Today, data is the foundation for everything, from knowing customers better to driving smarter product and services roadmaps, and beyond. But without a clearly defined data strategy, organizations find themselves awash in data yet unsure how to analyze and leverage it. Here are three imperatives for putting a rock-solid data strategy at the core of an intelligent enterprise.
Build for Standardization
When every function is siloed and handles its data differently, the Enterprise never “knows” all that it can know. The result? Muddled decision-making, needless re-work, and wasted resources.
Standardization is the key. Democratizing data ensures faster, smarter, better decision-making. With good data governance, enterprises can democratize and still ensure compliance with data, security and privacy standards.
Also, companies need to ensure definitions are consistent and well-organized across the enterprise. Building a business glossary can help people catalogue data properly to enable consistency and reusability.
For best success, organizations should avoid a top-down mandate. Instead, they can provide a forum for individual business leaders to talk about their needs and what can be done to meet those needs. Aim for real and lasting consensus.
Build for Scalability
With rapid growth in data volume, variety and velocity, companies need a data management solution that can keep up.
For example, in marketing there are many more new sources of data including social media and location data. If the organization checks these only once per day, it will miss critical signals and fleeting opportunities. To unlock the value in these large data volumes, companies need to integrate data into data lakes and data-warehouses for easier retrieval and sharper insights.
Investing in the right cloud infrastructure enables companies to extract data from multiple, disparate systems and transform it into analytics-ready information — and, ultimately, valuable insights.
Build for Success
Data and analytics can give an organization the answers it needs to shrink waste and drive growth. But good analytics begins with asking the right questions, and smarter questions begin with data literacy.
Everyone – from the data-entry operator, technical programmer, analyst, or user – needs to understand the importance of data and how it will be used to drive decisions. This is especially true in large enterprises, where a seemingly trivial decision by a data-entry operator will ripple through a complex global supply chain.
Data requirements must be aligned with the business goals. What data sources will the business use, what data is required, and how often must that data be collected, analyzed, and refreshed? What third-party data should be leveraged to add value? To ensure data quality, establish thresholds for key data elements.
It’s also critical to invest the time and effort to really understand the organization’s business goals. What answers are needed? Where there are multiple answers needed, which questions must be answered first, and how can the company prioritize them?
In the end, the leadership of a business must lead. The business team needs to take full ownership of data needs and drives incremental improvements.
Elements of a Successful Data Strategy
|Clear business goals||Helps ensure that the right questions are asked and answered|
|Clear processes||Guides the organization to be coordinated and uniform about data|
|Clear roles and responsibilities||Ensures the right people are taking care of what matters most|
|The right tools and technologies||Makes it easy and efficient to get critical work done|
|Standardization, data quality,
democratization, and data governance
|Ensures that data is available, ready to be used, and used responsibly|
Investing the time and effort to build the right data strategy now will pay dividends far into the future. For more about how Wipro can help, including lessons learned from successful engagements, please contact email@example.com