Financial and operational planning activities traditionally depend upon information that comes from within the company. Strategic plans, budgets and forecasts utilize a variety of data. This includes data from sales, workforce and facilities expenses, other general ledger (GL) data, and customer, product and supplier information.
What’s often missed, however, is external data. Some types of external data are considered static (e.g. global drivers), while some (e.g. competitor information) are altogether missed when plans are created. But external factors can play a big role in the success and accuracy of any plan. Because relevant and time-sensitive data is readily available or being continuously generated outside the walls of the organization, ignoring such data can lead to major strategic gaps in planning and performance analysis.
Consider the following examples of financial and operational planning processes where external data has significant impact, but may be insufficiently considered:
- Traditional three-year or five-year strategic planning activities make assumptions about external factors such as prices of commodities (sugar, electricity, gasoline) and currency exchange rates. These assumptions are not updated frequently. Yet updated commodity prices are available quarterly from the World Bank and exchange rate forecasts are readily available. Basing assumptions on outdated commodity pricing or incorrect exchange rates leads to inaccurate plans and is completely avoidable.
- If a sudden drop in competitor prices forces a company to slash its own product prices, this can have a significant impact on achieving a sales forecast or evaluating current results against historical sales performance. In most plans and forecasts, however, competitor pricing is a static input.
- Promotion planning can benefit greatly from mining social media(Twitter, Yelp, Facebook, etc.) for product or brand references, which can be used to identify new promotional opportunities or inform a plan for future campaigns. However, few companies can easily tie back social media insights into their promotion planning process.
There are several reasons, which contribute to creating the current “norm,” where external data is mainly used as static inputs or not at all. Legacy analytics and performance management solutions traditionally made it difficult for business users to easily access and use external data. Maintaining consistent, accurate and clean internal data has itself been a difficult task! Also, a lot of external data is unstructured, and correlating structured and unstructured data has until recently been a difficult technology challenge. All these factors can corrupt the quality and accuracy of financial and operational plans.
With new technologies enabling easier access to real-time data, and a pressing business environment that requires constant awareness of external factors, enterprises now need to reimagine their planning solutions. Cloud-first planning and analytic solutions are a perfect way to address this challenge:
- They have the elasticity to scale to large volumes of internal and external data.
- If they are built with Big Data in mind, they can leverage technologies such as Hadoop/HDFS and real-time processing with in-memory data analysis techniques. These techniques can efficiently correlate structured and unstructured data.
- They can take advantage of the analytical context of the planning process. Due to the proliferation of external data, context becomes both more accessible and even more critical, and these solutions are easily able to leverage the most relevant data from within the abundant volumes available.
Enterprises are quickly realizing the importance of making planning and performance analysis a strategic activity. CEOs are demanding both short- and long-term planning horizons, and they expect the kind of flexibility that can only come from continuous planning. By opening the door to contextual external data and solutions that allow enterprises to make easy use of it for planning and analysis, companies can improve the accuracy and quality of plans and forecasts.