There’s often too many variables to consider when making big decisions in business. While intuition and industry experience go a long way, there’s always the risk of overlooking key insights.  That’s where decision science can help businesses succeed.  Further, leveraging agile development practices and taking a human centered approach to the project will help you get more value more quickly from your decision science investment.

There are a lot of terms surrounding decision science – machine learning, AI, big data, data science. These can all be considered aspects of the practice. Our definition of decision science is simple: It’s a practice in which machines help business leaders solve problems that have traditionally been solved by human judgment, intuition, and experience alone.  Through 1904labs’ decision science practice, we help to architect and deploy analytics pipelines, integrate data scientist toolkits, and operationalize machine learning models.  

Occasionally, you’ll find articles online expressing doubt about the value of starting Big Data and data science efforts. Typically, these headlines grab attention but then the examples point to the challenges faced when a data project is started but fails to consider business strategy or the people affected by the systems.  That’s why human centered design (HCD) is crucial.

At 1904labs, HCD is a part of every project, every step of the way. Our HCD Leads work with clients from day one to pinpoint business problems, understand who the relevant business stakeholders are, who the people using and affected by the system are, and focus on the areas most beneficial to the business. This not only saves clients’ time and money, it also helps the engineering team build better products because they are able to architect systems that more effectively meet the needs of the stakeholders and the users.  We call this process Envisioneering.

Starting with these insights from our Envisioneering process, our agile engineering process really helps to put “science” in decision science.  Each iteration focuses on enabling data teams to apply the scientific method:  make observations of their data, form a hypothesis via models, test predictions, gather data, and refine their hypothesis on the next iteration.  

Companies already know they get the best results when they correctly apply the components of decision science to their business strategies. Our HCD infused Agile process helps clients apply these components correctly from day one. The result is boosted profits, better products, and an improved workflow. And most importantly? The right solution is delivered the first time—working the way the users need it to work.