In this article the common pitfalls in data and people management that hinder analytics success is highlighted. Aimed at C-suite leaders, it emphasizes the importance of valuing people alongside technology. It advocates for clear data value articulation, structured investment, leadership alignment, and talent-focused strategies to build resilient, high-performing data capabilities that drive business impact.
In the modern business landscape, data is both invaluable and inevitable. Organisations are investing heavily in analytics capabilities to remain competitive, enhance operational efficiency, and uncover new growth opportunities. Yet, despite this investment, more than 80% of data analytics initiatives fail to deliver sustained business value.
The root of this failure is rarely the data itself, or even the tools used to analyse it. Instead, it often lies in how organisations manage the human side of data – the people who collect, process, analyse, and interpret it. For C-suite leaders who are not yet confident in navigating the complexities of data, this becomes a blind spot that can have significant implications for business performance.
Recognising the Warning Signs
When leadership lacks data confidence, the following organisational symptoms are common:
- Unclear value and resource scrutiny: Investments in data are frequently questioned due to unclear return on investment.
- Frequent restructuring: Data teams are moved between departments, often annually, causing disruption and loss of strategic direction.
- High attrition: Talented data professionals leave due to misaligned expectations, lack of support, or inadequate remuneration.
- Underqualified staffing: Cost-saving measures lead to junior hires being placed in senior roles without sufficient guidance or mentorship.
- Overburdened teams: A handful of resources are expected to manage complex requests without the bandwidth to deliver long-term value.
- Commoditisation of skills: Data professionals are treated as generalists rather than as specialists with strategic potential, reducing morale and increasing turnover risk.
These challenges are often exacerbated when technology is prioritised without a corresponding investment in the people and structures needed to drive value from it. When value is not clearly articulated, cost-cutting becomes the default, and organisations try to “save their way” to success – a strategy that consistently fails. In some cases, this underinvestment is a deliberate cost-cutting strategy, one that inevitably undermines long-term outcomes.
Shifting the Focus: People as Strategic Enablers
The good news is that these issues are solvable, provided data is treated as a strategic business enabler and not just a technical function. The starting point is a clear articulation of the value data is expected to deliver. If this is vague or undefined, any investment, especially in people, will be scrutinised or deprioritised.
Once the value case is clear, leaders must adopt a formalised approach to building data capability, with people seen as both a critical input and a measurable output. Below are the strategic components of this approach.
-
Structure for Value Delivery
Organisational structure directly impacts the effectiveness of your data teams. While distributed teams can work well in highly mature environments with seamless collaboration between business, IT, and data functions, many organisations are better served by a centralised model, particularly in the early stages of data maturity. Centralised teams ensure consistency, improve visibility, and foster accountability. When business units push for embedded analytics support due to perceived lack of service, this is usually a symptom of poor demand planning rather than a structural issue.
-
Build Mutual Understanding Through Training
Business leaders and teams must be data-literate to identify opportunities and leverage insights effectively. Likewise, data professionals must understand the organisation’s strategic drivers, KPIs, and operational challenges. This two-way training not only improves collaboration but also ensures that analytics outputs are aligned with real business needs, enabling more relevant and impactful decision-making.
-
Attract Talent with Vision, Not Just Salary
Competitive compensation is important, but it’s not enough to attract and retain top data talent. High-performing professionals seek environments where data is respected, where leadership shows commitment, and where their work directly impacts strategic outcomes. By clearly communicating your data vision and demonstrating a structured investment plan, your organisation becomes a magnet for talent.
-
Capacitate for Delivery, Not Just Existence
Analytics teams must be adequately resourced to avoid burnout and reactive firefighting. Capacity can be built through full-time employees, contractors, hybrid models, or on-demand specialists, what matters is having the right mix for your business context. Strategic resource planning ensures teams spend more time on value-adding work, and less on scrambling to meet basic operational needs.
-
Mitigate Key-Person Risk
In many organisations, a few key data experts hold disproportionate responsibility. This creates significant risk, especially if documentation, standards, and knowledge-sharing are lacking. C-suite leaders must ensure that data outputs are standardised and well-documented, and that succession plans, or cross-skilling programmes are in place. If teams do not have time to document their work, that’s a red flag, reallocate resources before this becomes a costly issue.
-
Support Teams from the Top
Leadership support must be visible and consistent. Data teams should be tasked with delivering strategic business outcomes, not simply churning out reports. When teams constantly need to justify their existence or defend their value, morale drops. Once a key team member resigns, others often follow. Avoid this by aligning analytics goals with business outcomes and empowering your teams with trust and clarity.
-
Retention Requires More Than Money
Critical data skills are hard to replace. Retaining top talent requires meaningful work, fair recognition, growth opportunities, and a culture of inclusion. Hiring a Chief Data Officer or building a small analytics team is not enough. Without clean data, clear policies, and integrated systems, they will struggle to deliver impact. Retention, like value creation, is a holistic effort that spans the entire organisation.
Final Thought: The Human Edge in Data Value Creation
People are the most valuable, and volatile, asset in any data analytics initiative. They are also the element where executive leaders can have the most immediate and lasting impact. Building data capability is not a technical exercise; it is a business transformation that requires strategic clarity, intentional investment, and strong leadership alignment. Leaders who ignore this will find themselves in a cycle of missed opportunities, failed projects, and continuous rebuilding.
By focusing on value, resourcing strategically, and fostering a culture that respects and enables data talent, you break that cycle. The result is a high-performing, resilient analytics capability that drives sustained business value.
About the Author
Zjaen Coetzee, Chief Technology Officer at Nexus Data, brings nearly two decades of expertise in data analytics and has led data functions within major corporations. A bestselling, award-winning author, he is dedicated to empowering organizations to confidently unlock and realise business value through strategic and responsible use of data.
