Success is Utilizing the Right Data – Not Just Owning It

“No matter how much data is fed to machine learning and predictive analytics tools, the key is deciding which outputs are useful and how to act on them.”

When it comes to implementing new technologies, many businesses go through what Gartner calls a “hype cycle”- where the initial implementation is a period of inflated expectations that  becomes a “slope of enlightenment” once people begin to find practical uses for the technology, and finally develops into an extended “plateau of productivity”, where the actual value of the tool is realized. Today, technology itself will not provide a competitive advantage. How a business leverages their tools to gain meaningful business insight and what they do with that knowledge will define their success. With the rise of digital transformation and innovation, beating out competitors will come down to visibility, judgement, knowledge, strategy and approach.

Read More at CFO Magazine >

Better Business Decisions Come From Effective Data Visualization

Data visualization can greatly improve finance’s ability to view how the business is performing by providing access to key metrics, KPIs, forecasts, and other critical information that can aid decision-making and help each function chart effective courses of action. However, those goals depend heavily on quality data. Thanks to an expanding array of analytics tools and emerging cognitive technologies, finance is also able to leverage that data to attain meaningful insights that can influence a range of tactical and strategic decisions.

Read More at CFO Insights by Deloitte >

Growing Businesses Are Leveraging Data & Analytics For Long-Term Success

“Mid-size financial services providers are working continuously to improve their risk models because the more accurate their assessment of risk, the better their chances of profitability. Mid-size manufacturers worldwide are increasingly looking into the causes of quality fluctuations by combining “what if?” analysis with sensitivity analysis and predictive models.”

Data and analytics deliver major benefits to mid-size businesses and are becoming critical for differentiation and even long-term survival. Finance leaders should embrace four major data and analytics trends as they strive to develop data-driven organizations that deliver new business value.

Read More at Smarter with Gartner >

How Insights Drive Data-Driven Accounting

Businesses use data to understand how the business is performing, to manage operations, and to make key business decisions. With the accelerating pace of business today, accurate, up-to-date data is more essential than ever. Finance leaders need operational and performance data to know how their department is performing, to efficiently manage their operations, and to enable data-driven decision-making. It is imperative for companies to start modernizing their accounting functions in order to remain competitive. This starts by eliminated manual processes and digitizing operations. Once this is done, accounting and finance executives need access to performance data to improve their processes.

Read More at The Digitalist by SAP >

Connecting the Dots Between Manufacturing Data and Insight

Today’s manufacturers have more quality data at their fingertips than ever before. Companies are now leveraging tools to collect extensive amounts of data about their production processes—across multiple lines and sites, around the clock. Real-time data quality is key to plant-floor operators because it enables them to spot manufacturing issues and inconsistencies before they magnify, make timely corrections, and determine where to focus process improvement efforts at the plant and enterprise levels. To effectively sift through the amount of data coming from the modern plant floor and find real, valuable quality intelligence, there are essential pillars that manufacturers first need to have in place: standardization, centralized data, and prioritization.

Read More at Manufacturing.Net >

Why an Outcome-Driven Enterprise Data Strategy is Critical for Decision Making

A business cannot be successful without the processes to manage data and gain insightful analytics from it. Some processes can be automated via business rules, while others still require manual input. Whatever the approach, it’s important that data management processes are as simple, automated, and designed according to standards specific to the organization. Data life-cycle processes are critical to decision makers because they are a key component of any outcome-driven business strategy. The volume of data and enterprise landscape complexity are growing, and poor data processes often lead to poor data quality and unfounded decision making. Business can create a successful outcome-driven enterprise data strategy that is unmatched by combining a data life-cycle process with the right tools and technologies that provides actionable and real-time business insight.

A well-implemented data management system enables businesses to gain insights into customer behavior, market trends, and operational efficiency. It helps businesses make informed decisions based on reliable and accurate data, leading to better performance, reduced risk, and increased profitability.

To achieve efficient data management, businesses must first define their data requirements and establish data governance policies that ensure data is consistent, secure, and accessible to authorized users. This includes selecting appropriate data management tools and technologies, such as data warehouses, Name Matching, data lakes, and data analytics software, that align with their specific needs and goals.

By prioritizing data management, businesses and companies can leverage the power of data to drive innovation, streamline operations, and stay competitive in today’s fast-paced and data-driven marketplace.

Modern Technologies Are Critical for The Success of Midsize Businesses

Businesses that are not making digital transformation a priority have a much greater risk of going out of business in the next decade than those that are. Why? Successful digital transformation allows businesses to operate with a level of agility necessary to adapt to a marketplace that is increasingly volatile, uncertain, complex, and ambiguous. The rising intelligence of enterprise technologies presents tremendous opportunities for midsize businesses to outpace the rest of their competition. However, their growth depends on the strength of a unified modern data platform, which is critical for turning data into insight. Finance and IT leaders must create a strong foundation of connected, real-time data that is integrated enterprise-wide and provides the necessary visibility for decision makers to ultimately maximize profit growth.

Read More at The Digitalist by SAP >

IT and Finance Collaboration is the Key to Unlocking Powerful Business Analytics

Business leaders aim to make decisions faster and more accurately through automation and predictive modeling. Tools, technological innovation, and increasingly powerful business insights are readily available everywhere. However, a business only gets out of their technologies what the tool is actually capable of giving them. Decision makers must choose a platform that best fits their business specifically, and often times it is not a “one-stop-shop” solution. Moreover, it takes collaboration between finance and IT because there is no substitute for finance’s knowledge and experience to ensure that an accounting system meets their organization’s needs. As financial eyes and ears of their business, finance professionals can provide critical insight into business processes and requirements that can help decision makers get a true picture of the organization

Read More at Strategic Finance Magazine >

Data Mismanagement: How Good Data Can Lead to Bad Decisions

Master data is the foundation upon which businesses make important decisions. Since requirements for business data, reporting, and documentation have increased in the past few years, incorrectly recorded master data, lack of master data maintenance, and the storage of master data across too many systems create enormous challenges. In addition to this, more and more companies are beginning to use data analytics to process data better, real-time insights faster, and understand trends and future opportunities. If a large portion of the data is incorrect, data analytics are misleading, and people on the production floor and in the boardroom are working with the wrong numbers.

Read More at The Digitalist by SAP >