Key data & analytics trends that drive business growth
Data has always been collected by organisations around their products and solutions for several decades. Irrespective of the nature of the business, data provides critical insights that enable the business to take decisions around strategy, growth, revenue, innovation, employees, and customers.
In the past, data collection was done in a centralised and controlled manner where data resided within the business collecting it. Within companies, data collected by individual functions was largely limited to the scope of operation of the function and only aggregated and analysed for executives. This data was largely used for strategy and business purposes and not very concerned with customers or employees.
Tools and technologies were limited in their ability to collect and process data quickly. Analytics was performed on data already collected so the insights were largely around past data typically until the prior month. Data analysis cycle times used to be much longer given limitations around collecting near real-time data and having the right tools integrated for quick analysis. These capabilities serviced the needs of the business where environment and technology changes were much slower. And even in that case, businesses have succumbed to disruptive innovations because of ignoring data and analysis.
This article shares areas of data and analytics that will drive business growth in the next few years.
Today, businesses have made customer centricity their focus. They have multiple vendor and partner relationships and are capturing data both within and from every phase of a customer’s journey for near real-time data analysis. This is driven by tools, such as advanced data collection mechanisms and AI, that are fundamental to business success today. Also, the overall uncertainty in business environments as compared to the past has made data and analytics crucial pillars of business growth.
Presented below are 4 trends around data and analytics that will drive business growth in the coming years.
- Data fabrics, Data centric AI and Adaptive AI systems: Data management strategies need to be in place to ensure that data collected considers dimensions of bias, diversity and context in systematic ways so that AI systems can provide more accurate, reliable and clear insights. This means that Data fabrics or the layer that connects processes with data, receiving, analysing metadata assets to design, deploy and utilise data across all kinds of environments such as hybrid and multi-cloud platforms. These in-turn feed into adaptive AI systems that offer faster and flexible decisions based on changing situations. Businesses and their partners can leverage such systems to quickly change and drive growth. This kind of a system calls for AI engineering practices to orchestrate and optimise applications to adapt and absorb disruptions.
- Sharing Data and Connected Governance: Knowing how to share data and analytics at scale is key to growing business. Another critical factor here is establishing trust across the shared data network that comprises the business, its vendors, partners, local communities, governance and compliance. Increasing access to the right data in a timely manner across this network can drive collaboration and improve response times for the business while increasing budgets for investment in data sharing. The advantages of sharing the right data far outweigh the risks for a business. Shared data can solve operational challenges and businesses can become highly responsive to changing market dynamics and organisational needs.
- Context Enrichment and Analysis: Data on users is continuously growing and being enriched by constant analysis. Finding deeper relationships from varied data points quickly creates deeper context to identify similarities, differences, preferences, and trends, enabling fast responses to changing needs of customers. This helps businesses adapt, turn around and deliver newer and more effective products to customers thereby driving business.
- Expansion to the Edge: Today’s data environments are scattered rather than originating from a single source. Customers use multiple devices to access data. Since businesses are working with partner networks, useful and most important data and analyses are available and created in edge computing environments, largely located outside proprietary data centres. Companies that provide safe and timely access to data with technology, like small-footprint embedded databases for storage and processing of data at the edge, are poised to drive business growth. Gartner estimates that more than 50% of enterprise-critical data will be created and processed outside data centres.
To conclude, the areas highlighted above are where businesses will prioritise investments to drive new growth, optimally improve operational efficiency and agility* and deliver cutting edge, disruptive innovation. Growing these areas offers companies resilience to handle ever-dynamic markets, create networks of trust to share data, and augment decisions that can help scale and drive business growth.
*For organizations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed on organizational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive, yet modular suite of services is doing exactly that. Equipping organizations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organizations that are innovating collaboratively for the future.