Unleash your Potential by Leveraging Data Analytics
It’s the year 2022, and the world continues to shift ever so rapidly. Certain industries have been disrupted by the pandemic while others have seen this as an opportunity for growth. It’s no secret that Digital Transformation has been at the helm of many enterprises’ strategies – but how many organisations have effectively implemented change or made decisions supported by data rather than intuition or necessity?
A study conducted by Forrester estimated that 60% to 73% of enterprise data goes unused for analytics, indicating that most companies are only benefiting from a fraction of the potential value of data and insights. The pandemic has presented organisations with more opportunities to track and measure data due to the acceleration of digitalisation which generates endless data points, giving organisations a chance to have a datadriven culture where data is embedded into the fabric of their operations.
Why Should Your Business Value Data Analytics?
As organisations seek to increase operational efficiency, improve profitability, or increase market share - analytics offers the ability to gather insights on areas of the business that previously were a distant reality.
Findings from an EY survey in 2020 showed that leaders in digital transformation are using data to help them stay ahead. Companies in every sector understand that they need to be quicker and more agile. Data Analytics can no longer be considered an afterthought or secondary activity. It is changing the basis of competition with leading organisations strategically leveraging it to manage business challenges, enhance core operations as well as develop new business models. It can be used as a key business driver, further enabling intelligent decisionmaking and should be a core element at the start of any new initiatives. Businesses that embraced analytics have significantly grown more than those that delayed in adoption. These entities have also been characterized by having extensive digitization of data and the adoption of analytics throughout the organization.
The same EY survey indicated that 83% of companies surveyed used insights from data and analytics to innovate at speed. It’s no surprise, as data is essentially a strategic asset in the ‘Digital Age’. Increased consumer touchpoints, Internet of Things (IoT) devices, payment systems, cameras, and various other data sources supply organisations with data in all types and forms. However, the value of data is ultimately tied to how it is used and applied.
Context is Key!
At the beginning of your analytics journey, it is important to clearly define a well-understood business use case. Some key questions to consider are:
• What insights do you hope to obtain?
• What are you looking to measure?
• What do you hope to achieve through analytics for your enterprise?
Establishing a set of prioritized use cases at the business functional level will ensure clarity and strategic guidance for each initiative - providing success criteria for measuring accomplishments.
Value Realization
Gathering actionable insights from data can yield great returns for a business. Insight is the value obtained from processing data. Analytics offers insights that help organizations make informed decisions to reduce risks associated with the trial-and-error approach. Research also suggests that insight-driven organisations have an average annual growth of more than 30%.
At the end of the day, what matters most is having tangible business outcomes. However, before data is transformed into actionable insights, it needs to be processed, and there are many ways to do so.
One remarkable thing about data is how it can be paired with almost any technology. Artificial Intelligence (AI) and Machine Learning (ML) have made great leaps in the field of analytics - augmenting human capabilities to deliver businesses with greater value. They automate routine, repeatable tasks offering enhanced efficiency and time spent on a process, also reducing human error. AI and ML have wide applications to drive business value. Some examples include increasing sales by forecasting demand and ensuring that warehouse stocking is appropriate, improving customer satisfaction by reducing delivery time and boosting operational efficiency by automating processes that would otherwise require a human. They can also be used to combat financial crime by comparing millions of transactions to distinguish between legitimate and fraudulent activities. The same tools paired with different data sets can also analyse consumer behaviour and recommend products based on those results, which in turn could lead to more revenue for an organisation.
Cloud innovation plays an immense role in helping the modern organisation build robust analytics platforms. The increase in data collected by organisations has influenced a great shift to the cloud for more efficient business performance. Cloud can help modernize the business core, power computing infrastructures, drive data strategies, and enable experiences across multiple functional areas. Many organizations across the globe have migrated their analytics capabilities to the cloud to process larger data sets. The ability to scale up and down resources also means enterprises can have a costefficient way of processing critical data.
Organisations should also consider investing in Business Intelligence Software (BI) which is a range of analytics tools designed to analyse and manage data related to your business operations. It offers visualization capabilities that allow businesses to monitor sales, logistics and even productivity. BI Tools assist analytics teams to organize data empowering key decision-makers to make informed decisions more rapidly. Presenting data in a format that’s easy to understand enables organisations to have a clearer picture of their strengths and weaknesses, furthermore, offering actionable insights into KPIs and other valuable metrics.
Effective Data Management
As organizations create and consume data at extraordinary rates, data management solutions become essential for making sense of the vast quantities of data. This is the process by which data is collected, organized, protected, and stored so it can be analysed for business decisions. Effective data management is crucial for deploying the systems and applications that provide analytical information to help drive operational decision-making and strategic planning. The accuracy, availability and integrity of data greatly affect analytics performance.
To get the best out of your analytics initiatives, it is wise to have a data strategy and architecture that standardizes data practices across the organisation. A solution to consider is, “Data Fabric”. It is defined as “an architectural approach to simplify data access in an organization to facilitate self-service data consumption (the process of leveraging insights)”. It essentially standardizes data management practices and practicalities across the cloud, on-premises, and other environments enabling enterprises to use data to maximize their value chain.
Data fabric combines key data management technologies such as data catalogue, data governance and data integration, furthermore, enabling the automation of the movement of data from different sources and combining it to be available for analysis tools.
Some key benefits include:
• Reducing time to insights and making more informed decisions by transferring data into different repositories reliably and quickly.
Real-time 360 views of the business entity. Self-service data access capabilities allow users to get the data they need, whenever they need it, for increased business agility and speed.
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Embrace Analytics
There are endless use cases for data analytics. Analytics can be used in agriculture to provide more consistent yields, in mining to analyse underground images and in healthcare to help discover and cure diseases. Datadriven transformation can also help enterprises adapt, rise, and thrive in our ever-changing world. As the digital world evolves and enters new territories, so will the application of analytics – fuelling new ways of thinking and providing fresh perspectives of how we view the world as we know it.
Now begs the question, is data analytics a key part of the decision-making processes in your organisation?
At EY, Data and Insight Transformation helps clients to understand and leverage their data and data transformation methods to solve business problems; build a trusted data fabric to standardize, reuse and scale data and data models; and use data analytics to develop business insights and improve decisionmaking. Regardless of where the journey starts, our Transformative Solutions help clients find a pathway to deliver long-term value.
To find out more contact Mafaro Timba | Senior | Technology Consulting on:
Email: mafaro.timba@zw.ey.com or eymarketing@zw.ey.com Address: Angwa City Building, Corner Julius Nyerere Way/ Kwame Nkrumah Avenue. P O Box 62, Harare, Zimbabwe. Tel: +263 4 750905/ 750979
This article was compiled by EY as a source of general information and notification and should not be construed as a formal professional/legal opinion. Although reasonable skill and care is taken when providing information, EY offer no warranties or representations as to the information’s accuracy. The information provided is not intended to replace the need for an expert/ legal opinion on interpretation, application and consequences of the relevant legal, technical or regulatory provisions. E Y does not accept responsibility for any loss or damage you or any third party may suffer as a result of utilising the information provided.