Three Steps to Invest Intelligently in Data Innovation for Rapid Returns
"Data is just data if we do not deliver business value." This is something you might often read or hear about when big data opportunities are discussed. And these opportunities are not showing any signs of slowing down as more businesses move quicker with their digital transformation.
The big data and analytics market in Latin America alone was expected to generate 4.96 billion U.S. dollars in revenues, up from 2.9 billion reported in 2017. It is forecasted now to grow further and reach 8.5 billion in 2023. IT spending in Latin America is also expected to grow 7.7 percent this year, with Argentina and Mexico taking 1st and 2nd places in this race.
Even as we see all these positive trends, customers are still struggling with legacy and current data infrastructure, architecture, tools, processes, and staff which lack the flexibility and agility that data-driven organizations require. To get there, companies need new data strategies, and above all, a data transformation strategy that can promise return-on-investment, both in dollars and in innovation.
I. A transformative data strategy
First, we help them build a data strategy that will enable their transformation goals. What does a data strategy entail? At Alldatum, our passion is delivering and helping customers with not their data management but their data experience. A successful data strategy requires a partner who can accompany customers on their transformation journey and remain top-of-their-game and be responsive to challenges presented by the digital economy and data management initiatives.
Market demands and available technologies change all the time, and with a reliable transformation partner, customers are assured of the best information and choices to make their decisions. Remember that there is no one-size-fits-all approach for a transformative data strategy. It must be tailor-made to the organization while learning from best practices and tested solutions.
Alldatum has developed trained human capital with experience and values to support success and impact all our customers' businesses. We also partner with leading solutions providers like TIBCO, leveraging industry-acknowledged solutions like leveraging TIBCO EBX™ and TIBCO Data Virtualization towards our customers' goals.
II. Filling in data management gaps
Second, we work with customers to identify and fill their data management tool gaps. For some, it is around Master Data Management or Data Governance. For others, it might be around data quality. Either way and amongst a host of other potential data management gaps, it is vital to apply an integrated approach, especially given the cloud's disruptive nature and the growing convergence of traditional data management silos.
When we encounter data gaps, the potential errors within databases can skew a company's business strategies and impact product and solution development, forecasting sales and operational pipeline, and eventually the company's bottom line.
Imagine that there are three databases in a bank, each with more than 2,000 rows and more than 300 columns with detailed information on its customers. Now imagine that in each database, there is incorrect data for each customer, either because there was an error when entering the data because it has not been updated (for example, email, cell phone number, or a change of address), or because they have intentionally provided incorrect data.
Without the proper data governance policies in place, these errors result in what we call "Dirty Data." Each instance of "Dirty Data" changes the outcomes of any analytics and insights-driven decision, thus providing misinformation to key stakeholders, and in turn, developing the wrong customer acquisition and retention strategies. Before embarking on your strategy, set the expectations to understand the potential data gaps, what can be put in place to provide a view of all master and reference data sources, and then set benchmarks on what constitutes data management practices within your organization.
III. Address data governance with agility and focus
Lastly, we address data governance, focusing on providing necessary controls and meeting growing regulatory and security requirements. Within your data transformation strategy, it is imperative to ensure that you collect, create, own, and manage only trusted and complete data. Data governance and data management must be in place to address regulatory compliance, operational improvement, reporting quality, and customer experience. Integrating data management with a data governance program that incorporates documentation of definitions, ownership, policies, and procedures solves the problem.
One of the ways we have seen our customers achieve this is to use TIBCO EBX, a single platform for managing any kind of data asset, including master data, reference data, and metadata. Its multidomain approach enables our customers to support both data governance and data management initiatives. Having said that, EBX is more than just an MDM platform, but offers a complete Data Management Solution that has everything in a unified package and allows for seamless integration with other data management offerings. It uses a unique what-you-model-is-what-you-get design approach with applications generated on the fly and fully configurable. This way, we eliminate the need for long, costly, and endless development projects.
Our customers are well aware of the monetary investments they need to come up with if they are to compete in the digital age effectively. So, it is a question of investing intelligently and getting rapid returns that can fund additional investments. That is why we start by developing the data strategy as that becomes the investment roadmap.
Take the 80/20 rule – we want to focus on the top 20% of high-value opportunities that can yield 80% of the return. Using this approach, we evaluate and shortlist these opportunities and implement whatever data management and data governance capabilities are needed to realize that opportunity. Then, we go after the next opportunity and methodically build more modern data management and governance infrastructure as we go.