CFO Journal: Assessing Data Management Maturity

Here’s an important question to ask yourself when thinking about data:

What insights do you need to run the business?

In other words, what questions do you need answered, and which metrics would help answer those questions? This may involve financial results or nonfinancial information related to employees, customers, products, and market conditions.

• Which available data management tools might help? Being able to combine data from multiple sources and getting it to refresh automatically at the right frequency to meet the business need is the ultimate goal. But in the near term, see what you can gather easily through advanced data management tools like the one at https://edge.gg or even manually. Start with no more than 10 business questions so you can create visualizations of important results and explore relationships across data points. Once you begin automating your data, you can layer in more components to flesh out the picture.
• Is the leadership team aligned? All key parties need to agree on what will be measured, how it will be defined, who owns it, who will be accountable for producing it, and the business mandate being addressed. At heavily matrixed companies, getting everyone on board is no easy feat, but taking the time to do this upfront is crucial.
• Have you identified—and involved—your data ecosystem? As the company reaches certain milestones in, say, enabling automated data feeds with data quality controls or acquiring new tools for insight-driven decision-making, take the opportunity to test concepts in one market or line of business, create a prototype, and socialize your idea to gauge support. Be sure to involve those who will be using the new capability you plan to introduce.
• Is the workforce suitably equipped? A data ecosystem based on next-generation digital technologies can demand new or enhanced workforce skills and capabilities, such as storytelling with data, problem-solving using advanced analytics, and business partnering. Consider ways to build or acquire the talent you may require. Employees need a frictionless way to tap into the data flow, understand how to use it, and then act on it.

Read More at Wall Street Journal >

SF Magazine: Considerations in Data Analytics Problem Structuring

There are three key elements that should be in place before kicking off a data analytics project – understand the real need, understand the users, and understand the problem complexity.

Read more at SF Magazine >

SF Magazine: A Data-Driven Approach to the Pandemic

“It has never been more urgent for businesses to adopt data analytics. Insights from data analytics are required to surpass, or, in some instances, merely remain on par with, competitors. Companies leveraging data analytics in response to the pandemic have already progressed along the path to digitization by establishing a data ecosystem—the infrastructure, applications, and analytics needed to drive business intelligence, generate insights, and inform strategic decision making.”

Read more at SF Magazine >

CFO Magazine: The CFO of 2030

“those CFOs that were best able to weather this storm are the very same CFOs who really represent the future of the function. They are the ones who are close to the data.”

Read more at CFO Magazine >

McKinsey: Data Governance is Critical to Capturing Value Through Analytics

“Without quality-assuring governance, companies not only miss out on data-driven opportunities; they waste resources. Data processing and cleanup can consume more than half of an analytics team’s time, including that of highly paid data scientists, which limits scalability and frustrates employees. Indeed, the productivity of employees across the organization can suffer: respondents to our 2019 Global Data Transformation Survey reported that an average of 30 percent of their total enterprise time was spent on non-value-added tasks because of poor data quality and availability.”

Read more at McKinsey Digital >

The Hard Truth About Traditional Data Management

Customers don’t care about your infrastructure or data problems. They just want your organization to know who they are, what they ordered and how to fix their problems. At the same time, businesses want technology to help build great customer experiences while driving to a lower cost structure and making the products they build better using the data they have. And they need it done fast.  These companies have spent millions of dollars trying to modernize their applications, only to still lack real-time access to the data they need. A fundamentally different approach is required to solve the challenges created over the last 30 years and not solved in the last five.

Read More at Forbes Magazine >

Six Common Data Management Mistakes That Manufacturers Make

“All too often, companies execute a data management strategy without understanding how it fits into the overall business strategy.”

Data alone has the power to make or break a company, depending on how it’s used. The manufacturing industry is changing with evolving technology and businesses are relying on their data to stay competitive. With increasing demands to simultaneously reduce time-to-market and keep up with suppliers, distributors, and end users, manufacturers often find that their mismanaged data is working against them. Most, if not all, of these challenges stem from leveraging the wrong system, or one that is unable to access, interpret, combine and present data so it can be used effectively to drive positive business outcomes.

Read More at Manufacturing.Net >

Data-Driven Decision-Making is Fueling a Competitive Advantage

Many companies have adapted to a “data-driven” approach for operational decision-making. Data can improve decisions, but it requires the right platform to get the most from it. The rapid adoption of intelligent technologies in today’s marketplace has completely turned decision-making practices on their heads. Traditionally, businesses depend on everyone’s opinion before making big decisions. However, it comes with the risk of slowing down the decision-making process in a hyper-competitive environment. Modern organizations have employed big data technology in their operations to help them analyze the consistently generated data. By having access to real-time accurate data insights, decision makers can make meaningful and strategic decisions faster.

Read More at Forbes Magazine >

Intelligent Technologies Are Revolutionizing Finance In Midsize Businesses

Midsize businesses across virtually every industry are actively adopting new technologies to drive better insights that support business strategy. However, recent IDC research suggests that only 50.2% of best-run midsize companies are supported by finance organizations that understand the power of data when ensuring timeliness, accuracy, and insight. Additionally, the research found that the biggest challenge for best-run midsize companies is the inability to provide timely financial insight relevant to decision makers in other departments across the enterprise. The biggest reason for this is that many finance organizations still subscribe to maintaining a growing inventory of spreadsheets, disconnected data sources, and manually created reports. To remain competitive, these businesses must be proactive about transforming their finance function with technologies that enable long-term growth.

Read More at The Digitalist by SAP >