as AI might be, however, without a shift towards data literacy democratization and interdisciplinary collaboration, AI can easily fail to deliver sustained value.
Apart from the typical organizational challenges, companies can face another barrier when trying to apply such technology as a solution – the mismatch between a company’s data literacy and sophistication of the tools that are being deployed. On the other hand, companies with good scaling practices spend half of their analytics budgets on adoption and yet, most organizations fail to increase or sustain adoption levels and realize value from their data.
Organizations need more than AI tools - they need the tool which brings to life a strategy that empowers their people, aligns processes, and fosters a culture of data literacy growth at every level.
The Right Approach: From Silos to Data-Driven Agility
Companies must transform their approach to both data and organizational structures. Here, it is critical that businesses choose and apply the right AI solution that can transform their data and help them scale efficiently. The proper AI solution will allow businesses to experience:
· Data transparency: Front-line workers need access to real-time, digestible data that support their daily tasks and decisions.
· Interdisciplinary collaboration: Breaking down silos to enable data exchange seamlessly between departments. Cross-functional teams must work together to solve complex problems using shared insights and common data.
· Agile decision-making: Gut-based decisions must give a way to the culture of experimentation and data-driven decision-making. This agility encourages innovation, fosters adaptability, and empowers teams to respond to changes swiftly and accurately.
In the realm of Pricing and Revenue Management, the right AI solution can help businesses achieve these goals. Right-framed AI solutions provide real-time visibility into market conditions, customer behavior, and competitive pricing, allowing companies to make more informed pricing decisions. By breaking down data silos, AI enables seamless collaboration between departments, ensuring that pricing strategies are aligned across the organization. Moreover, AI fosters agile decision-making by enabling continuous experimentation with pricing models, adjusting them dynamically based on demand, seasonality, and other key factors. This approach not only maximizes revenue potential but also allows businesses to stay competitive in rapidly changing markets.
What can businesses look for in AI solution?
Data literacy enablement
Scaling AI in an organization is not solely a technological challenge - it’s an educational one. The right AI solution would enable companies to increase data literacy across the workforce, providing products that are business value focused, and reducing barriers to the use of analytics for faster decision making.
People enablement necessity
AI transformation requires a workforce that is continuously learning and adapting. Yet, a significant portion of employees are either resistant to training or lack opportunities to build the skills needed to work alongside AI. According to OECD data, nearly 50% of adults neither train nor want to train, and around 60% do not participate in training in a given year.
The best AI solutions should provide training tailored specifically for the company workforce itself. People learn best through experiences. The AI solution should offer assistance through Intelligent Center of Excellence (ICE) to help users maximize the value of those experiences and accompany users at every stage of growth.
An example of Kolb’s learning process application with AI-enabled Intelligent Automation (Source: Revenue.AI)
The Future: Sustainable Growth via AI-Supported Culture
AI is no longer a futuristic concept - it's transforming industries and processes. But for organizations to truly benefit from it, they need to find the suitable AI tool that fosters a data-driven culture and follows business-proven roadmap. This should begin with AI education, targeting quick wins, and gradually evolve to building specialized teams and developing a comprehensive AI and data strategy.
The question is no longer "Should we embrace AI?" – it’s "How fast can we transform?"
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