<img src="https://secure.leadforensics.com/133892.png" alt="" style="display:none;">

It’s a common question: Does my company need to use Microsoft Dynamics 365 solutions across our entire operation to see tangible results?

In short no, not necessarily. You can benefit from running just a few of your operations on Microsoft. Microsoft Dynamics business applications are designed to address specific business issues while working in conjunction with other solutions.

That said, there are certainly some big bonuses that come with adopting a complete Microsoft solution. Leveraging the entire Microsoft stack provides unmatched agility in connecting every area of your business faster and with better precision compared to disparate systems.

Adopting a complete Microsoft solution

Microsoft has designed the various entities of its tech stack to function in an elegant lockstep. Other providers can’t match that cohesion right now.

The goal is to drive outcomes for specific requirements and specific business processes.

Microsoft Dynamics 365 encompasses applications that offer breadth and depth to a company’s operational needs, including sales, finance and supply chain, field service and project service automation.

Those applications offer an incredible user experience on its own, but the apps are also designed to work with other Microsoft business offerings, including its Azure cloud services, the Microsoft Power Platform, and Microsoft Office 365. The Power Platform includes Power BI, Power Apps, Power Automate and Power Virtual Agents.  

These entities focus on streamlining your company’s end-to-end process. Power Apps, for instance, gives people the power to create beautiful applications without developer-level knowledge.

Microsoft makes data a game changer

Now let’s talk data—my favorite aspect of Dynamics 365.

The Microsoft tech stack uses the Common Data Service and the Common Data Model, which is the shared data language used by business and analytical applications.

The Common Data Service allows for integration of multiple data sources in one single store, which can then feed into Dynamics 365, Power Apps, Flow and Power BI. This equates to personalized, game-changing insights about your company—all based on the data you collect across your organization.

So what?

Unlike other ERP platforms, Microsoft focuses its platform around the movement and consolidation of data, meaning you can exist in a world with multiple CRM systems, ERP systems, as well as data flowing in from customers, social media, and other structured and unstructured data points. Then you can begin to transform and manipulate that data for decision making.

For example, I often see these features become paramount for companies with acquisitions, who need to streamline inherited technology into a unified view. Or companies with lots of machinery and equipment—the Common Data Model delivers data insights that allows these organizations to adopt an efficient predictive maintenance model and discard the break-fix approach.

Most other solutions only focus on finance as the core—Microsoft starts with the data.

All Microsoft or nothing at all?

It doesn’t have to be all or nothing. People have existing investments and strategies and Microsoft has architected its solutions in such a way that they can play nicely with others in the sandbox.

The reality is people are going to have other platforms and that's okay. We can still funnel data in and leverage the existing investments organizations have and augment pieces of the Microsoft stack that make the most sense.

So hypothetically yes, different entities can get along. They can integrate so that using all Microsoft products is not mandatory.

One of the main “pros” for opting to work with existing solutions, or only introduce a few new things, is that there’s no need to invest resources into retraining employees.

The “cons” include extensive integration and data latency that takes too long to garner results and drive business.

For example, yes, you can take 16 different ERP versions, consolidate the data and produce a reporting/forecasting engine for minimal cost that will allow you to make better decisions, but it won’t be as fast as migrating to a unified Microsoft solution.

My best advice when decision making is to start by considering your data. At the end of the day, it’s about finding the best fit for you and your company. Want to talk about solutions specifically for your company? Feel free to connect with me on LinkedIn or via email.

Next read: How do I create a data strategy and data plan for my business?

Topics

Discuss this post

Recommended posts

By 2023, digital transformation-enabling technologies and services are expected to touch the $2.3 trillion mark, according to a Statista study. Clearly, digital transformation in manufacturing is—and will be—the flavor of several seasons to come. Manufacturing companies are actively pursuing smart solutions to optimize their processes and output by leveraging next-gen technology. A key step is the adoption of an efficient manufacturing data and analytics solution—one that is capable of helping organizations take data-driven, informed business decisions.
Data analytics have drastically changed the nature of competition across multiple industries, according to 47% of respondents in a recent McKinsey Global Survey. Companies leveraging analytics saw the most overall revenue growth in the survey.
Back in 2017, Gartner reported less than 10% of enterprise Internet of Things (IoT) projects involved an artificial intelligence (AI) component. At the same time, they also predicted that this percentage would leap to over 80% by 2022. Today, industries are so frequently using these technologies in tandem that some people are asking a somewhat contrarian question, “Can you have IoT without AI?”
The Purchasing Managers Index (PMI) – a widely recognized leading economic indicator – registered at 47.2% in December, below the 50% that indicates the manufacturing sector is expanding. It was the lowest reading since June 2009. 
Data has been a very hot topic among clients lately. Specifically, I keep getting asked: "How can I create a strategy and plan around my data?" Most people I talk to are working for companies that collect data at every turn of the supply chain. This data might come from heavy equipment machinery or e-commerce metrics or financial growth numbers—the point is, it's usually contextually diverse and there's a lot of it.
right-arrow share search phone phone-filled menu filter envelope envelope-filled close checkmark caret-down arrow-up arrow-right arrow-left arrow-down