Why Businesses Struggle with AI and Data Transformation: Breaking Down Silos for Real Impact

3 MIN READ

JESSICA KENTCH, FOUNDING PARTNER, ABLAZE ANALYTICS & COLLECTIVE

Over the past decade, businesses across industries have invested millions into AI, digital transformation, and data initiatives. From cutting-edge machine learning algorithms to sophisticated data platforms, organizations have spared no expense in trying to harness the power of data to drive better decision-making, enhance customer experiences, and stay ahead of the competition.

But despite these investments, something is still not clicking.

Too often, data teams and operational teams are speaking different languages, working in silos, and struggling to turn insights into action. While the promise of AI and digital transformation is undeniable, the gap between insight and execution remains a persistent challenge for many businesses.

At Ablaze Collective, we’ve seen this disconnect firsthand—particularly in industries like cloud accounting and fintech where data is a critical asset. But we also understand that the real challenge lies not in the data itself, but in how businesses integrate, activate, and apply that data across the organization. Here’s why this happens and how businesses can break down these barriers to turn their data into real, actionable outcomes.

The Problem: Data Teams and Operational Teams Are Working in Silos

One of the key reasons businesses struggle with AI and data initiatives is the disconnect between data teams and operational teams.

• Data teams are typically focused on gathering, processing, and analyzing data. They may work with data scientists, engineers, and analysts to build sophisticated models, identify patterns, and generate insights. These teams are highly technical, often using specialized tools and platforms like AI models, data lakes, and machine learning algorithms.

• Operational teams, on the other hand, are focused on using that data to run day-to-day operations. They might be in charge of marketing, sales, customer service, or even accounting. These teams often work with tools like CRM systems, ERP software, or financial management platforms to make decisions that impact revenue, customer satisfaction, and overall business growth.

However, when these two groups aren’t aligned, a gap forms. Data insights may not translate into actionable steps, and operational teams may find it difficult to implement findings in a way that makes a real impact.

The Language Barrier: Data Isn’t Always Actionable

Another key issue that keeps businesses from realizing the full potential of their data is the lack of actionable insights. Data teams may generate complex reports, visualizations, and predictions, but if they don’t communicate in a way that’s easily understood by operational teams, those insights fall flat.

Take financial data as an example. A CFO might receive a complex model that predicts customer churn, but if that model isn’t linked to specific actions—like targeted marketing campaigns or personalized sales outreach—the insight becomes theoretical rather than practical.

Additionally, if the operational team lacks the tools to act on the data in real time, insights become outdated quickly. This is a huge pain point, especially for fintech companies or CPA firms that rely on up-to-date financial data to advise clients or make business decisions.

The Cost of This Disconnect

The costs of this gap between insight and action are clear:

• Missed opportunities: The inability to act on data quickly means businesses can miss opportunities for growth, optimization, and innovation.

• Wasted resources: Investing in advanced technologies, AI, and data analytics can feel like throwing money into a black hole if there’s no clear plan to apply those insights.

• Employee frustration: When data teams and operational teams are not on the same page, it leads to inefficiency, miscommunication, and frustration on both sides. Data professionals may feel their work is undervalued, while operational teams may feel they aren’t getting the information they need to make informed decisions.

The Solution: Breaking Down the Silos and Making Data Actionable

To overcome these barriers, businesses must break down the silos between data teams and operational teams. Here’s how:

1. Bridge the Communication Gap

It’s essential to create a common language between data teams and operational teams. Data teams need to present insights in a way that’s relevant and actionable to operational teams. This means avoiding jargon and translating complex models into simple, clear recommendations that drive action.

• Instead of simply reporting on a trend, data teams should highlight next steps and recommended actions.

• Tools like BI dashboards can help bring data to life, presenting actionable insights in real-time and making them accessible to non-technical team members.

2. Create a Unified Data Platform

Data should flow seamlessly across the organization. Rather than relying on isolated systems, businesses should create a centralized data platform that integrates data from all parts of the organization. This platform should be accessible to both data and operational teams, ensuring that everyone is working with the same data set and insights.

For example, businesses using platforms like QuickBooks, Xero, or Plaid can integrate financial data into a unified system, allowing both data scientists and operational teams to work from the same information. This eliminates the need for manual data transfers and ensures that everyone has access to real-time, accurate data.

3. Empower Operational Teams with Self-Service Analytics

Empowering operational teams to access and act on data without needing constant input from data teams is key. Self-service analytics tools—like Metabase, Tableau, or Power BI—enable operational teams to create their own reports and dashboards based on the data available to them.

These tools are intuitive and user-friendly, making it easier for non-technical staff to analyze data and make decisions without always relying on data experts. By democratizing access to data, operational teams can act more swiftly and with greater confidence.

4. Focus on Real-Time Data Activation

For data to have real-time impact, it must be activated within the workflows of operational teams. This means integrating insights directly into the tools that operational teams use every day, such as CRMs, ERP systems, or marketing platforms.

When data is activated in real-time, businesses can make immediate, informed decisions that drive action. Whether it’s adjusting marketing spend based on customer behavior or providing timely financial advice to clients, data that is actionable leads to results.

Conclusion: The Path to Data-Driven Success

At Ablaze Collective, we understand the frustration of businesses that invest heavily in AI, digital transformation, and data initiatives, only to see limited results. The root of the problem often lies in a disconnect between data and operations. When data insights aren’t actionable or easily integrated into everyday workflows, businesses miss out on the true power of their data.

To truly unlock the value of your data, you need to create a seamless connection between data teams and operational teams. By bridging the communication gap, centralizing data, empowering teams with self-service analytics, and activating insights in real time, you can transform your data from a buzzword into a business-driving force.

If you're ready to break down the barriers and take your data to the next level, Ablaze Collective is here to help. We specialize in turning financial data from platforms like QuickBooks, Xero, and Plaid into actionable insights that drive growth and efficiency for CPA firms, fintech founders, and other data-forward businesses.