Executive Consultant Kevin Modany Details the Benefits and Challenges of Data-Driven Decision-Making

In today’s rapidly evolving business landscape, company leaders make dozens ─ or even hundreds ─ of decisions every day. In any industry, a business’ executives and managers choose the path forward on operations, sales and marketing, technology, and other issues daily. These decision-makers use all the tools at their disposal, considering the available information while taking the company’s mission and goals into account.

Traditional and 21^st-Century Decision-Making Approaches

Historically, company decision-makers used paper-sourced data and (later on) spreadsheets and computer-generated reports. Legacy computer systems processed data in batches, with delayed information that didn’t provide timely (and accurate) results. Huge amounts of data further slowed down the processing and analysis operation. Together, these factors forced company leaders to make decisions based on less-than-optimal information.

In the 21^st century, technological advancements enable leaders to obtain real-time data to better inform decision-making processes. Automation, artificial intelligence (or AI), and machine learning (or ML) analyze often-expansive datasets with blinding speed.

With the targeted results in hand, executive consultant Kevin Modany emphasizes that leaders can confidently make data-driven decisions that often provide a competitive edge. A former Chief Executive Officer (or CEO), he currently serves in this position for a private equity firm’s portfolio client.

5 Data Types Ideal for Analysis and Interpretation

Mastering an emerging technology begins with an understanding of its key components. Here, executive consultant Kevin Modany highlights five data types that lend themselves to sophisticated analysis and interpretation.

Market Data

Every company should remain aware of its industry developments and overall market trends. Obtaining knowledge of competitors’ activities is also key. Updated industry reports, respected market research, and ongoing competitor analyses can provide the relevant data.

Operational Data

A company’s operational data pertains to the firm’s day-to-day functions. Leaders would likely track inventory levels, sales numbers, and employee performance outcomes, among other metrics. Over time, the business will monitor changing trends and market indicators.

Performance Data

Meeting strategic company objectives is important for growth. Performance metrics and Key Performance Indicators (or KPIs) can indicate whether the business is meeting its targets. Scorecards, dashboards, and reviews will likely yield useful information.

Financial Data

In any industry, a company should track its revenues, expenses, and overall profit margins. This real-time data shows the business’ profitability and financial stability, which influence its return on investment.

Customer Data

Organizations that market products or services should closely track customers’ preferences, buying behaviors, and personal feedback. Each customer’s purchase history, targeted surveys, and social media engagements are good data sources.

4 Data-Driven Decision-Making Benefits

Companies in every industry can reap the data-driven decision-making benefits. Here, executive consultant Kevin Modany highlights four benefits of this increasingly utilized methodology.

Enhanced Accuracy via Fact-Based Decisions

Leaders who integrate a real-time, data-driven decision-making approach will obtain more accurate data than those who rely on suboptimal data analysis methods. Real-time data also enables analyses to pinpoint relevant patterns and trends. Finally, data-driven decision-making takes personal biases out of the equation.

Expeditious, Efficiency-Based Outcomes

In the 21^st century, industries such as finance, healthcare, and technology operate at a lightning-fast pace. In these (and other) fields, data-driven decision-making enables a firm to quickly determine customer inclinations and buying behaviors. Equipped with this data, the firm can create targeted marketing strategies that promote customer loyalty. The company can also seize key opportunities and maintain a valuable competitive edge.

Improved Resource and Investment Allocations

A well-managed organization seeks to maximize its returns on resource and financial investments. Data-driven decision-making enables company leaders to allocate the firm’s resources based on their likely impact. Concurrently, these insights enable increasingly accurate forecasts, providing the data needed to minimize potential risks.

Increased Innovation and Competitive Edge

Data-driven decision-making enables companies to use sophisticated analytics tools that pinpoint patterns and identify emerging trends. This can spur innovation and increase employees’ productivity. Firms can use this momentum to build a competitive edge, even in a crowded industry.

Kevin Modany’s Data-Driven Decisions Insights

Executive consultant Kevin Modany has long recognized that a data-driven decision-making approach makes the most sense. His solid data analytics skills enable him to identify, and develop a plan to resolve, clients’ issues of concern.

Like any complex challenge, correctly identifying the problem is the first step to developing a targeted solution. Here, Kevin Modany says obtaining the correct dataset enables accurate analyses. “There’s a plethora of data. People are collecting more and more of it. I think it requires that we prioritize and we make sure that we’re focused on the right set of data, and we don’t get overwhelmed by it. But I think it’s super exciting,” Kevin Modany remarked.

That said, Kevin Modany believes qualitative factors should also play a significant role in most business decisions. “[The data is] not the end all be all, right? There are still qualitative considerations, and you always have to have that as part of the equation,’ he concluded.

4 Data-Driven Decision-Making Challenges

As with any new technology, leaders must overcome specific challenges in transitioning to a data-driven decision-making methodology. Executive consultant Kevin Modany details four challenges and offers a feasible solution for each issue.

Resistance to the New Methodology

As a newer methodology, data-driven decision-making may face resistance from legacy firm leaders who prefer maintaining the status quo. Some executives and/or managers may fear that the new methodology may erode their influence and control. To allay their concerns, executive consultant Kevin Modany recommends that the firm’s CEO and senior leaders thoroughly explain the new approach and its benefits.

Substandard Data Quality and Accuracy

In any industry, leaders should make investments that will ensure optimal data quality. Accurate, well-constructed, and consistent data positions a firm to make well-informed decisions. If a firm’s data doesn’t meet these criteria, executive consultant Kevin Modany says a skilled data analytics consultant can help resolve the issues.

Questionable Data Security and Privacy

Company leaders may be concerned with the protection of sensitive data and compliance with data privacy regulations. Executive consultant Kevin Modany states that the firm’s information technology manager should lead a team focused on ensuring these protections and developing compliance protocols.

Data Analysis and Interpretation Knowledge Gaps

Certain companies may lack internal data analysis and interpretation experts. Upskilling current employees will likely be less expensive. However, executive consultant Kevin Modany notes that the business may choose to hire externally for these positions.

Company-Wide Technology Access is Key

A company-wide data-driven decision-making methodology enables leaders at all levels to capitalize on the approach’s advantages. Executive consultant Kevin Modany acknowledges that data-driven decision-making will incur upfront technology investments. However, he emphasizes that the methodology’s long-term advantages will help improve the business’ marketplace position.