Turn data-driven decisions into informed decisions

Building an information supply chain

The business world has been championing data-driven decision making for the last few decades. The concept is simple: Get data into the hands of business users so they can make the right decisions at the right time. Producers of data tools, such as data warehouses and business intelligence applications, have promoted the idea that, with the right data, every decision will be effective and lead to positive outcomes. Although there has been some progress in the adoption and successful use of data in decision making, the results are not up to the promise. In this article, we’ll look at what’s missing from the information pipeline and how it can be reworked to empower timely, informed decisions for business leaders everywhere.

Data is not information

When people say they want to make data-driven decisions, what they really mean is they want to make informed decisions - decisions that are based on information, not data. What’s the difference between information and data? Data becomes information when it’s processed, cleaned, aggregated, and given context. As information, data can be effortlessly understood by decision makers and applied to real-world problems.

For example, a set of sales records for various stores in a data warehouse is data. In its raw form, it doesn’t offer much. However, when it’s aggregated and the expenses are subtracted for each store (in other words, when it becomes information), it can be used to determine relative store profitability. Sales transactions are data. Profit values per store are information. Businesses can make informed decisions about which stores to invest in based on the derived information.

It doesn’t stop there. Over time, this kind of information becomes knowledge and wisdom. As business teams find patterns in the information they use, they develop a set of repeatable decisions to help them run their business.

The business world is still focused on data

Historically, analytics tools have focused on the collection and storage of data, accessed and processed by trained individuals. Data Warehouse and Business Intelligence tools represent the lion’s share of modern IT budgets. With powerful data collection and manipulation capabilities, they enable those with the right skills to do almost anything with data.

Therein lies the problem. Not everyone has the knowledge and experience to work with, and effectively interpret, raw data. Most business tools are designed for skilled individuals, such as data experts, analysts and scientists. The result? The industry has created a need for data experts to enable data-driven decisions, rather than building a framework that puts information directly into the hands of decision makers.

It’s a supply chain problem

At its core, the issue is a supply chain problem. Data is a raw resource that’s collected and refined within an organization. Information is the product derived from that resource. Like any other supply chain, value is generated when the raw resource is shaped into a final product that meets the needs of the consumer (in this case, the decision makers).

Optimizing supply chains to meet consumer needs is well understood. It starts with understanding the consumer and their requirements. Successful supply chains don’t focus on making it easy to access raw resources, instead they provide products engineered to match consumer needs. For decision makers and business teams, the “product” they need is timely, accurate and relevant information.

Business intelligence reports contain information created from refined data. However, they’re often too focused on a specific decision or set of decisions, potentially neglecting the needs of many decision makers. In the real world of business economics, leaders often have to make fast-paced, unexpected decisions. They need a “product” that gives them available, trusted, well-understood information that they can repurpose and use in ways that may not have been conceived of by the report authors.

Decision makers know what kind of information they need. There’s a whole language that describes it - terms like “revenue”, “cost” and “margin. Unfortunately, these terms are often not connected to data in a usable way. They’re applied abstractly to describe business strategies and goals rather than as a way to make concrete decisions based on actual information. But, wait! It’s possible though to express these business concepts using actual values derived from data, and, even better, to set up an information supply chain to enable this new data strategy.

Creating an information supply chain

As with all collaborations, creating an information supply chain begins with a conversation. In this case, between data consumers and data experts. As a first step, consumers decide which business concepts they need to be supported by data. They then talk to the data team, detailing the pieces of information they require to make good decisions. Each requirement is defined and formalized in a way that both the decision makers and the data experts understand.

Next, the data experts determine whether the data they’re collecting can support the requirements and, if not, they identify gaps and create strategies to fill them. This may involve new collection systems for data and new models and schemas to store the data in a consistent and structured manner.

Once the right data is available, it needs to be converted into information decision makers can use. This requires analysis and data transformation expertise and tooling. Special care must be taken to provide clarity and preserve meaning in the processed data and to ensure it meets the needs of the decision makers, as defined in the first step. This is the magic moment when data becomes information that can be used for decision making.

Like any other supply chain, this process is iterative as the business, the needs of its consumers (decision makers) and the data (raw resources) evolve and change. When data and business teams are invested in, and actively promoting and managing the information supply chain, the rewards are huge. Instead of blind decisions based on instinct, leaders can make informed decisions based on real-world information.

There are new tools that help

Many existing tools support parts of the information supply chain setup. For example, those that store, manage, transform, and analyze data. However, there’s no single tool that covers the entire process of converting data to information. Instead, success relies on a combination of analytics tools and cross-team collaboration and communication.

That being said, you’ll be glad to hear there’s a new category of business tools out there. One that creates and delivers information, rather than data, to decision makers in a user-friendly format. Such tools revolve around a data structure, known as a metric, that’s at the intersection of refined data and business meaning. A metric is a queryable data artifact. It contains or exposes processed data around a single meaning, as defined in the metric. By enabling the creation and consumption of metrics, Klipfolio PowerMetrics is a great example of this new type of business tool. 

Revenue is an example of a commonly-used metric. A revenue metric always returns revenue data no matter what context or query parameters are applied. However, a revenue metric isn’t only data. It’s a specific and recognized business concept with a well-defined formula and meaning. Metrics are inherently useful and timely and describe relevant business information that’s understood by decision makers. Metrics are also easily connected to the data that powers them.

Metrics are defined using the process described earlier. Using a tool like PowerMetrics, they’re added to a catalog. Here, consumers can access them as information that’s relevant to their unique business needs. (The metric catalog doesn’t enforce specific uses of the data, only that it is presented to business users as meaningful information) Up-to-date information empowers both daily and unexpected decisions (that often require in-the-moment choices).

Metrics encourage exploration and discovery. For example, existing metrics can be combined into new calculations to better understand rates of change or other business-critical concepts. In short, metrics support and help create the information supply chain that every business needs to be successful in its day to day operations.

Looking for more resources to kickstart your metric journey? There are metric libraries out there that provide a standard set of industry-validated business metrics AND guidance on how to connect these metrics to real data so they can power your business. MetricHQ, the largest online resource for everything metrics, is a perfect example.

Start making informed decisions

The path to informed decisions begins with acknowledging the need for relevant information,  not just data. Start a conversation in your organization today and decide on the steps required to set up your own information supply chain. Working together, your data experts and data consumers can transform data management and analysis into something more meaningful that informs every decision, every day.