February 8, 2022

Written by

Collective[i] Team

  • Posted in
  • Sales Forecasting
  • Networked Intelligence

The difference between networked applications and point solutions – and why it matters

For B2B companies looking for new sales tools, the options are nearly endless — which makes choosing solutions complicated and stressful. After all, sales tools are designed to help teams do their job better and more efficiently, so the right solution can be paramount to success. However, some companies struggle to navigate the process of selecting the right sales tools.

A 2019 SalesTech report by Smart Selling Tools indicated that the median number of sales tools used by a company is nine. While that may not sound like many at first, it’s a lot of tools for employees to navigate and spend time using — especially for new team members who have to learn to use each tool. Essentially, some companies are dealing with tool overload.

The solution to tool overload is platform-based solutions (also called integrated solutions) that provide end-to-end intelligent applications for an entire team. Point solutions may be able to help with individual tasks, but their efficacy is too siloed and simply cannot operate at the advanced level required by teams today. This article will explore point solutions vs integrated solutions and how networked data sets are helping platform-based solutions outperform point solutions across the board.

What is a point solution?

A point solution is a product, tool, or service that is designed to solve a single problem. Point solutions have an incredibly narrow focus, with providers aiming to meet a singular need very well. For example, a point solution example could be a helpdesk tool, a room reservation assistant, a meeting scheduler, or a new sales training tool. The main idea is that it solves one need.

There are certainly some advantages to adopting point solutions, including deep functionality, vendor expertise in a single area, and the ability to implement a new tool without upending anything else. However, while point solutions can be very good at what they do, therein lies the weakness, too. Point solutions solve one problem without any consideration of context, other tools, or other problems. Disadvantages of point solutions include:

  • Management of multiple tools from multiple vendors that may not integrate well
  • Complex user training of multiple tools with different features, functionality, and onboarding
  • Solution overload, meaning too many tools or services are overwhelming employees, decreasing efficacy, or demanding too much time to use
  • Burden of IT to support several systems with different back-end requirements

What is a platform-based solution?

A platform-based solution, or integrated solution, is a set of tools or services that are packaged together and act as an end-to-end solution stack. Just like any system, there are some drawbacks, such as high upfront costs or larger time commitments, but the pros of platform-based solutions far outweigh the cons.

With platform-based solutions, rather than cobbling together several tools from several vendors, a company has everything it needs in one platform. That means data, storage, and connections between functions are integrated and automatic, ensuring that teams are operating off the same set of data and the same information. A platform-based solution also better facilitates cross-departmental collaboration and has fewer integrations and lower maintenance costs. But the real beauty of platform-based solutions lies in the potential to support networked data and intelligent applications.

The difference between intelligent applications and point solutions — and why it matters

Intelligent applications support both narrow data and networked data and have the power to learn from data to provide unique information and insights.

  • “Narrow data” refers to internal data, specific to a company’s knowledge about its products and market.
  • “Networked data” refers to a wide net of pooled data collected from a broader set of sources that feeds into intelligent applications and enables them to improve and learn.

Combined, this means that platform-based solutions, powered by intelligent applications, have the power to go beyond providing simple solutions into providing intelligent suggestions, recommendations, and insights — something point solutions simply can’t provide due to their limited scope.

And this means freeing up more time for revenue-generating teams to generate revenue — not analyze data to decide what move to make next. Collective[i]’s C[i] RecommendsTM, for example, uses networked data from top sellers to guide the work of every seller on a team. Collective[i]’s Intelligent ForecastTM uses networked data to augment a team’s sales forecasting with vast networks of dynamic data.

According to Stephen Messer, co-founder of Collective[i], “The future of work is about enabling agile and highly targeted execution that adapts to market changes and customer preferences. Intelligent applications are the underlying technology enabling this transformation.”

In truth, the B2C industry has been using networked data for years, with huge amounts of success. Companies such as Amazon and Netflix capture their customers’ transactions in their systems to collect massive amounts of networked data, which they also collect from other aggregated, external data sources. All of that data enables them to learn from customers’ buying habits and radically improve customers’ experiences with more accurate product recommendations and on-demand services. Messer sees this transition to networked data is beginning to happen in the B2B world and says that late adopters are going to have a difficult time catching up to their early-adopter competitors.

That’s part of the reason he co-founded Collective[i] — to give B2B companies better, smarter solutions. Collective[i] is the only enterprise solution that uses an intelligent model to provide users with all the benefits of a platform-based solution combined with the power of networked data. Experience the difference Collective[i] can make today.

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