4 ways data science services is helping businesses reach IoT goals, faster

Data scientists are a key component of an IoT deployment, however in-house data science resources can become thinly stretched. Outsourcing data scientists has the dual benefit of helping keep IoT initiatives moving forward while freeing up internal resources to focus on other areas of the business.

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Data scientists are an essential part of an IoT deployment. They fill a critical need to interpret data and provide valuable context around machine learning. However, as IoT initiatives expand and mature in a business, in-house data science resources can become thinly stretched. This creates a data pile-up that is a surefire way to set your deployment back.

Hiring more data scientists is typically not an option either as there is a significant shortage in the market. Demand is only going up too: Gartner predicts that a shortage of data scientists will hinder 75% of organizations from reaching their full potential with IoT through 2020. Because hiring is difficult, time consuming and expensive, many organizations are turning to data science services to fill in resource gaps. Outsourcing data scientists has the dual benefit of helping keep IoT initiatives moving forward while freeing up internal resources to focus on other areas of the business.

How does it work? Ideally, a data scientist will meet with your team first to discuss goals and explore available data. This typically includes pinpointing a specific business objective and then mapping available data against the desired outcome. If the required data is not available to achieve a more ambitious objective such as predicting a future event, like equipment failures or demand, plans can be made to obtain it. Meanwhile a data scientist can help you discover what outcomes your data does support now. This helps you begin taking steps toward your bigger goals right away.

Next, the data scientist accesses the data and begins the analytics process. This should be a collaborative exercise, with internal SMEs participating throughout to provide data scientists with more detail regarding the operating characteristics of the equipment being analyzed. A data scientist operating without this first-hand insight will almost certainly miss important equipment and operational nuances. Pairing data modeling and analysis with institutional knowledge from internal SMEs is therefore essential to achieving optimal results.

Data science services can help you get your implementation running in weeks to months, depending on the scale. They will also play a part in maintaining and optimizing your solution over time to incorporate changes and other factors of maturity. IoT is an ongoing process, and data scientists play a critical role in continuing to update and optimize a solution to maintain accuracy and relevance as conditions and environments change over time.

Data science services have become a lifeline in an IoT deployment. Four of the most compelling top-line benefits include:

1. Key projects can work in parallel, not sequential

With limited data science resources at your disposal, it’s pretty typical to schedule IoT initiatives by priority, time-to-value, or potential to deliver the greatest ROI. But if you have multiple high-value efforts, there is no reason not to pursue them in tandem. Sometimes, data can be exchanged between the two to a) speed up progress and/or b) deliver a greater cumulative value.

2. Because it’s a service, you can scale up and scale down depending on needs

Some stages of IoT require more “heavy lifting” data science, others much less. Using outsourced data scientists, you can schedule only what you need. Hiring full-time data scientists is a much heavier investment in terms of hiring and salary costs, as well as training.

3. Greater depth and breadth of expertise to tap

Incorporating the knowledge of a larger pool of data scientists makes it possible to more effectively address a wider range of problems on an accelerated timeline. By applying related experiences to new problems, data scientists can find patterns and look for problems in areas that internal SMEs may overlook. They can also help you avoid making common mistakes or wasting time diagnosing root causes of issues.

4. In-house data science resources are freed up to focus on the highest priorities

Augmenting in-house data science capabilities with additional capacity allows a team to do more, better and faster. Internal resources are able to reallocate their time to dig into more pressing matters and add value wherever it’s needed most.

The benefits of data science services are enormous for IoT initiatives that are just starting out. An outsourced data scientist engagement can help you review what data you have and what goals you’ve set to help you determine if what you want to do is possible. Having the right foundation from the start is key to reaching success much faster. But Data Science Services are also designed to help businesses mature their existing installations or quickly overcome a roadblock, such as underperforming results.

If you’re considering a data science service engagement, consider the past work of the company. Do they work with businesses like yours? Ask for case studies to determine what progress past clients have made and how quickly. Once you’ve found your match, be sure to request a timeline for key milestones. This will help set expectations with the team as well as help keep both parties accountable for their work. Be prepared to help considerably. I can’t emphasize enough how critical SME involvement is in making your IoT implementation a success.

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