With the advent of technology, everyone began accumulating data at a rapid-fire rate. With easy access to low cost computing power and Cloud software, more small to medium-sized businesses (SMBs) have been empowered with data, and the ability to learn from it, than ever before.
The ability to leverage large amounts of data effectively used to be cost prohibitive for smaller organizations. Many SMBs lacked the capital means to perform a number of key tasks that are foundational to using data well, including:
But Cloud software has changed the game. Not only has it eliminated many aspects of these up-front barriers, it has also allowed SMBs to benefit from crowdsourced learnings that are built into the solutions themselves. The best SMB Cloud software solutions will take care of the heavy lifting on the data collection, aggregation and governance side of the house, ensuring that results are coming from a single source of truth.
Additionally, the best solution providers will offer templated and flexible reporting and forecasting capabilities, which can reduce or entirely eliminate the need to employ specialized data and analytics professionals.
To be successful with data, it’s important to develop a data informed mindset. In this guide we’ve brought together research from organizations that have spent millions trying to understand why companies win and lose based on their use of data. Now we’ve broken it down for your convenience, so that businesses of any size can use it to build strong, data informed foundations.
So how do you merge data driven results and human intuition? And how do you introduce data informed decision making into your company without being overwhelmed by the sheer volume of information?
Let’s find out.
Evolving to become a data informed merchant is no small task, but the transition doesn’t have to be overwhelming.
Although you’re looking to purchase Cloud software—to help take care of your organization’s data, provide access to templated reporting and forecasting, and more—it’s important to think about the data itself first. Fortunately, there are already well-defined strategies in place that you can use to ensure the process toward your new mindset and even operational structure are as efficient and straightforward as possible.
A Deloitte study breaks down the 5 key factors in any data project as strategy, people, process, data, and technology—with strategy as the first step, always.
Before undertaking any organizational initiative it’s important to understand the root of why you’re doing it.
Is it to identify a new product category, marketing strategy, or pricing sensitivity? Are you trying to optimize shipping costs to increase margins? In every scenario, it’s critical to begin with the ‘why’ and build from there. Develop measurable outcomes for your vision with a project roadmap.
Ensure they are feasible and realistic; in certain instances, accepting many small projects is more useful when building competencies than waiting for one ‘perfect’ project and stagnating in the interim. Smaller projects allow for more growth and honing an experimental mindset, both of which are necessary to ensure success when implementing a new data informed operating model.
Having an experimental mindset is critical for thinking about data—and becomes especially important in data informed decisions, which leave room for human interpretation. According to a Harvard Business Review report, “Big data requires ‘little experiments.’” Correlation does not always indicate a causal link, and any relationships you observe between datasets needs to be rigorously tested for validity.
As a McKinsey report argued, aggregating all your data without a filter leaves room for misinterpretation and loss of key information in the shuffle. As such, the real impact of data interpretation comes from taking the results of data a step further and vetting them for the truth.
“Culture eats strategy for breakfast.” - Peter Drucker
Any new initiative is made or broken by the people in an organization. In order for data informed initiatives to be successful, the proper culture and management practices have to be in place beforehand to provide foundation and support. According to a paper published by the Harvard Business Review, adoption of a change project must begin at the top: initiatives build confidence when leaders demonstrate their trust in the system.
When encouraging a data informed mindset within your company, this involves setting up best practices for how people should approach data. Incentivize information sharing and quality assurance between teams. According to an EY study analyzing the data habits of senior leaders, over 50% of participants viewed poor data quality as a concern. Data management is incredibly important for successful projects, and happens most effectively when data integrity is on everyone’s mind and is ingrained in the culture.
When everyone stays on a course toward a common goal, processes and habits become easier to form and maintain.
Culture and change management are not a one-and-done strategy. Upskill your people through various means and initiatives, and hire individuals that you believe can learn quickly and drive success.
According to a McKinsey report, you may already have individuals in your company that approach problems with an experimental and data informed mindset; conduct an audit to determine the potential gaps (or talents!) your team already has.
