Financial analysis dates back centuries, at least to the codification of double-entry bookkeeping in the 15th century. The analysis of balance sheets and income statements has long served as the basis of credit and lending decisions. The discipline of management accounting developed in the early 20th century as a way of using accounting data to keep corporate executives and managers informed about what happened or is happening and why.
The scope of data finance departments have to work with has expanded considerably over the past two decades. Moreover, the discipline of management accounting has changed considerably to reflect business practices and the significantly broader availability of business data. Much of that change involves automating previously manual processes with the positive results of reducing repetition and error, saving time and improving productivity.
Among these technology advances are ones that provide greater analytic power to the office of finance. Open standards have made data far more accessible. In addition, increased processing power and the continued push to make sophisticated applications easier to use have enabled more managers to harness the power of analytic software. Predictive analytics borrow a variety of techniques from statistics, game theory and data mining to improve forecasts of future business outcomes, and these capabilities can be used with a richer set of operating and financial data to improve the quality, accuracy and timeliness of information to support business activities. The upshot is that technology has given finance the opportunity to play a more central, strategic role in its organization than ever before.
The timing of these advances is fortuitous. Given the pace of business today, finance departments cannot stand still. If the organization is to maintain its competitive standing, they must take advantage of the widening range of data -- especially more operating data -- to provide deeper analysis of company results. The use of analytics also will be important in the emerging recovery since companies will be challenged to maintain or improve their position in more competitive and volatile environments.
Corporations will need to pay increased attention to managing profitability. Analytics should be at the center of this effort. Having a clearer picture of the profitability of products and customers is critical to crafting strategies and establishing objectives; it's also essential for measuring results and providing the incentives necessary to ensure these objectives are met consistently. Today, operating units likely have only a vague idea of the impact their strategies will have on the bottom line, and much of the top-down financial analysis done in this area does not incorporate enough data from those operating units. That situation can change if finance steps up to lead the efforts.
Ventana Research recently conducted benchmark research to determine attitudes toward analytics and metrics in the office of finance and their rate of utilization. Many organizations participating in the research rely on traditional budget-related metrics and conventional types of analytics; the most important analyses their finance professionals perform involve income statements, financial planning, cashflow planning and product profitability.
Not many use innovative tools such as predictive analytics and fraud detection, nor do they analyze customer profitability. Yet they are not complacent: More than half of organizations said it is very important to their business goals to simplify making analytics and metrics available to people who need them.
Furthermore, the vast majority of organizations -- almost nine out of 10 -- said they can improve the way their company uses analytics and those in senior roles most often said that use can be improved significantly. Roughly half of all organizations said they are satisfied with the processes used to create analytics, and the other half are not satisfied with them.
The research found that quality of data derived through analytics is not an area where many see a strong need for improvement; more than two-thirds said they are confident or very confident in the quality of the information generated by their analytics. Nor is availability of data a major issue: Organizations generally do not find it difficult to get to the data they need to assemble metrics and performance indicators. However, the research also found fewer than half of senior finance executives and just one-third of other senior executives always have analytics available when they need them.
Yet even if data is largely available and accurate, it is not necessarily fresh and timely, and the research found this to be an area of more concern. More than half of organizations have stale or outdated data in the metrics and key performance indicators (KPIs) they use, and half also require longer than one business week to provide important metrics and KPIs to people who need them. Lacking the latest metrics and KPIs, people at all levels find it difficult to take advantage of opportunities, address issues or correct mistakes.
The analytics process itself is another area where improvement is needed: 40 percent spend most of their time here in unproductive activities including waiting for data, reviewing it for quality and consistency and grappling with metrics that are not easily accessible. Analysis of the research using our Ventana Research Maturity Index determined that most organizations are immature in process, one of the four categories in which we assess maturity. Taking an extended length of time to provide important metrics and KPIs is an indicator of immaturity in the relevant processes as is infrequency of formally reviewing them: 28 percent do this only quarterly, annually or not at all.
This analysis found organizations are most mature in the technology category and least mature in process and information. Yet in every category, most organizations do not get the fullest benefit from finance analytics; in none of them do as many as one in five reach the top innovative maturity level. And even in technology, more than half rank at the two lowest of four levels of maturity. Spreadsheets are the tool most commonly used by more than one-fourth of participating organizations. We consider spreadsheets inadequate for complex analytics because spreadsheets are designed for individual, ad-hoc analyses and are poorly suited to other enterprise-wide tasks. To get maximum benefit from applying analytics to finance, we advise organizations that use spreadsheets for repetitive analyses and reports or to collaborate in ongoing analysis and decision-making processes to replace them with analytic databases and warehouses as well as software for planning and forecasting and business intelligence.
To reach the innovative level of maturity, organizations should add tools for performing predictive analytics as well. They also should determine what analytic capabilities are most important for their business, ensure data used for metrics is timely and people who use analytics have what they need and modify the process of using analytics to facilitate productive effort.
The research shows the three most significant barriers to making changes are a lack of resources and budget for the change, a business case that is not strong enough and low priority given to the issue. These factors indicate that most in finance do not see a driving motivation to reach the highest level of excellence in this area. But as the economic recovery gathers momentum, we expect more finance organizations to consider enhancing their finance analytics processes and capabilities in order to compete more effectively.
To read Ventana Research's benchmark research on financial analytics, click here (http://www.ventanaresearch.com/fam/). Parts two and three of this story explore recommendations on how to achieve more relevant analytics and metrics.
