The Trailblazers of Improved Analytics
“Our data shows that there’s still a big gap between the expected impact of digital transformation and finance’s level of readiness. But top-performing finance organizations are not waiting around until all the statistics look good; they are pushing ahead with exploration and testing of new tools.” While most organizations have a digital strategy, finance lags in the ability to execute it. Still, top performers are blazing a trail for peers to follow and realize the effectiveness and efficiency promise of digital transformation.
Do You Know the Full Potential of Your Analytics?
Data analytics are shaking up multiple industries. McKinsey recently surveyed and found that almost 90% of executives reported that their organizations were only somewhat effective at meeting the goals they set out for their data and analytics initiatives. In many cases, the culprit is a gap between launching a few analytics experiments and embedding these insights into the operating model of the larger organization. Many companies invested in analytics systems without fully appreciating that turning data into real value requires a profound reshaping of their day-to-day workflow. Others are still lagging behind in terms of fully digitizing transactions and processes to generate and collect all the data that could be useful.
Key Challenges for Monetizing Your Data
Have you been focused on analyzing the data rather than extracting intelligence from it and taking quick action on that information? If the answer is yes, you haven’t been leveraging your data to its full potential. It’s possible to transform your big data into an amazingly accurate predictor using process-centric and process-embedded AI and machine learning. In order to do so, you have to overcome the three biggest challenges in the quest to monetize big data: complexity, consumerization and continuity.
Create Stronger Strategies, Not Goals
A strategy involves a clear set of choices that define what the firm is going to do and what it’s not going to do. Many strategies fail to get implemented, despite the ample efforts of hard-working people, because they do not represent a set of clear choices. These so-called “strategies” are in fact goals. They don’t tell you what you are going to do; all they do is tell you what you hope the outcome will be. But you’ll still need a strategy to achieve it. This is important to note because companies often get the two confused, and they are left with an unsuccessful “strategy”. Without a clear strategic direction, any implementation process is doomed to fail.
Predictive Analytics in Marketing
“Converting analysis into behavior-changing programs if often challenging for marketers. While descriptive analysis investigates what has happened in the past (i.e., what is the demographic profile of individuals who buy shampoo), predictive analytics uses existing data and trends to predict what might happen in the future (i.e., integrating different data to predict the market share a company might achieve as they enter a new geography).”