Data science projects are being used by leading companies to grow business models and expand opportunities. How so? In general, data science efforts produce two results – they help produce better products and help leaders make better decisions. Let’s explore.
Products that Improve Themselves
Self-improving products may sound somewhat far-fetched. Yet, in today’s data-smart companies, products are actively re-designing themselves. These dynamic product changes allow companies to outsmart their competition faster, and overall move the market expectations forward at a more rapid rate. We can look to the aerospace and defense industries for proof – in these industries, data science is redefining capabilities by expanding the use of:
- Predictive software – software that can tell you what a customer or user is likely to do with your product, and even display what the software “thinks” your customer will want to see next
- Interconnected products and parts – reducing engineering time and preventing problems before they happen
- Utilizing 3-D printing to improve supply chain performance and product design – data points about actual product failures and usage can be fed back into 3D models
Data that Improves Products
Consider for a moment an engine for a race car, which has many external and internal parts. Modern engines are full of sensors, which can measure data points such as emissions quality or piston timing. Other data measurements might be the relationship between the tire and the road surface, or shift point information coming from the transmission.
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When dealing with data science projects such as these, it is important to have a goal. If you want your car to go faster, then use the data reported by the all of the parts to improve engine performance – it may be the case that a piece of data that you wouldn’t normally associate with engine performance has an effect that you wouldn’t expect.
This same process applies to business processes within your company, and those experiences your customers have. Whether we are talking about making decisions or improving products data science helps. If you need to improve sales, then turn to data science. Available technologies can help leaders evaluate, predict, forecast, and solve problems. The data show where improvements must occur to meet your goal.
Data Science Goes Beyond Just Telling
In some industries, data science projects are not just for telling you when there is a problem, but for showing you how to fix that problem. For example, your engine has a poorly designed fuel injector. If sensor data shows that the injector is not fuel-efficient, it can also show you why. It can, when paired with the right software, redesign the injector. This helps to solve the problem so you can meet your fuel efficiency goal.
Data Science Projects and Decisions
Five years ago managers and leaders made decisions based on protocols. If “A” happens, do this. That kind of decision-making worked and produced a consistent set of results. As technology improved, the process of decision-making using protocols became less efficient. Today, data science projects empower managers and leaders to make decisions that reflect real-time situations. The difference is that while protocols provided instructions that are situational, data provides solutions optimized to 
fit each situation.
Data science is an interconnected web of streaming information. It produces tools that allow business leaders to lead more efficiently. Decision making becomes easier, and product development and improvement become faster.
Does your strategic IT plan include tackling data science initiatives? To learn how these might help your business, reach out to our professional team.
Free Project Cost Estimation Tool
Download this free Microsoft Excel Project Estimator tool to gain some insights into what your software development project might cost! Fill out the form at the right to download this FREE resource.
