What the data analyst wants the company to understand about benchmark data


by Analytics Insight


December 15, 2020

Every executive now talks about the value of a data-driven business and culture. It’s all well and good; However, many fail to understand that a comprehensive data management plan is often the foundation for early business value creation. The result is that they don’t always actively promote usage or changes in the way the business manages data. Specifically, data widely shared in a logical manner across the enterprise that tends to change slowly because it cannot see the end results on its own.

Without a master data plan, there is no real incentive for business leaders to cooperate to eliminate data silos. There are also no consequences specific to them when they don’t. This impairs the ability of data analysts to make high-level customer or supplier data consistent across various business processes, applications, and data platforms.

Having to continually manually resolve errors in master data for entities that live in multiple functions and have varying levels of granularity is both time consuming and resource intensive. Worse yet, data instability decreases the efficiency of reporting, analysis and decision-making, and can also erode the performance of key business processes.

Data management therefore continues to take a back seat to almost everything business leaders deem important to do to achieve enterprise-wide digital transformation. But the point is that well-managed and well-governed benchmarks are a prerequisite for achieving

enterprise-wide digital transformation. Since, by definition, all applications are based on master data, their integrity must be ensured.

What many business leaders have not fully recognized is that if database analysts do not receive the support and resources necessary to stabilize master data across different operational systems and business platforms. Analysis, the ability to execute collaborative business opportunities is compromised. The same goes for multi-brand promotions, as there is an increased likelihood of making uninformed decisions based on inaccurate reporting and inaccurate information resources.

How will the dynamics change?

A data analyst, and even a data manager, usually don’t have enough access high up in the business chain to directly explain why it’s important to change the priorities, and possibly the culture, of the organization so that everyone plays a role. part role to make the data excellent. They alone are not empowered to force business stakeholders to invest in efforts to define and manage critical data for an organization on the way to a single point of reference. These efforts must encompass business processes, governance policies, and technology to provide a reliable database across the enterprise.

But such a change can only happen if C-level leaders are faced with a major situation that reveals that something is rotten in the state of the data. The C-Suite may have historically been shielded from the challenges that data analysts regularly face when attempting to reconcile, link, synchronize, and publish master data across different processes, systems, and analytics. But the following incidents could finally make it clear that data management is not an IT problem, but rather a fundamental business enabler:

  • Declining revenues and market share: A leader in its industry for decades, with a healthy position, an organization realizes that its market share has declined over the past year. This steady, albeit slow, decline has started to make senior management and board nervous as they mull over the root of the problem. Are their competitors doing a better job of marketing or are they converting new and / or incremental net sales at a faster rate? Or do they move more efficiently and faster because they can rely on trusted data analytics, where dots are all connected between business systems and processes using master data? clean and consistent? The reality is that clear, accurate data is the key enabler of all of these strategies, and is reflected by Forrester who says all knowledge-driven businesses are growing on average over 30% per year and are on track to earn 1 , $ 8 trillion by 2021..
  • Complications of merger and acquisition: It takes a long time to identify, plan, implement and close a merger and acquisition transaction designed to help the company gain a competitive advantage or diversify its services. Once executed, leaders want to see return on investment as soon as possible. But if the data and semantics are inconsistent across several internal areas within the new business, things get off to a bad start. Additionally, the lack of data coordination within one organization will make it even more difficult for data and systems to converge with each other. Along with the foresight to manage data consolidation carefully and proactively, sales and profitability will be further hampered by the inability to quickly create reliable reports and analysis.

Any business facing such concerns will hopefully make its senior executives realize that building a data-driven culture starts at the top and works its way down the line of business. Data analysts will be the first to applaud the revolution, followed closely by the balance sheet.

About the Author:

Bill O’Kane is Vice President and MDM Strategist at Profisee, a pioneer in master data management (MDM) solutions. To learn more, visit www.profisee.com or follow the company on Twitter @Profisee.

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Analytics Insight is an influential platform dedicated to insights, trends and opinions from the world of data-driven technologies. It monitors the developments, recognition and achievements of artificial intelligence, big data and analytics companies around the world.

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