Why Businesses Fail to Capitalize on Their Data
The promise of data is clear. The companies that have already adopted a data-centric mindset are using their data professionals and analytics tools to gain deeper insights into their markets, products and customers. They are also transforming their cultures, turning business questions into data-informed decisions, rather than acting on hunches.
Yet, businesses are struggling to make the leap from raw data to insights to tactical business decisions that create value.
The Untapped Potential of Data
According to McKinsey, only a fraction of the potential value from data and analytics envisioned in 2011 has been reached today:
In their examination of why companies are missing out on a huge portion of their data’s potential value, McKinsey uncovered a few common barriers:
- Lack of Analytical Skills: As businesses focus on making more data-driven decisions, they are increasingly looking to data pros to guide the way. But the demand for data analysts and data scientists is exceeding the supply. Retail and public sector organizations are particularly feeling the impact of this skill set shortage.
- Siloed Data: You can’t make data-driven decisions without access to data. But legacy IT systems and a lack of centralized data teams, tools and databases means analysts often struggle to even get the data they need to analyze. Aggregating all of a company’s data sources in a single warehouse is extremely valuable, but many companies are struggling to overcome the organizational barriers to doing so.
More Data. More Complexity.
New forms of data from diverse sources are introducing even more complexity into the mix. Businesses all know to mine their traditional data sources (from sales or marketing) for insights, and most realize the questions they need to ask of that data to understand their markets. But the explosion of data you’ve been hearing about — the data that’s doubling every two years — isn’t due to more of this traditional business data being generated.
This new wave of data is being driven by new and diverse sources — people and devices generating sensor data, social data, application usage data and location data:
Real, transformative business value comes from combining these new sources of data with traditional business data and finding answers to new questions. By doing so, the most data-centric businesses — the Amazons and Ubers of the world — are attaining deeper understandings of their customer behaviors and market dynamics, and using those insights to fly past their competition.
New Data Sources Defy Easy Analysis
However, these new sources of data defy easy analysis — they are often unstructured and can’t be dragged, dropped and charted using traditional business intelligence (BI) tools.
These combined datasets are much harder to process — requiring advanced analytics skills and powerful tools. Most businesses understand the traditional correlations in their business data (for example, how marketing might affect sales), and therefore the questions asked of that data are relatively straightforward. But things get more complicated when you throw these new data sources into the mix. For example, if your dataset includes sales, marketing, social media and sensor data, it’s not immediately clear what questions you need to ask to see relationships or uncover recommended actions.
That is where your data team comes in. In order to get the most value out of all of that diverse data, you need a team of professionals who can help bring powerful analysis to your most critical decisions.
In the age of data-driven decisions, your decisions are only as good as your data team. Learn more about the steps your business can take to grow and empower your data team, and the benefits you will realize as result in our new guide, Building & Empowering Your Data Team.
Sources for infographics: