For example, automated, data-driven solution design engines improve the lead-to-requirements-to-order process for enterprise IT sales. With easy access to a wealth of relevant content, solution architects can quickly build validated graphical solutions that adhere to vendor interoperability rules, and attributes.

Details, Details: an Industry-Tailored Data Model

Validation and configuration rules are the tip of the IT sales “big data” iceberg. A comprehensive knowledge base includes up-to-date product and service catalogs from multiple manufacturers and deal and promotion feeds.

At the core, is a data model that supports an extensive knowledge base with millions of routes and rules, parent-child relationships, component attributes, pricing, images, number of ports, power consumption and many more. The knowledge base can include multi-vendor and cross-vendor relationships among components, such as associating specific headsets with specific phones.

The data model extends to services, software defined implementations, cloud and any solution that is offered. Migration paths can be modeled to support land and expand strategies.

Changing the Sales Motion with AI

Rather than just using automation to speed the existing linear IT sales process, AI operating on big data can make fundamental changes to the sales motion itself, such as influencing sales behavior early to focus on business outcomes and profitability.

AI enables a more holistic, dynamic approach that informs the sales motion or process end-to-end, from discovering existing infrastructure to solution design to ordering and provisioning.

AI also has a unique opportunity to enable and streamline management of the IT solution sales business across the entire sales lifecycle.

AI and Big Data: More Than Dashboards

AI and big data are not just about dashboards, analytics, and process enablement. The real value comes from applying AI to big data in order to identify and execute business actions—to define what the selling motion or process should be. The selling motion is the action of the sales process: getting the right solutions at the right price into the right hands at the right time.

Selling complex IT solutions can be a long and complex process. Changing that process to be insightful, fast, and simple while focusing on customer benefits and seller profitability is the real opportunity and value of data- and algorithm-driven AI. Here are some examples:

Maximize service-attach rates

Many solution providers have experienced declining professional services profitability, due to low attach rates, quoting vendor services and discounting.

How can AI and big data help? They can help create a centrally managed catalog of professional services tasks and data that are always up-to-date and capable of being seamlessly distributed globally in real time to all users. Through AI, the professional services information is automatically associated with products and solutions.

Automating the service-attach to the quotes allows the designer to automatically include the tasks, resources required, and their costs, including travel and expenses and third-party costs.

Leading with services becomes the new norm and complete product and service quotes are delivered faster and more accurately, increasing margins and customer satisfaction.

Suggest alternate parts based on business needs

Similarly, by applying AI algorithms to product information, alternate products can be automatically suggested during the design process, influencing seller behavior early in the process. The alternates may, for example offer, higher profitability, help reduce excess inventory, or adhere to a company best practice such as leading with Power over Ethernet (PoE)-based solutions.

As a result, the sellers’ behavior is influenced in the most profitable directions for their company as early in the process as possible.