Nowadays, everyone is talking about being ‘data-driven’. What lies beneath this idea, is the wish to make the decision-making process easier and more effective. But in general, it means delivering the required data of acceptable quality to the relevant decision makers when and where they need it.

What are the FP&A concerns about being ‘data-driven’?

How far can you go with improving your FP&A practices? This article reveals relationship between three important  factors for any FP&A frameworks:  the quality of data, business planning and analytcal tools and techniques. 

Business users want the power of analytics – but analytics can only be as good as the data being analysed. A survey by TDWI has revealed best practices to improve data preparation, finding 76% of businesses hope to increase data-driven decision making and 37% are currently unequipped to do so. 

To create value from data, you do need a big data strategy – right? Well, actually, probably not.  According to Gartner, the ‘all-encompassing data strategy’ fails around 60% of the time.  In fact, Gartner have even stopped publishing a Big Data ‘Hype Cycle’ (their measure of maturity and adoption of technologies).

The Financial Planning & Analysis (FP&A) function has become more prominent in the decision making process in most large organizations because of the emergence of BIG DATA (large volumes of unstructured and structured data). Today, most companies have access to vast amounts of data (financial and operational) and must figure out how to use it to drive growth and profitability.

It’s the middle of the year and it’s time to take charge of your “data destiny” before the budgeting and planning season starts. What exactly is your data destiny? No, it’s not the new Netrunner card game where the objective is to control all the data in the Universe.