Organizations should consider democratizing data science to enhance its benefits to a broader audience.

Data science is the backbone of many organizations in the current scenario. Businesses are continuously competing to become data-driven to enhance agility and growth especially in today’s time of crisis. The pandemic accelerated digital transformation across the industries and data plays a huge role in achieving this transformation. According to BARC research, organizations leveraging Big data reported an average 8% increase in revenues and a 10% decrease in costs.

Data science for business is not a new strategy and thus is not unfamiliar. Artificial intelligence and data science go hand in hand to automate operations and deliver the best business insights. Data is a critical business asset and hence data science has a great impact on revenue, operation costs, risk management, customer experience, supply chain and logistics management, predictive analytics, and fraud detection.

To achieve business productivity and growth, many organizations are investing in data science by hiring data scientists into their systems. Data scientists are professionally qualified in studying data and deriving insights from them. However, due to the importance of data science, companies tend to centralize on data scientists rather, which decreases the awareness among the others.

Data science needs to be decentralized and democratizing data science in organizations should be an important business agenda.

Democratizing Data Science- As a Strategy

Extending the accessibility of data science across an organization needs a definite plan. For example, understanding and implementing data science for beginners might be difficult considering the lack of communication and awareness on the subject.

• Once they have data scientists, companies often forget the need to communicate the broad vision of data science to others. This scenario should stop. Enhancing communication and educating employees on the power of data and data science is a crucial step in democratizing data science in organizations. Employers should work towards upskilling their employees on data analytics and gaining business insights from it. This kind of collaboration within a work environment will increase the knowledge about data science and enable people other than data scientists to leverage data science. Involvement is the key.

• Unburdening your data scientists can be another way to standardize data science in your organization. Most of the organizations maintain their data science tools with the specialized data science team creating a silo by restricting other employees from accessing these tools. The data science silo needs to be broken so that these tools can be shared among others enabling them to act on issues that need basic training. Thus, the data scientist team can focus on tasks that need high-level expertise. Integrating AI and machine learning systems to automate repetitive tasks can also free up data scientists.

• Sharing tools are not enough since analyzing data requires specific skills. Organizations should make sure that they create a knowledge pool to share data science skills and train employees on the same. Once the employees have hands-on experience, it becomes easier to find solutions. When employees start understanding the language of data the business productivity escalates considering the huge capabilities of data analytics and science.

• Organizations should incorporate user-friendly tools like no-code or low-code automation, graphical user interfaces, drag and drop technology, etc. to enhance the accessibility of data analytics to the whole organization.

Data science in organizations should be accessible to all the employees rather than restricting it to a particular group. The strategy of democratizing data science in organizations will enhance the scalability, enable better innovations, fast-track productivity, and minimize costs.

An article by Jeff Feng, PM lead for Data at Airbnb reveals how the organization has embraced data science democratization by introducing Data University, which is ‘data education for anyone.’  He says, “Our vision is to empower every employee to make data-informed decisions. Our approach is unique since organizations offering data education typically focus just on their technical employees. Our approach is also intentional because we believe that every person at Airbnb should and can utilize data in his/her role to make better decisions. Thus, we designed the program to make it accessible and relevant to anyone at Airbnb.”

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Traditional marketing approaches for kitchen and bath showrooms have generally involved identifying market opportunities from trends such as neighborhoods that your showroom serves, customer demographics and a healthy dose of throwing spaghetti against the wall to identify what would stick. However, this approach, while at times effective, is extremely inefficient.

Marketing today has been transformed from trial-and-error to a more sophisticated and scientific approach using data analytics to identify new and underserved markets and to develop growth strategies. Analytics were initially used by businesses to determine the effectiveness of marketing and advertising campaigns, measuring the impact of their value propositions and calls-to-action. The effectiveness of those efforts expanded the use of analytics to enable businesses to:

• Better understand market size, potential customers, customer preferences and behaviors.
• Enhance customer experiences.
• Test new products/services.
• Improve marketing spend and return on investment.
• Optimize pricing strategies.

Most kitchen and bath showroom owners are likely to believe that analytics are something that only big corporations use. They may erroneously believe that they don’t have time, the resources or the skill sets needed to employ analytics to help develop business growth strategies. But nothing could be further from the truth. The bottom line is that companies that use data – not simply gut instincts or guesswork – are going to win. Trade-area analytics could well prove a critical factor in assuring business growth.

