As humans, we like certainty. We strive for the “definite” everywhere—from looking for the best in purchases and investments to our lifestyles and even relationships. It stands to reason that we do the same with business decisions. Many of us may be so preoccupied and comfortable with our choices that we rarely want to revisit the underlying assumptions and instincts. And yet, we are surprised when age-old business strategies suddenly start to fail.
Take, for example, the fashion industry. Fashion trends are changing faster than ever. If inventories are designed based on traditional models and only changed quarterly, stores cannot keep up with updates in consumer outlook. If, instead, they utilize mathematical analyses of data, they can find more success with customers whose tastes are different every month. Bringing in data scientists who continuously monitor consumer trends on social media and elsewhere can help brands stay up to date on the constantly changing landscape.
APPLICATIONS OF DATA SCIENCE
The application of data science can also be exceptionally transformative for fields outside of fashion, such as digital marketing. Many marketers may not be able to look at success from LinkedIn, social media, or proprietary data sources and figure out the right mix, and as a result, strategies may not be tweaked when required. However, with insights from data science consultants, campaign managers can adjust outbound campaigns daily instead of monthly. This can lead to lower money- and resource-churn and fewer lost opportunities. It can also enable businesses to improve processes and move beyond digital marketing.
Retail chains like 7-Eleven are great examples of how this applies to inventory management. Each store carries hundreds of items and many different varieties of each item. Using data science to look at all the locations and traffic, it is possible to gain comprehensive insights about which item is selling at what rate and where it should be positioned in the store. One item may be selling much faster in a particular store but not in a different store due to a difference in positioning. Enabling highly analytical insights in a simplified manner can allow companies to change strategies across locations daily to increase sales. As fixed costs remain the same but sales go up, companies can improve revenue.
DO BUSINESSES NEED A DATA SCIENCE CONSULTANT?
Data scientists are highly trained and can evaluate whether your business strategy is rooted in quantitative evidence. They also consider a much broader scope of real-world performances of solutions and strategies.
For instance, a business plans to invest X amount of dollars in acquiring Y amount of leads based on the advice of consultants with historical data. A data scientist can predict the exact rate of lead generation. More importantly, they can look at the bigger picture in the industry and find examples where a company with similar strategies may have failed and pinpoint the exact cause of failure. This can enable the company to tweak its business plan and avoid the same mistakes.
Perhaps one of the biggest arguments against hiring a data scientist is that computers can do it all. However, even the best data analytics and business intelligence tools require a skilled data scientist to unlock their true power.
Data science algorithms and consultants work best when they deploy in tandem. AI models run in real time and need negative feedback from human inputs to stabilize without disruptions as the assumptions behind the model change. The math needs continuous fine-tuning by a person to align with modeling objectives. Data scientists can be AI modelers, but AI modelers or models cannot serve as data science consultants. These consultants are needed to continuously examine results and perfect the performance of the AI in ever-expanding contexts.
Data science is more adaptive, and the numbers and models deployed by scientists are continuously evolving. Companies do not need to sail in blind and throw strategies at the wall to see what sticks. The quantitative fundamentals of data science can tell businesses precisely what will work and to what degree of success, even in changing contexts. Data science support is consistent and helps companies with long-term decision-making while remaining adaptable to the unexpected changes of market demands.
FINDING THE RIGHT DATA SCIENTIST
The need for data science consultants is critical, but you may not be clear on how to find the right one for your business. Businesses need to strike the right balance between the data scientists’ skillsets to build remarkable adaptive models and their ability to grasp the DNA of the business. Interviews alone may not be an effective tool in such hiring scenarios.
Companies should have clear-cut, needs-based objectives and ask data scientists to pitch them solutions. This can significantly improve the quality of the hire, as companies get insights into the fit of the proposed solutions and the scientist’s thought process. It is also necessary for companies to keep an open mind and be willing to listen as the person and the company adapt to each other.
The need to tap into your data streams and truly understand them is greater than ever. With more businesses unlocking advanced data tools and talent each and every day, shifting to a data-first strategy is mission-critical. In this world, if you’re not ahead, you’re falling behind—and it won’t take long for the distance to be too far to make up.
Founder, CEO, and CIO of HGM Fund, managing investments in the financial technology, health technology, and communications industries.
