Data lies at the core of any organization. This is evident from the fact that data-driven organizations are 23 times more likely to acquire new customers, six times as likely to retain existing customers, and 19 times as likely to gain profit consequently, as revealed in a report by McKinsey Global Institute.
These findings reinforce that a digital transformation journey starts with defining your data strategy.
The First Step to Digital Transformation
Any digital transformation requires data transformation to be effective. Digital transformation initiatives are only as powerful as their ability to help enterprises transform and evolve into their next intended state: be it in terms of profitability, cost reduction, customer acquisition, growth, expansion, time to market, and so on.
Businesses, therefore, that accelerate the shift to new solutions that empower business intelligence, such as SAP S/4HANA, will unlock new business value and help gain a competitive advantage.
Invariably, the first step to digital transformation then is to define the organizational vision and identity post-transformation. By doing so, it becomes easy to measure any progress against intended KPIs for the future.
These KPIs will set benchmarks and guideposts for all business data that should be reported and accessed throughout the organization, allowing leaders to develop a holistic data strategy that reflects the potential of these metrics.
Establishing trusted business data is a prerequisite to deriving value from it. Often underestimated, but critical to data success are data quality, completeness, and accuracy. SAP S/4HANA is a critical facilitator of digital and data transformation for many organizations.
Since there are a number of critical data points involved in a digital transformation journey, it can get challenging to find the starting point. Taking on a holistic, 360-degree view of the organization’s data journey is key.
A lot of digital transformation strategies offer sophisticated data analytics. But the successful ones will help cross-functionally leverage data and analytics to bring priority outcomes faster.
The Role of AI and ML in a Data-driven Reality
AI and ML top the wishlists of CIOs and CEOs. However, to realize the full potential of AI and ML, organizations need data that is relevant and accurate. You need to trust the sources of this data and it needs to be governed across the organization properly.
Data is a critical piece for AI and machine learning puzzle for them to learn to evolve in the changing landscape and make smarter recommendations for the business. For valuable data reuse, information from the past and the present must be preserved.
Many CEOs struggle to identify the most relevant and accurate versions of their data owing to poor data quality and gaps in governance. These companies need a trusted source from which their data is managed by following best practices through automation and standardized data definitions.
Once data trust and governance are laid out, AI and ML can be executed to maximize business gains.
Data Strategy Beyond Data Management
Trusted data can be beneficial if it aligns with business context and compliances. Executing governance for low-volume data is not an issue. But when we talk about millions of transactions and data, we need robust processes and tools in place.
This is the shortest path for business owners to manage and leverage critical data. For this, stakeholders need to know which data is high-priority, which data sources can be trusted, and which individuals can contribute to maintaining the quality of data.
Companies also need to lay down the business processes and rules that must be followed to ensure a concrete and sustainable governance program.
Real-time Compliances with Next-gen Automation
Organizations in all industries must align with prevalent compliances and regulations. These change frequently and can have costly consequences for non-compliance.
However, mapping relevant compliance rules to your key data is straightforward for any organization that has a clearly defined set of critical data elements and trustworthy data sources.
To navigate the GDPR compliances, for example, companies can track the use and storage of data across the enterprise and ensure compliance by automating rules around this data. Then, they can easily navigate changes in compliances and evolve governance programs to adapt to shifting data elements.
Ensuring Satisfactory ROI Generation
When you have clarity over the metrics to measure business results, the intended benefits are easy to realize. The dynamics of data management can be tricky.
The holistic data equation has its roots in clean, governed, trusted data, which drives the ROI of the entire transformation journey. From this point onward, the transformation only delivers higher ROI as organizations benefit from increased productivity, response rates, and the use of other value-added activities.
Insights-driven businesses are growing at a rate of over 30 percent every year, and by 2020, will take $1.8 trillion annually from their less data-aware peers.
itelligence is one of the leading full-service providers of SAP solutions. Being an SAP Platinum Partner, itelligence offers SAP-certified package solutions which deliver promised ROI over a short period of time. Get in touch with us today to learn more.