Comprehensive data management enables decision-making for CIO and CFO functions

CIO and CFO functions face data integrity challenges with the sheer amount of data generated, which has to be addressed for reliable business outcomes. The data quality issues are usually due to human errors, migration from legacy or disparate systems, obsolete/redundant data, etc.  The issues could be many and to address these, enterprises must look at data comprehensively to enable impactful business outcomes. Enterprises are always seeking unified solutions that address their data strategy, a solution that helps them manage data residency, security, severity, governance, and quality.

In the 2022 HFS Pulse survey data in Exhibit 1, leadership’s ability to use data as a business asset is among the top priorities of the leadership agenda today across the Global 2000 companies for bringing more value to business outcomes and delivering employee and customer experience.

However, enterprises in Exhibit 2 face challenges in the automation of data and lack of centralized data governance across the organization, leading to challenges in meeting their strategic objectives.

Exhibit 1: Increasing leadership priority to use data as an asset in decision making

Sample Size: 123 executives across Global 2000 enterprises
Source: HFS Pulse Dashboard, 2022

Syniti recognized these exact challenges—a lack of data quality, residency, migration, and governance—and it built its data quality and matching capabilities into its new unified Knowledge Platform to address enterprises’ needs.

A unified solution that helps in data strategy and security

Leaning on the learnings from the marketplace for a SaaS solution that connects to the customer’s landscape and is faster and easier to use with a streamlined UI/UX, the Syniti Knowledge Platform enables enterprises to keep their data where they want to—whether behind their own firewall or with their hyperscaler. Unlike many point-based solutions, the platform provides a one-stop solution to all data needs to enable a data strategy for an enterprise.

New data quality and catalog capabilities deliver business value

Syniti brings data management capabilities to life by viewing systems with a metadata perspective and trying to bring data strategy to software. The automation delivers metadata scanning and profiling through which it can sample data, manage exceptions, create a central data catalog, and it has smart rule recommendations. Linking data to business initiatives and goals provides a perspective on how to achieve an initiative or goal, but the data quality has a large impact on such insights. Syniti’s new capabilities enable efficient data management and improved business processes, delivering an ability to link data to functional KPIs. In HFS’ view, the linkage to KPIs enables stronger business cases and ROI measurements than traditional approaches to data quality, no longer letting it be just an IT-centric initiative.

Exhibit 2: Data management challenges to meet the company’s strategic objectives

Sample: HFS Pulse Dashboard, 602 executives across Global 2000 enterprises
Source: HFS Research 2022

The AI-driven matching capability supports the party and operational data

Operational data can be quite complex and captures multiple fields from supply chain and ERP systems, like vendor and supplier data, items, equipment, product descriptions, business partners, and SKUs. For a global enterprise, this data can be captured in different forms, languages, and formats, often resulting in duplications, and missing or mistyped fields and sometimes leading to a struggle with data quality, productivity leaks, and higher inventory impacting the bottom line. Syniti’s operational data-matching capability addresses this exact issue through its proprietary algorithm. Working on data quality and remediation in the analytics stack is not an optimum data strategy, so addressing this in transactional and operational systems that improve data quality before reporting it to the analytics team is the key. Syniti has been investing in this capability and recently added it to its platform as a module within the SKP; the solution is also available as a standalone. Syniti’s offering in this space targets the worthy goal of helping clients fix data at the source rather than downstream.

The Bottom Line: Syniti targets the right business problems, and its “all-encompassing” approach to developing SKP could be just what clients need to make progress on data quality and governance.

Data quality management is a continuous process as enterprises integrate data analytics to drive efficient decision-making and target new avenues of growth. A data quality strategy with intelligent data quality tools reduces operational inefficiencies and brings better data governance helping enterprises derive exponential value out of data.

Syniti has gauged this mandate well and has tailored its enterprise data management capabilities to provide what the market demands. It brings value to its customers via its integrated UI/UX with multiple persona-based approaches, all modules at a single location, and easy access to data by breaking down traditional silos of data.