Today, we live in a world where the magnitude of change is unprecedented. Escalating costs, evolving technologies, complex regulations and unpredictable markets are impacting businesses around the world and creating new challenges in meeting shareholder and client expectations. These mega-changes necessitate the need for businesses to make smarter decisions in order to operate efficiently. One important way of enabling smart decision-making is leveraging analytics.
There are, however, some misconceptions of analytics in the marketplace. Many people equate «business analytics» with basic number crunching in Excel spreadsheets. Others equate it to business intelligence tools, reporting or MIS and advanced predictive analysis. And there are some who associate analytics with business processes such as financial planning and accounting or emerging trends such as social media analytics.
In fact, analytics is all of the above and much more. Not just a business function, analytics is a process that bridges the data-information-insight-decision gaps in an organization. It not only encompasses obtaining information, but also finding the means to manage and make sense out of that information.
Big data analytics, in particular, helps organizations leverage all available data, including previously unused data, to understand customers, partners, markets and businesses, and to significantly impact performance. With big data analytics, a consumer packaged goods manufacturer can use advanced visualization techniques on geospatial data overlaid with demographic data to help determine market entry strategies and distribution strategies. The same manufacturer can also optimize trade spends by running predictive models using data on trade programs, promotions and sales. And a financial services organization can reduce risk exposure by identifying risky customers and fraudulent transactions. Organizations that successfully embed analytic insights into business decisions create a competitive advantage, one that CFOs cannot afford to ignore.
What is Big Data?
Data is everywhere — in financial databases containing price, revenue and cost figures; in operational databases containing effort and activity data; and in HR systems containing resource cost and availability. Recently, however, there has been an upsurge in the volume of data that companies produce. Part of this upsurge is due to technology’s increasing ability to read text, audio, image and video as «data.»
In an article by David Rosenbaum, the author cites sensing devices (such as radio frequency identification), wireless networks, social networks, point-of-sale systems and online transaction systems as potential sources of big data. And with 4.6 billion mobile phone subscriptions worldwide and between 1 billion and 2 billion people accessing the Internet, there are more people interacting with data or information than ever before. Every day, 2.5 quintillion bytes of data is created, and 90% of this data was created within the past two years.
According to a recent Gartner report, «enterprise data . . . is expected to grow by 650% in the next five years.» A recent IDC study found that the world’s data is doubling every two years, and that businesses will «manage 50 times more data, and files will grow 75 times more in the next decade.» The sources might vary but the numbers are staggering.
What You Need to Know about Analytics and Big Data
Big data and analytics don’t have to mean big spending. Over the years, millions of dollars’ worth of investment in data warehouse and business intelligence tools have failed to deliver as promised.
As a result, there is a growing demand among businesses for initiating smaller pilots in a test-and-learn environment. And open source tools such as Talend for MDM and Pentaho for BI can offer a less expensive route to build quick pilots.
In addition, a functional assessment by experts and business units is critical to making smarter procurement decisions. Smart procurement ensures that the business buys the right technology, one that is in line with the CIO’s technology roadmap.
Smart partnerships are key. CFOs need to work with partners specializing in advanced analytics capabilities to handle crests and troughs in internal demand.
Analytics must improve ROI on all spend, especially in major areas such as sales and marketing. The sales force is a major expense item for most companies, especially in pharmaceutical and B2B organizations. Analytics can help to streamline the sales process by providing the right metrics at the right time to optimize cost.
In addition, analytics can have a positive influence on a company’s marketing function. The impact of marketing spend on price, sales and P&L is generally misunderstood by a company’s CFO, CEO and investors. Advanced analytics techniques can be used to determine the effectiveness (the impact on marketing and sales metrics) and efficiency (ROI) of various marketing elements, including media, trade promotions and consumer promotions. Analytics can also provide insight into environmental factors such as competitor activity, price changes and category factors.
Analytics can be used to better assess risk. There is plenty of risk in the world today. Analytics can be used to assess, benchmark and identify gaps across various forms of risk — business, financial and operational — to increase stakeholder value. The right analytics control tools and governance models can address higher perceived risk due to lower direct control. For example, with analytics, CFOs can assess the impact of supplier risk on their P&L and measure that risk in terms of financial troubles, availability and labor unrest.
While CFOs are no stranger to analytics, in the past it has been the marketing, technology and risk functions driven by CEOs, CIOs and CMOs that have embraced analytics. Today, the traditional finance function is evolving from its reactive role of collecting, validating and reporting on data to proactively employing predictive analytics to aid decision-making. As a result of this, CFOs have both major opportunities and certain challenges in front of them.
Potential opportunities for the CFO can be found in mitigating risk, cutting costs, improving margins and revenues, improving market share, enhancing satisfaction, reducing customer churn and improving operational efficiencies. Challenges for the CFO lie in finding the right people with the right skill sets, and finding the proper technologies that can provide data quality and harmonization as well as deliver desired insights.
Making Big Data Analytics an Intrinsic Part of the Organization
There are various organizational models that can work to embed analytics in an organization. Of equal importance, however, is creating an enabling culture that will be receptive to big data analytics. Companies that are ideal for big data analytics allow different analytics resources to focus on core production activities such as developing strategies and fostering operational excellence.
In addition, collaboration is key to making big data analytics an intrinsic part of the organization. A collaborative environment that proactively fosters innovation is better equipped to create an overall analytics visual. And by promoting cooperation with other functional leaders, companies can leverage their investments and resources through the regular governance structure. Most importantly, successful companies that foster a collaborative culture can drive rigorous cross-functional governance to ensure analytics activities lead to actual «end» business impact — critical for success.
This blog originally appeared at BusinessFinancemag.com
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