Manufacturing analytics: build it or buy?

Last updated on April 14th, 2024

You know better than anyone how unique your manufacturing environment is. 

Maybe you’ve explored some analytics solutions, sat in on some product demos, and you have decided that no existing platform is just right for you. It can feel tempting to create a manufacturing analytics solution catered to your specific needs  something that uses your own internal terminology and works with your existing systems. 

Remember the companies who built before you...

This is the same thinking that led companies to build their own software to manage Human Resources, Accounting, or Sales systems in the 2010’s. Hundreds of hours were spent creating custom solutions… only to end up with a solution that paled in comparison to software that came on the market in the meantime.

Today, it would seem foolish for most companies to develop their own Human Resources Information Software when they could so easily use something like Ceridian or Paycor.

If those companies had understood the coming trends in software development, they could have saved enormous effort in planning, hiring, building, and maintaining a sub-par solution to their problems.

There are some situations could warrant building your own software, but we would argue that these situations are rare. The global business software and services market was valued at $474.61 billion in 2022 and is expected to grow by 11.9% from 2023 to 2030. As a result, there is software available for almost any business use case you can imagine, and even some you can’t imagine. 

Twenty years ago, no one was thinking that there would someday be a manufacturing analytics tool to help you predict when a quality issue would occur in productionToday, it’s a reality. With products like LinePulse on the market, why would a manufacturer consider taking on an analytics building project? 

Challenges in building your own manufacturing analytics

If you decide to build your own custom manufacturing analytics solution, you will face some unique challenges. It is important to consider what it will take to overcome these problems before you decide to take on a new project.

1. Building analytics is not your core competency

The most successful businesses focus on what they do best

Businesses succeed by focusing on what they do best. Companies like Apple, Amazon, and McDonalds have all succeeded by building their businesses around the core attributes (not necessarily the products) that make their companies uniquely competitive. 

These companies know that splitting their focus too much can lead to disjointed management and operational confusion. Juggling other priorities in addition to your core manufacturing business only leads to inefficiencies and distractions.

Heed the failures others have had at building their own software

A great example of businesses that have taken on software development in addition to the core part of their business are banks. 

Most traditional banks developed their own IT systems and software while that industry was beginning to undergo its own digital transformation. However, one could argue it hasn’t been overly successful. 

Banking IT systems, apps and software tend to fall behind the rest of the tech sector in functionality, ease of use, and design. Often, layers of systems were built on top of each other over time that have gotten convoluted and complex, making it challenging for new employees to learn how to manage them. Old code bases that lay the foundation for these systems are outdated, and small issues can be hard to fix without bringing the whole leaning IT tower down.

2. Your data science and IT team is probably too small

The key to creating a successful piece of software is all in the team. You may have a robust IT and development department already, but creating a new product is quite different compared to the ongoing procurement, operations, and maintenance work that your data science or IT team is used to. 

Is this team capable to consider long-term business needs and ROI? Do they have the skills to design, develop, test, deploy, and maintain a new product?

If you don’t have these people in place, you will need to hire a few. In that case, does your business have what it takes to attract top talent in the tech industry? Successful candidates are used to high salaries, flexible work arrangements, and a specific style of work and management.

Additionally, once your all-star analytics product development team is assembled, it is likely that this team will still be be small compared to the larger ones at many software development companies working on analytics platforms for manufacturing.

A small team can work in a fast and agile manner, but what often falls to the wayside is proper documentation and procedure. Within small, busy software teams, excessive documentation is not necessary to do the ongoing work. But… what happens if two of these project team members leave in the middle of the development process? How easily can they be replaced, when they are taking months or years of domain knowledge with them?

Manufacturing software development team
Small teams can work quickly but can struggle to support a software deployment long term.

After the analytics software is successfully deployed, is there a plan in place for what to do when turnover happens in the development team, and the original developers are not present to help when problems arise? What about planning long-term updates and adding functionality to the software?

3. Building your own analytics is expensive

Let’s look at the costs that may be involved to develop your own manufacturing analytics platform.

Build or buy software math

Oh, and did we mention the need for ongoing support and maintenance for your manufacturing analytics platform? How about the cost required to hire, train, and manage this team of software experts?

The more money you spend on your analytics solution, the longer it will take to get a return on the initial investment.

4. Building analytics can distract from growth in your core business

The software development process is very different from that of manufacturing physical products. Managers, directors and VPs who have spent a lifetime in manufacturing may be unprepared to handle the differences, such as:

Manufacturing management can get distracted by analytics projects. By splitting their time and financial resources up, they will be dedicating less towards the core manufacturing business. Do you really have the time and mental space to monitor another project that is outside your wheelhouse?

5. Analytics solutions take a long time to build

Developing an analytics platform takes time. You will need to:

  • Get approval for your analytics project
  • Hire and build your development and data science team
  • Plan and scope the project
  • Develop and build the analytics tool
  • Test, evaluate, and validate the analytics tool
  • Fix bugs and make revisions
  • Deploy the analytics tool

This could take a year, or perhaps longer.

Building custom analytics software can take several cycles of testing, deployment, and updating to get right.

During the year or more that this entire process takes, other software companies out there are refining and adding more features to their already-built tools. Perhaps by the time you finish developing your custom analytics solution, you realize that there is one already on the market that has the same functionality you were looking for in the first place.

There is also the opportunity cost of the years spent building analytics software. If it takes you 18 months to build a solution, that is 18 months you could have been improving quality and OEE, reducing scrap and rework, and increasing machine uptime if you had instead bought an existing analytics tool.

Why you should buy analytics software

1. Software companies create better software

This is a big one. When a company is entirely built around designing analytics software, they tend to be pretty good at it. They have already put in the work to hire a robust team of highly skilled analytics experts and developers. They are tuned in to  trends in data science, artificial intelligence, and infrastructure technology (for example, the different ways to build machine learning algorithms for a predictive quality analytics solution).

An analytics software company is aware of considerations like security, maintenance, long-term stability, testing, accessibility, and technical support. They know what it takes to bring a successful piece of analytics software to life, and how to do it efficiently. 

Analytics software companies have a plan for the long-term use of their software in manufacturing, and how and when new features should be added. They have customer service teams available to train new users to use the software, and technical support staff working around the clock to resolve any issues.

2. Analytics software stays updated and cutting-edge

Software development is a fast-paced industry that uses speed as a major advantage to compete in the marketplace. Once a new product emerges, it isn’t long before competitors pop up. Software developers are not limited by physical constraints such as building infrastructure or even having a fixed office location to create products. This makes it possible for companies to be as agile and quick as their developers can code.  

Like any competitive industry, software development companies keep a close eye on their competition. To stay relevant, they must incorporate new features that their competitors develop – and more. Your analytics software vendor has no choice but to create the best tool they can, or their company will not survive.

Software companies rely on user feedback to improve their analytics tools. When they receive requests from users to add or change certain features, it is in the company’s best interest to integrate this feedback. This means that their product is build on the feedback of many manufacturers. If you build your own analytics, you are limited by only the features and designs that your team can envision. 

3. Flexibility to change analytics platforms

If you have already bought an analytics solution from a vendor, it is easy to swap to a competing platform for a few reasons:

  • Subscription payment model: Analytics companies usually offer their product on a subscription basis. If you purchase analytics, you can test out a fully-designed platform with little upfront cost. Even if you decide to build your own analytics later on, this investment will not be wasted.
  • Cloud-based architecture: Most analytics platforms operate in the cloud, meaning that there is little change required in terms of hardware to swap providers.
  • Onboarding redundancies: When you first buy an analytics platform, you may need to do some administrative work upfront. For example, you may need to go through a corporate IT approval process for safely connecting to an external cloud instance. Once you have done these steps once, they often do not need to be repeated when you switch vendors.

If you develop a custom analytics solution, it is challenging to switch. After putting the in the initial investment to develop analytics internally, there is strong pressure to use it long enough to get a return on investment, even if the end product is less functional compared to what is available on the market. 

4. You can use OpEx instead of CapEx to buy analytics software

For accounting purposes, building your own analytics platform is likely to be a long-term investment put towards the Capital Expenditures (CapEx) budgets. CapEx is reserved for long-term investments in fixed assets that eventually depreciate over time, such as buildings, trucks, and machinery. 

Getting an expense approved as a Capital Expenditure can be a lengthy process, as the business needs to be certain that the asset will offer long-term value. 

Capex vs Opex spending

When you purchase analytics software (especially a SaaS solution with an ongoing subscription model) this comes out of your Operational Expenditures (OpEx) budget. OpEx are business expenses like employee wages, rent, R&D, legal expenses, etc. Operational expenses are considered short-term, and are used up within the year they are purchased in. For example, one year of rent or one year of employee wages.  

By purchasing software under OpEx, the budget approval process is usually faster and easier. When the software becomes an operational expense, it offers more flexibility to the business, and is easier to manage from an accounting perspective. 

I'm not convinced... I still need to build a custom analytics solution

If this is where you are at, there are still some options for you to get the custom functionality you need, without the risks of building your own software.

Software companies are eager to build products for their large clients, and often work in partnership with manufacturers to tweak or customize off-the-shelf offerings for specific use cases, or even build a custom solution. If you need an analytics software solution tailored to you, get in touch with an Acerta sales rep.

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