When building your digital transformation strategy, you will ultimately face the decision of crafting your own predictive solutions in-house or out-sourcing to an external solutions provider. While there is no one-size-fits-all approach, there are many different points of note to consider when making your choice:

Speed of Implementation: Development vs. Adoption

Going through the process of developing, testing, validating, and deploying a robust, scalable, and supportable solution internally can be time consuming and involve a greater commitment of internal resources than what is required for identifying, assessing, selecting, and adopting an external solution.

In most cases, an outside industrial predictive solution has been “cooked” by a team focused specifically on the industrial space. These solutions have already been “road tested” with proven ROI in dozens of projects. They have also been previously validated by other clients, making them quicker to deploy. This helps companies see results faster.

Industrial Experience and Expertise Required for Industrial Solutions

Industrial data analytics is a complex field understood by professionals with specialized education and experience. It requires a unique mix of industrial domain knowledge and data science capabilities.

Often companies will leverage internal data science resources by converting existing analytics team members working in other areas, such as business or even marketing analytics, and having them focus on industrial applications. However, working with industrial data is a vastly different area of data science and it presents many unique challenges. Industrial data is typically harder to work with due to its unstructured and unlabeled nature. Industrial domain knowledge is crucial to successfully deciphering and leveraging this kind of data in order to build a reliable and accurate model. In addition to data science skills, other proficiencies, such as system design, connectivity, software development, and more, are needed to see that a solution reaches its full potential in the implementation stage. With all this in mind, building an internal team can prove daunting and many companies typically face an uphill battle when attempting to find the available personnel with the right skills to populate it.

By acquiring a solution from the outside, you are purchasing the collective expertise of that team without having to amass that understanding and proficiency within your internal team, ensuring that the employed solution directly and effectively addresses your industrial application.

Cost-Effectiveness of Internal vs External Solutions

Developing internal industrial analytics solutions can be costly. The budget needed for an internal team to create a solution from scratch is far greater than what is needed for an external team.

An outside vendor usually only charges for their services, specifically the time it takes to configure a solution for a customer’s application. Since the solution is developed by knowledgeable experts and powered by an existing software platform, the time frame is much shorter, resulting in substantial cost savings. This allows companies to quickly realize ROI and see value.

Development and Support Continuity

Another challenge companies face when building an internal solution is staff turnover. Turnover within an internal team results in a loss of critical institutional and technical knowledge. For however long the search for a replacement takes, so too will the company experience significant development delays, as well as repeat work and inconsistent results.

Support for an internal solution could also be compromised by turnover. With an outside provider, the solution is already built and supported by the external team, as a whole.

Applicability and Scalability

Considering the amount of time, effort, and money involved in the development of industrial analytics solutions, the developed solution should be applicable to as many use cases as possible and should be able to do so at scale, in order to realize optimal ROI.

Outside solutions are often more general and can be applied to numerous applications throughout a customer’s value chain. For example, Predictronics has over 25 templates for common industrial assets that we can configure and deploy to meet the unique needs of a client.

With an internal team, each new solution is often developed from scratch, individually. As highlighted above, this not only takes time and money, but also a wide range of skills that an internal team may not have.

Again, by going with an external team, companies benefit from the expertise, previous work, and validation that has gone into the outside solution.

Value at all Levels

Internally developed solutions are not only typically specific to only one application, but they are also often made for one certain type of user, limiting their impact and ability to drive ROI. More general solutions from outside providers typically try to deliver value at all levels of an organization.

For example, although PDX was developed by experienced industrial data scientists, the domain knowledge of these data scientists helped make PDX accessible to those at any skill level, ensuring that PDX provides understandable, and actionable, data-driven insights to decision makers no matter their role and expertise. Companies that have personnel with more data analysis skills can use PDX to do a deeper dive and obtain an even earlier indication of potential issues, as well as identify the source of said issues. Whereas those with less know-how in the company, who are directly responsible for operating or maintaining the monitored equipment, can rely on simple notifications, alerts, and reports that do not require specialized knowledge in order to make rapid and necessary process decisions on the floor. At a higher level, those responsible for equipment performance operation-wide can get a global view of the overall condition of their assets and any potential impacts on productivity that can be avoided before they occur.

There are many factors to consider when deciding whether to create your own solution in-house or reach out to an external provider. While there isn’t one specific right answer for every company, there are many clear benefits to choosing solutions from outside vendors. In terms of speed of implementation, knowledge needed to adopt, expense, scalability, value, and more, working with a solution provider allows companies to deploy solutions in a fast and cost-efficient manner, allowing them to realize ROI and value sooner.

Once you have made the decision to find a solution from an outside vendor, the next step is understanding what kind of solution is right for you. Learn more about choosing the right predictive software for your operations here.

Learn the value of adopting external solutions from our customer, MacLean-Fogg, and gain an understanding of the end-user perspective, as well as best practices to help you on your journey here.