5 benefits to implementing an effective data strategy

Improve operations, compliance and risk management with data analytics

Feb 28, 2019
Business risk consulting Digital evolution Data analytics

Middle market companies collect increasingly large volumes of data, from customer and vendor information to sales, inventory and production data. However, many organizations do not understand how to fully leverage this asset and utilize data to truly enhance multiple facets of the business. Implementing a comprehensive data strategy can optimize processes across your organization, including:

  • Enhancing business decision-making
  • Mitigating risk
  • Identifying and addressing fraud
  • Strengthening transactional due diligence
  • Accurately determining tax exposure

In addition, as companies grow they become more complex—through acquisition, innovation, or both—and require integration of systems and business insights to manage new demands. The business insights needed in growth mode are different and more intricate, and require more and different data sets. Due to a lack of an effective data strategy, companies often rely on more people and resources to gain the information required to manage the business. 

However, a change in strategy with a data-driven analytics foundation and an effective reporting, analytics and information delivery framework can create a single source of truth for your organization. Instead of making decisions based on stale data, you can get the insights you need in a more efficient manner. With the increase in data sources and urgency, companies cannot always rely on internal IT resources to generate reports; instead, harnessing the power of real-time and self-service data analytics can get actionable results to stakeholders quicker and without the need for additional internal resources.

Implementing a comprehensive data analytics strategy can optimize processes in several key business areas, with specific benefits including:

1. Helping your business make more agile, informed decisions

Implementing a data warehouse strategy can enable organizations to better organize data, gain more insight and make better business decisions. For instance, many organizations outgrow out-of-the-box data analytics and reporting capabilities within their existing enterprise resource planning (ERP) or business intelligence (BI) solutions. Therefore, many companies are unable to get the real-time metrics they need from their key business activities.

For example, we recently helped a company develop a new data analytics strategy, utilizing a data warehouse, integrating new key performance indicators (KPIs) and drawing in additional data from several new sources. While its previous framework could only show what results happened, the new analytic tools and depth of information available helped extensively explain variances in reporting. In addition, the company reduced waste on ad hoc manual reporting with data that was often out-of-date by the time they saw it.  

2. Understanding and addressing business risks

Increasing the use of data analysis can enhance many risk management functions, helping to understand the risks an organization is facing, the impact and likelihood of those risks and how to create an effective mitigation plan. Timely identification of risks by all three lines of defense (management, compliance and internal audit) is critical, and data-driven techniques enable a continuous auditing strategy. Operational transactions are continuously tested and monitored, and dashboards and visual analytics provide a higher level of insight into ongoing risks.

Our team recently worked with an organization to leverage data analytics to test key controls in support of Sarbanes-Oxley (SOX) compliance. The company tried to test general controls over financial reporting, standard internal process controls and key general ledger, purchase to pay, and revenue cycle-to-cash controls internally, but struggled to get the right data at the right time.

We helped the company overcome data access issues and developed a data analytics strategy that addressed each of its challenges. Key data access processes were automated independently of IT, and the people and process aspects of how the company conducts audits and SOX compliance efforts were redesigned and streamlined—allowing management to focus on more value-added tasks.   

3. Enabling fraud risk management and detection

Data analytics can be used to assess an organization’s risk of intentional and unintentional fraudulent acts. In addition, data analytics can strengthen forensic accounting processes, helping to determine if and how fraud has occurred. Forensic data analytics is typically reactive in nature, triggered by a whistleblower tip, internal audit or during management reviews. However, leading companies use continuous fraud analytics to reinforce the perception of detection—something the Association of Certified Fraud Examiners identifies as one of the biggest deterrents to fraud.

When companies find themselves faced with fraud investigations, many do not have the qualified or knowledgeable resources to uncover the appropriate data to understand the situation. A comprehensive forensic data analysis, conducted by certified fraud examiners, can create a picture of what happened and the extent of potential damage.

4. Obtaining anticipated value from a transaction

Data analysis can be a critical element of buy side or sell side due diligence projects prior to completing a transaction. From a buyer’s perspective, data can provide a higher level of insight into the potential target. Benchmarking studies are a common value-added data analysis process, comparing performance and operational metrics to other competitors in the sector and indicating potential strengths and weaknesses.

For example, we routinely use enhanced data analytics to perform quality of earnings analyses that accurately reflect the financials of a target company. Analytics can quickly determine whether a company’s books are accurate and what an owner can pass through to increase EBITDA. In addition, evaluating data can target and measure KPIs that demonstrate how to improve the business, as well as enabling sensitivity analyses to identify peculiarities—such as an overreliance on a specific customer—that could result in a discount in purchase price.     

5. Ensuring you pay the appropriate tax amount

To maximize profitability, you must ensure that you are paying the right amount of taxes, and lessening your tax burden if possible. Using data tools and platforms, you can compare your company to an organization with a similar financial profile to ensure you pay an accurate tax rate.

For instance, we work with tools that efficiently allow clients to know their effective tax rate, based on the financial performance of the business. By knowing how you arrived at a specific tax rate, you can understand whether you may be underpaying or potentially overpaying, and how to make adjustments to reduce tax responsibilities.    

Are you ready?

Companies are now getting data in more ways than they ever have before. However, to gain a competitive advantage, your organization must implement strategies to aggregate that data, turn it into a true asset and analyze it in real-time. When leveraged effectively, data can provide an avenue to better understand your customers and operations, discover key trends, and support more effective and informed decision-making.    

RSM contributors