Insights > Insights from Data Can Sharpen the Competitive Edge

Insights from Data Can Sharpen the Competitive Edge

Competing in the modern business era requires every function to do more with less and to deal with a diverse set of decisions and criteria. Whether a company seeks to improve its customer experience or back-office reporting, it needs a technical architecture that provides resilient operations and enables insights to foresee imminent business disruptions. Data is a valuable asset that —once collected and stored properly— stays with the company, and it can enable better decisions giving a competitive advantage within an organization.

Optimizing data collection and analysis methods can powerfully impact various business functions, but several roadblocks may occur during this journey, causing organizations to realize their goals in a substandard fashion. Instances such as network outages, network access issues, and overwhelming online traffic have all caused customer experience to deteriorate and cut into profits. It helps to start by examining common gaps and roadblocks for data-driven initiatives:

Unscalable, outdated systems: Businesses across several industries often have legacy, home-grown applications that store proprietary data that cannot be transferred to a modern application. Further, unsophisticated and outdated systems often lack the proper scalability to meet future business growth and regulatory demands and result in an overall lack of automation and controls.

Cluttered and chaotic data: The data and related insights that can help differentiate a company can be lost due to poor data collection at the sources and lack of data transferability across platforms. Companies also frequently fall into the trap of collecting as much data as possible, some of which is not needed, thereby creating “noise” and failing to create credible business insights.

“Gut” decision-making habits: Company culture, often driven from executives, impacts how data gets used in driving business decisions. The absence of meaningful data often leads to ineffective budgets and developing business strategies that lack relevant market focus. Further, inadequate data can force companies to act in reactive ways as opposed to being proactive.

Lengthy, opaque modernization efforts: Multi-year implementations and siloed efforts for technology transformations often lead to a loss in its value impact.

Although these challenges are prevalent, companies that seek to remain competitive cannot afford to ignore a data-driven approach any longer. Companies seeking to scale and be more agile to meet market demands need to consider modernizing the data collection methods and the architecture that supports data analysis architecture.

To enable a modern approach to data, organizations must be willing to spend appropriate technology investment in the near term to enable a suitable data-driven strategy. In addition, the proper data governance and infrastructure must be aligned to support the strategy long term.

Mobilizing a data-driven strategy

To address common gaps, a data-driven strategy needs to be developed leveraging insights from historical past performance to help influence the roadmap for a company’s future vision. An impactful data-driven strategy includes developing company performance metrics that are visible to the team and showcase key areas of strength, such as which implementations have been successful, where the most profitable customers are coming from, what areas can drive the best cost savings or efficient level of effort, and so forth.

Business and technology leaders can develop a robust data-centric strategy by using the following tactics:

1) Develop an operating model backed by data

Developing a modernization approach that is collaborative from the beginning helps businesses to align expectations and analyze the downstream or upstream impacts of any technology initiative. A collaborative approach also avoids delays as it helps foresee interdependencies and downstream issues early in the process. It also enables easier adoption by the stakeholders, especially when the individuals have a voice in building the solution.

To develop meaningful insights, data collection needs to happen at scale across all business units and geographies. To ensure adequate coverage, a company’s IT organization should develop the capabilities to partner with different business functions and the technology platforms to capture data for all target purposes.

Infrastructure that will house all this data is like the backbone of the company. Understanding requirements regarding on-premises, public, and private cloud will be essential for faster data processing, adequate data storage and data retention capabilities. To enable a robust infrastructure architecture that supports the goals of a company, it must develop an operating model that considers whether a data center or surge networking capacity is required.

2) Undertake a relevant technology transformation, using an agile approach

Over time, outdated and redundant systems overload the infrastructure as well as maintenance staff to keep them running. Modernizing, and preferably replacing these systems, with a set of integrated solutions, will reduce the burden on IT and other related functional areas.

To get started, businesses should assess the current landscape and develop a system roadmap to be ready for the future. Organizations can leverage the latest proven software applications via a sophisticated vendor selection process to automate repetitive processes and collect relevant data. This includes assessing and rationalizing the organization’s system landscape. It is also important to establish security access and protocols during these implementations to address cyber security, data retention, and other internal audit requirements.

To ensure success, teams should develop an agile approach to project deliveries that will enable flexibility and help prioritize projects that offer rapid, accretive results. By performing multiple sprints and developing proofs-of-concept and robust testing at each phase, agile delivery will provide the quality and value that most companies desire.

3) Develop an enterprise reporting strategy

Simplification of data is just as important as the collection. Data must be contextualized and delivered to internal and external customers in a meaningful way that can help them make decisions that help address current needs and uncover new potential.

For an effective last mile of this journey, leaders and key stakeholders of each organization should be willing to make decisions based on the story data is telling. Enabling them with appropriate visualization and analytics is critical.

Related Success Story

Riveron engaged with an urgent care clinic that has been on a transformational journey to scale its business and grow specific business services. Years of data existed related to patient visits that were organized in a variety of ways such as by diagnosis, by payer, etc., but the healthcare organization had no accurate way to tell a story to the stakeholders and outline what approaches were working or not. In short, it was difficult to make informed decisions, and Riveron worked with the organization to develop insightful analytics showcasing a decade of patient return histories. This data could be organized by patient demographics, diagnoses, and care center locations. Ultimately, this provided comprehensive analytics on return visit patterns of patients and thereby offered several insightful key performance indicators (KPIs) for the team. These included average visits per patient, COVID-19 impacts on the business model, demographic-based analyses, and several other specifics. Enabled by the new outputs and approach, the care clinic’s decision-making team can now assess business growth drivers with accuracy and develop a better business roadmap to realize new potential.

Lastly, businesses should educate and train internal resources to cultivate knowledge internally. It is critical to develop in-house capabilities, which encourage employees to be more productive in their day-to-day work. It also reduces bottom-line costs associated with employees quitting and avoids low motivation resulting in loss of productivity. By having employees and key stakeholders take ownership of the final delivery, there is an increased sense of accountability that will ultimately result in having a better-quality end product and better adoption by the user community.

The role of a traditional IT function has evolved over the last few years from being simply a support function to now being an extension of the business delivery to front-end customers, stakeholders, and employees. This elevated role adds responsibilities such as anticipating new requirements (for example, ESG reporting), and assessing how different technologies can support overall business goals, enable better insights, and drive automation. Together with new technologies and software platforms, data can enable IT to play an enhanced, critical role in the company. Having robust access to data and a resilient data strategy can help companies to make informed and timely decisions, improve profitability, and enable organizations to do more with less.

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