Let’s briefly revisit process. Process at your company is important because it reinforces strategy, sets habits, and allows you to critically evaluate how you drive decisions.
It may not be the foundation of your change project the way strategy and culture are, but it’s the steam engine that keeps it moving. Process on a personal level reflects how we think, react, approach problems, and more.
An experimental, data informed process goes through the following steps for any task:
In this model, your organization must be willing to challenge or change any current processes. Even technological processes can become detrimental if you begin to disqualify better alternatives in favor of options you have used before. Don’t trap yourself in ‘legacy thinking.’ An Inc. article reported that it was common for organizations to struggle with their legacy systems, unable—or unwilling—to take the leap toward something potentially better.
This is not to say that change projects should happen blindly—rather the opposite!
Data informed mindsets and processes encourage evidence-based, calculated risk. In this way, risk tolerance supports experimental mindsets because it leverages data to drive insights that examine the way your business operates, before driving action to improve.
Shared, high-quality data is imperative to driving the success of any data informed initiative.
A report from EY found that while “81% of organizations think data should be at the heart of every business decision,” the majority are still using isolated systems and ignoring the red flags that signal change. Silos have to be broken to achieve a holistic view. Any insights gained and action driven as the result of incomplete or bad data will inevitably produce equally poor results.
Resolve a lack of collaboration in your organization as a way to improve shared data; encouraging cross-team projects and multidisciplinary thinking can drive more focused business outcomes and better customer experiences.
While your organization may have one or more experts that are proficient in data analysis, it’s critical to develop a certain degree of data literacy across all roles.
In an article by InfoWorld, the business intelligence software provider Sisense revealed that the best data informed companies are those that understand when data should be omnipresent and accessible at a company. To that end, it’s imperative that “every person who can use data to make better decisions has access to the data they need, when they need it.”
This concept is the data informed strategy at its peak: quality data, when peer-reviewed and made available to everyone, is the tool that empowers data literate decision makers and their teams to drive quality results.
The technology partners your organization selects should be chosen based on their ability to ease and enhance your data collection, access, and evaluation process.
According to a McKinsey study, one of the key underpinnings of a successful data strategy is the “deployment of the right technology architecture and capabilities.” You need to find a technology that works for your current goals and can scale to meet your future objectives.
With the introduction and low costs of Cloud technology, the barriers to adopting and advancing smart technology are lower than ever before. Compared to on-premise installations that require heavy infrastructure and individuals to maintain, many of today’s Cloud technologies can be operated by smaller businesses and teams of one. Which is why, as a Harvard Business Review study suggests, it’s important to leverage technology with a powerful back-end and a user-friendly interface.
Moreover, the best Cloud systems for SMBs often provide data in pre-packaged reports that have been cultivated by data from thousands of customers. Now, even companies without the resources for robust internal crowdsourcing or a dedicated data analyst are able to access information in a format that has been reliably tested, vetted, and approved.
Automating processes is the foundation that leads to more efficient and effective operations. By turning to technological systems for automating elements of your team’s day-to-day activities, you can eliminate error-prone, repetitive, and manual tasks that would have been previously required for data aggregation and preparation.
Merchants from across all industries and sectors are embarking on digital transformation journeys to become data informed organizations.
Because of the Cloud, the barriers to becoming a data informed merchant have never been lower, and shared learning has never been so accessible. Through the task of digitally transforming your business, you can seek answers to countless questions. If you’re new to the journey, we recommend you start with the following:
If you’re going to succeed, remember the importance of defining an appropriate and measurable strategy—regardless of your project, this will be your first step. Educate and build internal structures and a culture to enable and support this new strategy.
Set up processes to encourage questions, different viewpoints, and projected problems. Establish best practices to keep quality data accessible to all relevant parties. And finally, explore your technology options, and ensure the choices you make are those that best set you up for a more efficient, effective, and successful process.
Whether you’re a large-scale organization or a small- to medium-sized business, data informed decision-making can help you drive results that will improve your business and, ultimately, your bottom line.