Data can assist in isolating targetable areas for remodeling activity at different price points. It can help pinpoint where you’ll receive the greatest return on your marketing spend. It can also help you develop more effective marketing messages tailored to a specific demographic and improve the look, feel and effectiveness of your showroom by helping to assure a consistency of image between marketing and sales efforts and showroom displays.

How Do Analytics Work?

Trade-area analytics identify and evaluate targeted demographics in a service area, usually within 30 minutes’ drive of a showroom’s location. The process examines demographics and consumer purchasing behavior in specific zip codes within a service area. Typical criteria used to evaluate a showroom’s service territory are number of homeowners with discretionary income, owner-occupied heads of households aged 35-64, number of houses built 20 or more years ago, level of remodeling activity in that neighborhood, and the percentage of homeowners likely to purchase kitchen cabinets or renovate their kitchens or baths.

What’s eye-opening for most showrooms that are aware of trade-area analytics is that demographic information for every neighborhood in the U.S. is readily available at no cost from the U.S. Census. Within the Census, you can search any demographic that you want by income level, zip code or other criteria. Simmons National Consumer Surveys can also assist in determining the level of kitchen and bath remodeling activity in specific zip codes and neighborhoods surveyed.

After performing a zip code analysis of a service territory, the next step is to create a map of the showroom’s job history for the past two to three years and compare that to the trade area analysis that shows neighborhoods with the highest sales and remodeling potential. Some 80% to 90% of the time, there’s a disconnect between where opportunity exists and where a showroom has been servicing, and that disconnect shines a spotlight on growth opportunities.

“I was surprised by the ability to take a map and pinpoint exactly what you want,” says BKBG member Danny McGeady, of JEM Designs, in Beavercreek, OH. “The analytics identified specific neighborhoods that are ripe for remodeling, primarily those featuring production homes built more than 10 years ago. From old listings, brochures and other data, we could accurately estimate the size and configuration of existing kitchens and the number and size of cabinets.”

Using that information, McGeady says, he developed a direct-mail campaign that features a new kitchen in the homeowners existing home and what it would cost. In contrast, past marketing efforts, McGeady notes, employed TV advertising to help build his brand.

Another reason to target specific neighborhoods using data for growth opportunities is the concept of “homophily,” which suggests that people who live next to one another share similar characteristics and circumstances, and thus can be drawn to use similar products and services. People who live in the same neighborhood not only consume similar goods and services, they share what they like, and their endorsements are the most trusted of all.

Neil Pfeister, of Englewood, CO-based Enchanted Kitchens, used the information identified in the data analytics of his service territory to develop and implement a drip marketing campaign that generated 400 leads in the last year, resulting in nine new projects.

“We never realized the depth of data that was readily available to us. Far and away, analytics have generated the best cost of leads and sales returns that we’ve ever had,” Pfeister says.

Justin Leatherman, of Leatherman Supply, in Goshen, IN, notes that “some of the zip code opportunities identified by our trade-area analytics shocked us. We were missing opportunities in a neighborhood directly across the street from our showroom.”

Leatherman not only is using trade-area analytics as a cornerstone to grow sales; he also plans to use them to identify locations for potential new showrooms.

Understanding the Market

Most showroom owners understand their market dynamics, but not many have a comprehensive grasp of the depth of their market. For example, they know how far a customer will likely travel to use their showroom and they have a fairly good idea of the cost of homes in their service area, but what they don’t often understand is the number of homeowners that are potential customers and the potential volume of business in their market. Data analytics provides that information.

The vast majority of kitchen and bath showrooms do what they do because they’ve been doing the same thing forever. They may almost exclusively serve a specific price-point customer. But if you limit your sights only on the customers and demographics that you currently serve, you may be missing 35% to 40% of your market. Trade-area analytics identify that 35% to 40% of market potential most showrooms never know about.

Big data is not the exclusive province of big businesses. There is nothing to prevent a showroom of any size from using trade-area analytics to identify new and underserved markets in their own backyards. Best of all, the data you need to make better decisions and develop more effective growth strategies is available in a few clicks at absolutely no cost. 

Tom Cohn is the exec. v.p. of the Bath & Kitchen Business Group, a Bethesda, MD-based, shareholder-owned organization of independent kitchen and bath design firms. He has more than two decades of experience providing growth strategies for kitchen and bath and decorative plumbing and hardware showrooms.

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