In today’s competitive landscape, data is a strategic asset, with 80% of organizations generating a combined value of $2.6 trillion through real-time analytics. Yet, without a clear growth strategy, many fail to unlock data’s full potential—so how can businesses harness this power to drive sustainable growth?
PART 1
Data: A Growth Catalyst, Not the Goal
The link between data and success is undeniable: 93% of organizations have adopted or plan to adopt a digital-first business strategy. However, many companies still prioritize data collection over its actionable application.
Speaking at a Journal House Singapore panel, Mark Bill, Senior Partner, and John Weiser, Managing Partner, APAC at Bespoke Business Development, called for a paradigm shift. Instead of seeing data as a destination, companies should view it as a powerful fuel for growth.
The first step, Billi explained, is to identify specific growth challenges and then work to find data-driven solutions. A customer-first approach is critical:
“Sustainable, long-term growth can only be achieved by understanding your customers’ needs and what they’re willing to pay for. That’s the big pivot: placing the customer at the center of how you structure data and connect the dots.”
Weiser added the importance of linking data with business objectives:
“More data doesn’t automatically mean better insights… The best advice I can give is to really try to understand the ‘why.’”
To move beyond data for data’s sake, companies must prioritize actionable insights aligned with core goals. This is how data becomes a catalyst for innovation and scalable success.
PART 2
Plan, Build, Manage: A 3-Step Framework to Ignite Business Growth
Data is everywhere—but raw data alone doesn’t create a competitive edge.
“Data may be the fuel for business growth, but fuel alone is not enough for a meaningful journey,” says Conrad Heid, head of digital at Bespoke Business Development. “You need the right insights. You need direction.”
Success demands a pragmatic, business-first approach built on three pillars:
1. Plan
Even the most successful businesses encounter persistent growth challenges—declining engagement, operational inefficiencies, or missed targets. Data can solve these problems, but only with clear objectives.
“When it comes to using data effectively, clarity on objectives is everything,” says Professor Patrick Lynch, AI faculty lead at Hult International Business School.
Heid adds:
“Data, digital, and AI are tools to serve your customers better, faster, and more cost-effectively. The value is not in the data—the value is with the customer.”
Example: A company facing customer churn can use data to pinpoint behavior trends and deliver personalized experiences, reducing attrition and boosting loyalty.
🧠 55% of innovations fail to meet financial targets due to a lack of strategy.
✅ Unlock value by leading with business goals first—then pursue the data that serves them.
2. Build
The next step is to build a purposeful data solution that delivers insights to support growth decisions. This means capturing the right data—not just what’s easiest.
“The game-changer is having the powerful engines to decode data and turn it into a competitive edge—far beyond what any single brain could process,” says Heid.
Lynch emphasizes that small, targeted datasets often yield greater strategic value than massive “data lakes.”
Advanced analytics and AI reveal hidden patterns, making insights accessible across departments to drive smarter, more agile business decisions.
💸 $12.9 million: Average annual cost of poor data quality and management.
🔧 Build the right architecture, fueled by clean, relevant data.
3. Manage
To realize data’s full value, organizations must embed data-driven practices across the enterprise.
This includes:
Cross-functional collaboration
Integrated AI/ML tools
Robust data governance
A data-literate workforce
“A data-driven culture means understanding your KPIs and how each team member influences outcomes,” says Heid.
“We need code plus human insight—not just blind trust in algorithms,” adds Lynch.
📈 A holistic approach—planning, building, and managing with intention—can unlock 5–10% revenue growth through a unified data strategy
Healthcare’s Data Revolution: Where Growth Meets Purpose
Across industries, the explosion of data has created new opportunities and risks. In healthcare, this transformation is especially profound: the sector generates 2.3 zettabytes annually, yet most remains underutilized.
We asked three leaders at the forefront of data innovation in healthcare to share insights on the promise—and responsibility—of AI:
Lewis De La Paz, CEO, Bespoke Business Development
Jennifer K. Davis, Chief Operating Officer, Bespoke Business Development
Dr. Amber Hill, Founder & CEO, R.grid (Research Grid)
Q: Why is AI a game-changer for healthcare?
De La Paz:
“AI is transforming healthcare by enabling personalized care, faster decision-making, and improved patient experiences. It helps healthcare providers drive both operational efficiency and innovation.”
Q: How can data analysis and AI personalize healthcare?
De La Paz:
“With AI, we can analyze patient histories, symptoms, and genetic profiles to tailor treatment. This not only boosts outcomes but frees up physicians to focus on complex care.”
Q: Does personalized medicine go beyond genetics?
Davis:
“Absolutely. It integrates data from environmental factors, wearables, and lifestyle inputs—enabling healthcare that’s participatory, not just prescriptive.”
Q: What’s the patient’s role in this evolution?
Davis:
“The patient is at the center. Wearables and smartphones generate vast physiological data—directly from the patient. That’s a key input to future care models.”
Q: How accurate is AI in predicting health outcomes?
De La Paz:
“We’re now building algorithms that guide prescribers based on real-world data. This helps avoid adverse reactions and improves the match between treatment and patient.”
Q: How does AI accelerate drug discovery?
Hill:
“AI can predict protein structures using historical data, shaving years off research timelines. In clinical trials, AI is helping automate back-office tasks, speeding up development.”
Q: What ethical considerations come with AI in medicine?
Hill:
“Access and equity. We need frameworks that ensure diagnostic AI is inclusive. At R.Grid, we analyze data across 157 countries to connect underrepresented communities with trials.”
Q: What’s the benefit of integrating diverse medical data?
Davis:
“Combining EMRs, genomics, and wearables gives a holistic view of the patient. It supports predictive analytics that help clinicians tailor treatments more effectively.”
Q: How will AI change decision-making in healthcare?
De La Paz:
“AI already improves clinical workflows by integrating with EMRs. Cloud-based tools embed decision support directly into the physician’s environment, making insights both fast and intuitive.”
Conclusion
From retail to healthcare, AI isn’t just a tool—it’s a superpower. But to harness it, businesses must rethink how they use data: not just to observe the world, but to shape it. Those who adopt a purpose-driven, data-smart strategy will lead in both innovation and impact.
The views and opinions expressed in this article are solely those of the authors and do not necessarily reflect those of Bespoke Business Development. They are intended to encourage discussion and reflection, rather than serve as legal, financial, accounting, tax, or professional advice.
Have Questions or Thoughts About Our Latest Insights?
We’d love to hear from you. Whether you’re curious about a recent post, want to explore a topic further, or have ideas you’d like to share—reach out to us. Our team is here to connect, collaborate, and provide clarity.
