Unlocking the most underutilised assets in most companies. What, when and why makes Data so valuable?
Data is an integral part of every business in every industry and translates into a growing share of competitive advantage for every organisation.
Yet most organisations produce more data than they can efficiently manage and use in day-to-day operations. Moreover, all of them face similar problems, as data is unreliable, hard to access or requires an expert skill set.
Now, let’s start with ‘When’.
When is data valuable?
Data is valuable when it’s accessible and reliable at the same time. Data can deliver its full potential only when you can access the right, reliable data at the right time. As data informs decisions or powers the algorithms behind automation, if you can be sure that something is true, you can act on it confidently.
Accessing and using the correct and reliable data when and where it is needed is becoming critical to efficient value-creation for any organisation.
→ Examples
Accessible and reliable data in healthcare:
In a hospital environment, medical professionals require rapid access to precise and current patient information to make vital decisions about treatment plans. With a dependable and easily accessible electronic health records (EHR) system, healthcare providers are empowered to make well-informed judgments, leading to better patient outcomes and a decrease in medical errors.
Right data at the right time in retail:
A retail company that operates a chain of stores needs to make data-driven decisions about inventory management, pricing, and promotional activities. When their data analytics system provides accurate, real-time information about customer demand and sales trends, store managers can adjust inventory levels and pricing strategies accordingly, leading to increased sales and reduced costs related to overstocking or stockouts.
Data-driven automation in manufacturing:
For a manufacturing company, keeping a close eye on equipment performance is crucial to avoid costly downtime or maintenance expenses. The company can make informed decisions about when to schedule maintenance based on real-time, reliable data by relying on data collected from sensors and IoT devices installed across production lines. This allows for implementing predictive maintenance algorithms to minimise downtime, reduce maintenance costs, and ultimately increase overall equipment effectiveness.
Timely and reliable data in finance:
In the finance industry, investment firms and traders rely on accurate, real-time market data to make informed decisions about buying and selling assets. When financial data platforms provide reliable and up-to-date information on stock prices, economic indicators, and market trends, investors can confidently execute their trades and strategies, capitalising on opportunities and minimising risk. This efficient value creation ultimately contributes to the growth and stability of financial markets.
Why is data so valuable?
Data is the only resource you don’t need to spend to create value. When you utilise data to create value, it doesn’t disappear.
Data is highly reusable and replicable. Copying data is simple. Once data is cleared and available (as today, everyone works with data), it can improve work across all departments.
Data can be omnipresent and portable. The same information can be displayed in many places at once, ready to help multiple consumers make informed decisions simultaneously.
→ Examples
Data-driven marketing campaigns:
A company can analyse customer behaviour data to create targeted marketing campaigns without spending additional resources. This approach maximises the return on investment by reaching the right audience with the right message at the right time, increasing sales and customer loyalty.
Leveraging data in the automotive industry:
Car manufacturers can use data collected from vehicle sensors to improve their products without incurring additional costs. By analysing data on fuel efficiency, driving patterns, and maintenance issues, they can identify areas for improvement and optimise their vehicles’ performance, enhancing customer satisfaction and brand loyalty.
Reusing data in medical research:
Medical researchers have the opportunity to analyse anonymised patient data from various studies to uncover correlations and patterns that may have otherwise gone unnoticed. This data reuse can result in fresh insights, enhanced treatments, and a deeper understanding of disease mechanisms without the need for costly new studies.
Copying data for disaster recovery:
Businesses can easily create copies of their critical data and store them offsite to protect against data loss due to natural disasters, hardware failures, or cyber-attacks. This simple act of copying and backing up data ensures business continuity and reduces the risk of losing valuable information.
Improving efficiency in a manufacturing company:
By making data on production processes and resource allocation available to all departments, a manufacturing company can identify inefficiencies, streamline workflows, and reduce waste, leading to higher productivity and lower costs.
Data portability in the travel industry:
A travel booking platform can gather data on customer preferences, booking history, and travel patterns, making this information accessible across devices and platforms. This enables the platform to provide personalised recommendations, tailored offers, and seamless booking experiences for customers, regardless of where they access the service.
Real-time data access in supply chain management:
In a large retail organisation, having real-time inventory data available to multiple stakeholders enables better decision-making across the supply chain. Warehouse managers, store managers, and procurement teams can all access the same data simultaneously, allowing them to make informed decisions about stock levels, product ordering, and demand forecasting, ultimately improving overall supply chain efficiency.
What makes data so valuable?
Data helps organisations understand performance, allocate resources efficiently, and provide the clarity needed for better results.
Data helps identify problems, describes new opportunities, and boosts productivity by powering automation. Data helps predict behaviour, reduces the cost of sale, and improves operational efficiency enriching any other organisational assets.
Data can generate value directly by being prepared and monetised as a new product or service.
→ Examples
Data improving performance and resource allocation:
A logistics company uses data on delivery routes, fuel consumption, and traffic patterns to optimise resource allocation, reducing costs and improving delivery times.
Data identifying problems and powering automation:
A manufacturing company uses sensor data from production lines to detect equipment failures and automate maintenance schedules, preventing downtime and improving overall productivity.
Data predicting behaviour and improving efficiency:
An energy provider uses smart meter data to predict customer demand patterns, allowing them to optimise energy production and distribution, reducing costs and improving service reliability.
Data generating value through monetisation:
A fitness app company collects anonymised user data on workout habits and sells it to sports equipment manufacturers, providing them with valuable insights for product development and marketing.
Better data makes better companies, so ensure your data is ready to work on all tomorrow's problems.
Electricity infrastructure propelled the potential of the industrial revolution to get us to the comforts of today’s life.
AI may be the missing key to unleashing the full potential of data democratisation so that we can enrich our personal and professional lives through data.
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