How data REALLY should be used to drive strategy and differentiation

When it comes to strategy, most companies fail. In reality, 95% of products entering the market fail. The common excuse is a failed execution, but this is often just a bad executive responsibility for the company not meeting their quarterly targets. Other common reasons that business leaders indicate are unrealistic plans, the wrong team involved, market conditions, and so on. The blame game can go on, but it only focuses on how strategy failed and not really finished Why†

The strategy itself is never questioned. A strategy should not be just a goal, but rather a set of clear choices that drive company-wide alignment and focus† Fast-growing companies are already wondering how these choices are made when determining their strategies. That’s usually when data comes in, and that’s when companies rush to become data-driven. Most companies recognize the value of data in determining a strategy, but cannot realize their full potential because they cannot create a systemic approach to a data-driven strategy.

Why companies don’t use data to inform strategy

The first mistake companies make when creating a data-driven strategy is how they use their data capabilities, or how the company culture behaves regarding this topic. Organizations that often make this mistake apply data-driven approaches to some processes or decisions, but not all, leaving important decisions outside this circle. They ultimately lead to inefficiencies and misuse of data across the organization, and in many areas of the business, business problems are still being solved through traditional approaches.

Another common reason for this is that data often doesn’t have a real “owner” or strategy for making sure it’s updated and ready to go in various ways. This should not just be a compliance issue, but a core decision that affects the entire strategy.

The second mistake companies make is in the data strategy itself† Most of the value in the current data overload era is in unstructured data, but companies don’t see that or can’t handle it well. Most of the data businesses use is still organized like a large spreadsheet or relational database, requiring a lot of time to manually explore and modify datasets. Another bad use of unstructured data is that companies have to refine data into a structured form using manual, time-consuming and error-prone processes.

To make matters worse, only a small portion of unstructured data is recorded, processed and analyzed in real time due to the limitations of the tools used by many companies. Data sets are silos and expensive, making it difficult for non-technical users within an organization to quickly access and manipulate the data they need. Companies must then make a loss-loss decision about their data strategy, choosing between two essential factors for successful strategy implementation: agile decision-making or more advanced analytics and use cases involving data.

Characteristics of a true data-driven strategy

A successful strategy is preceded by a data-driven culture across the organization. Therefore, data must be embedded in every decision, interaction and process, not just in some cases† That makes any decision-making easy, fast and aligned with the “set of choices” that are at the heart of the strategy’s implementation. In addition, data-driven companies are: 58% more likely to beat sales targets than those who do not use data in the decision-making process. Another key feature of a data-driven strategy is the real-time delivery and processing of data, making it integrated and ready to use for any stakeholder.

The roadmap for a data-driven business strategy starts with choosing the right data. This provides the opportunity to gain more depth and breadth in the business environment, enabling better strategic decisions to be made. It provides the ability to see the past correctly and make better predictions about the competitive landscape, market trends and other variables that influence the results of the business strategy.

Choosing the right data also means being more comprehensive about the business problems and opportunities that need to be addressed. Business leaders also need to be creative about the potential of external and new data sources, especially when it comes to unstructured data.

Once companies have the right data to address business problems, they need to build the right analytics models to optimize business outcomes. That starts with a hypothesis-driven approach to identify a business opportunity and determine how the model can improve performance. This approach also ensures that less data-conscious professionals are committed to the day-to-day use of analytic tools.

Why embrace technology to create a data-driven strategy?

The truth is that strategy decision makers no longer have to rely on experience or outsourced consultants to create data-driven strategies. Multiple technologies can help with this, saving time and money and providing accurate insights. Putting data to work isn’t always easy; the first step is to learn how to deal with data from different sources and how technology can help collect and standardize this data.

The challenge of working with unstructured data at scale to create better strategies can be solved using predictive systems to artificial intelligence (AI)-driven automation used to efficiently organize this data and ensure the best analytical model to maximize business results. machine learning, for example, can be considered one of the most important analytical approaches, which can help find connections and trends in the data that human data analysts may not even know how to look for. It can also enable the focus on forward-looking insights so that current data can be turned into real and actionable insights.

To create and implement a data-driven culture, companies need to embrace innovative technology solutions as a faster and more assertive way to interact with the metadata world. And they need to be able to make decisions based on reliable information, which speeds up the decision-making process.

Patricia Osorio is co-founder and CRO of Birdie†