Choose your language:



Hong Kong




New Zealand




United Kingdom

United States


Data Untangled

Swerving lines of bright light on a wet curved street at night


Every organisation has a not-so-secret weapon: data. Incredibly valuable information generated from every aspect of the enterprise. From research and development, to the supply chain, sales performance, human resources, marketing, operations as well as customer service and behavioural insights. Every activity in every facet of the business provides more data. Periphery data outside of businesses’ control, such as social media, syndicated or other public data, is critical too.

The volume of available data is almost incomprehensible. According to IDC the world’s collective data will grow from 33 zettabytes (ZB) in 2018 to 175 ZB by 2025.1

For organisations planning to stick around, harnessing the power of data is a business imperative because of the opportunity it holds: competitive differentiation. When armed with the knowledge and capabilities to digest data and extrapolate meaningful insights, organisations are poised to make informed and strategic decisions about all areas of the business. In turn, these data-driven decisions can help save time and money, create new revenue streams and exceed customer expectations.

Narrow triangle with multicolored streaks of light

Unfortunately, many organisations struggle with using data to their advantage. The reasons include:

  • Overcustomised technology: Legacy ERP systems can be overengineered to fit an enterprise’s precise needs. This level of customisation becomes burdensome to maintain and scale over time.
  • Costly new technology: Replacing the old with the new, on-premise implementations can be a massive investment.
  • Misguided technology selection: Best-in-class enterprise applications and systems demand the integration of multiple technologies; mistakes can be made in this important process, hampering connections. On the other hand, by going only with standardised platforms, organisations may sacrifice desired features and tools.
  • Managing expectations: Organisations need to recognise that for many of the niche skills required there is a shortage of professionals and the cost of employing them is high. As an example, most organisations admit needing an innovator who can deliver transformational analytics solutions, however many do not allocate the budget required to attract that calibre of talent.

Success with data starts with a data strategy

A data strategy helps organisations map the business objectives, needs and priorities they’re trying to solve with their data. It ensures future technology decisions and business activities are sound and aligned with enterprise goals. Establishing a data strategy—and reviewing it regularly—not only paves the way to informed decision-making and successful business outcomes, it also positions the organisation to competitively thrive.

In fact, research proves that productivity and profitability improve when an organisation is empowered by data. Businesses that strategically leverage their data see an estimated $430 billion in productivity benefits compared to their less data-friendly peers, according to the International Institute for Analytics.2 And organisations that incorporate big data and analytics into their operations realise productivity and profitability rates that are as high as 6% greater than the competition.3

Cost and productivity efficiencies directly help the bottom line. Data puts them one step ahead and ready to apply technologies such as AI and machine learning.

Shaping a Data Strategy

A well-informed, well-defined data strategy is your future-state blueprint. “Most companies know they need data, but they don’t know they need a data strategy. When they want to extract value out of the data, that’s where the rubber meets the road,” says David Spires, TEKsystems’ Executive Director of Applications Services. To be successful, a company’s data strategy needs to align with the broader goals of the business. Not only should the strategy be actionable but also comprehensive, considering the entire enterprise and not just one department.

Success with data

With the right data strategy in place, organisations set themselves up for success in one of three ways:

  1. Creating efficiencies that drive increased time and cost savings
  2. Identifying new or adjacent market opportunities that generate new revenue streams
  3. Strengthening relationships and loyalty through improved customer experiences

Mapping a data strategy

So how does a data strategy take shape?

To begin, an organisation should map out these necessary steps:

  1. Identify top data priorities for the whole enterprise and clarify intentions for practical data usage
  2. Establish a hypothesis, desired business outcomes and use cases (e.g., chatbot, natural language processing, machine learning)
  3. Define the type of data needed, identify data sources and plan the approach to data collection, ingestion, management, storage, analysis and governance

Throughout data strategy development, collaboration across the organisation is vital. IT, the chief data officer and all lines of business (e.g., marketing, finance, HR, sales and supply chain) need to work together. Collaboration ensures there is consistency and quality with the data, eliminates redundant data and aligns the business to a single source of truth.

Before going too far, businesses can establish a proof of concept, demonstrating that solutions work before scaling. Regular gut checks and quality assurance tell you if you’re on the right track or if you need to revisit your strategy.

Cascade of white light onto a dark blue background

Common Pitfalls

Avoid these frequent missteps when developing a data strategy:

  • No common denominator: There needs to be a leader, like a chief data officer, who can identify and resolve competing priorities within the organisation.
  • Technology vs. business-based decisions: Technology selection should be a component of executing the strategy rather than what drives the development of a strategy.
  • Hiring for the sake of hiring: Before hiring a data expert, be clear on the role this person will play.

Key Considerations

  • Business strategy: Data is only a competitive advantage when aligned to the business strategy.
  • Security: Proper privacy and security measures are essential to maintain integrity and trust.
  • Data democratisation: Gatekeepers create bottlenecks. A healthy strategy enables access and consumption of data across an organisation.
  • Empowerment: Enable employees to take advantage of insights through self-service solutions.
  • Monetisation: Identify opportunities through which data can enhance or extend products and services.

TEKsystems' Tips

  • Identify use cases: Determine the end goal you’re trying to reach.
  • Achieve quick wins: Understand what your use cases are and try to achieve some quick wins. This helps to justify the amount of time and effort behind the initiatives and the need to have a strategy in place.
  • Solicit feedback: Look for common data uses across lines of business to avoid redundancy.
  • Engage a strategic partner: Work with a full-stack partner that understands your data needs and goals across the enterprise. Make sure the partner can help craft the most effective strategy, technology selection and proof of concept.
  • Govern data: Data is an enterprise-wide asset. Establish policies and mechanisms to control and protect it.


David Spires, Executive Director of Applications Services, TEKsystems


  1. The Digitization of the World from Edge to Core, IDC
  2. Why Every Business Needs a Data and Analytics Strategy, Bernard Marr & Co.
  3. Making Advanced Analytics Work for You, Harvard Business Review

Disclaimer: The views and opinions expressed in this publication are those of the authors and do not necessarily reflect the views of TEKsystems, Inc. or its related entities.

Interested in speaking with TEKsystems?

Start a conversation