7 Reasons Why AI Advisors will Replace Traditional Configure Price Quote (CPQ)

 

7 Reasons Why AI Advisors will Replace Traditional CPQ

Source: World Bank

“We're presently in the midst of a third intellectual revolution. The first came with Newton: the planets obey physical laws. The second came with Darwin: biology obeys genetic laws. In today’s third revolution, were coming to realize that even minds and societies emerge from interacting laws that can be regarded as computations. Everything is a computation.”

― Rudy Rucker

At the same time we are hearing about AI’s rapid advancements, we also hear the horror stories of failed Configure-Price-Quote (CPQ) implementations with excessive cost overruns, heavy customization, never ending content maintenance and an inability to communicate well with third-party software.

CPQ is suffering the similar fate of CRM and ERP implementations as many are finding burdensome costs and low adoption rates:

  • Upfront Costs:  For every $1 in software they spend $3 in customization of the software. 
  • Maintenance Costs:  To get value from CPQ systems, you must provide consistent feeding and nurturing.   Often companies spend more on content maintenance of the products and rules than on software and customization!
  • Inability to Scale:  User based Pricing Models prevent scaling out to channel partners and customers.
  • Extremely Low Adoption Rates:  Sales reps and customers refuse to use the CPQ sites and prefer to have valuable engineers assist them.  Just like many CRM implementations management find adoption rates as low as 20-30% for many projects.

 

Signs you may need to replace your CPQ with newer AI Based Technology

In today’s rapidly changing technology market, newer AI based technologies are replacing older applications based approaches. Specifically, AI Based Knowledge as a Service offerings such as Digital Knowledge Advisors or Knowledge Bots can do the work of CPQ and more.


As head of your sales or marketing organization, are you beginning to ask, “Do we need CPQ or do we need something else?”  Questions to ask yourself include:

  • Are you seeing low employee and customer engagement/adoption?
  • Do you see that the CPQ rules do not get updated regularly?
  • Is it too expensive to scale out CPQ to your channel partners and customers?
  • Does your CPQ system let you select products but falls short of advising buyers on optimal solutions?
  • Are your CPQ systems too difficult for everyone but high-end engineering talent to use – draining resources from developing new accounts?

If you answered yes to any of these questions then this is the time to rethink about your old CPQ application.

7 Reasons AI Based Advisors will Replace Traditional CPQ

Newer AI based advisors go beyond product configuration and instead are intelligent co-workers that provide advice on solutions – making classic CPQ look limited. If you have deployed conventional CPQ, it may have many drawbacks for your employees, your customers and your business. Have you ever thought about the reasons for these limitations?  If not, then the reasons below are common reasons CPQ will not cut it in today’s digital universe and is not able to meet your customer experience requirements.

  1. Back Office Led Instead of Customer Experience Led:  Today the customer must be in the center of everything.  According to research by Gartner, 89 percent of companies believe that customer experience represents their “primary basis for competition” in 2016.  Given this fact it is amazing how many companies put Back Office Organizations (Sales Operations Engineering, IT and Manufacturing) instead of Customer Experience Leaders in charge of CPQ!
    • Types of BACKOFFICE LED CPQ
      • Engineering and ERP and Manufacturing Led - Insure that products can be manufactured
      • CRM and Sales Operations Led – Insure that orders can be entered into CRM correctly
    • Types of CUSTOMER EXPERIENCE LED Knowledge Advisement
      • Help Buyers solve problems
      • Automatically build solutions instead of forcing users to “Select Products”
      • Help Generate Leads and Track Lead Conversion
     

    CPQ built by back office organizations is typically concerned with internal operational efficiency and not with customer experience.Although they may be suitable for internal manufacturing or Sales operations users, when these CPQ “tools” are provided to sales, marketing, channel partners and customers they often fail badly as they burden and confuse the user.

    CALL TO ACTION: Companies must keep conventional CPQ where it belongs - in the back office and create new Customer Experience Led Advisors using an AI based Digital Knowledge Advisor.These new advisors can 1) insure higher adoption by users and 2) hand off solutions to conventional tool sets that interface to sales operations and manufacturing.

  2. Product Focused versus Value Chain Focused:  Nothing is sold alone.   But old fashioned CPQ only addresses the only the products a vendor sells instead of advising the customer on blending and building a complete solution with value chain of surrounding 3rd party products (hardware, software, services, leasing). 
     

    CALL TO ACTION:  Vendors must position their products as part of a solution.  Modern vendors will showcase how their products can blend with other components of a solution to meet customers technical and business objectives.  Presenting a vendor’s product in the context of a complete solution incorporating other complementary third-party products and services is key to presenting a vendor’s value proposition.  AI based Recommendation Engines and Advisors can address this problem but conventional CPQ cannot.

  3. Simple CPQ Product Selectors are not Enough: Companies must help solve real business problems faced by customers.  Companies must empower its customers to make smarter decisions.  CPQ is usually built to allow users to “select a product” and compatible options but what it overlooks is solving a customer’s business problem:
    • Helping a customer determine what is the best or optimal solution based on their business requirements (eg Total Cost of Ownership)
    • Addressing each type of customer journey for purchase – New Purchase, Add-On Purchase, Renewal, Refresh.
    • Addressing each type of customer journey by application.
     

    CALL TO ACTION:  Vendors must help buyers tradeoff Total Cost of Ownership and performance for each type of customer journey.  Journeys include the purchase type but also the application.  This is where AI Knowledge Based Advisors can do everything that CPQ can and more – the buyer is provided a list of products for purchase but more importantly they can be assured that this list of products comprise the OPTIMAL solution meeting both their technical and business requirements.  When we work with vendors make sure that AI advisors are not “one size fits all”.  For one data center vendor we built unique advisors for different customer applications such as storage versus compute intensive applications and saw significant usage for each customer journey. 

  4. Eco-Systems versus an Island: CPQ does not address 70% of the administrative work involved in the sales process.  Often it contributes to this burden.  CPQ assumes that a “Bill of Material” (BOM) transferred to a CRM or ERP is the finish line.  What is ignored is that a single BOM requires numerous annotations from internal personnel, systems and external partners (Vendors, Distribution).   Think of the difference between classic ERP accounting ledgers which are only updated by internal personnel and Block Chain where ledgers are updated by numerous external parties.  More modern, open and intelligent software is needed to allow all these parties contribute to the pricing and BOM annotations at once.
     

    CALL TO ACTION:  Companies must be “easy to do business with” and account for all the steps needed to complete a purchase!  These steps grow exponentially when there is an ecosystem of manufacturers and a multi-tier sales channel.  We have seen users build BOM’s with an average of 6-12 vendors.  This can require over 24 requests for deal registration, special pricing, part numbers, availability.  AI Knowledge Based systems will identify and make these requests for the user and weave them into the BOM - removing the work for the user.

  5. Bespoke versus One Size Fits all: CPQ is like Henry Ford – you can have any color you want as long it is black.  CPQ typically has numerous technical limitations which prevent vendors from offering customized versions (branding, views, additional products services, pricing, routing) to their channel partners and customers.  

    To be relevant in today’s market vendors must put customers in control.Brands must focus on one-to-one engagement, connecting at the right time — with the right message — the right people — across any and all channels.To do this their Knowledge must be personalized for each sales partner using multiple channels (email, web, mobile, chat bots).

    CALL TO ACTION: Vendors must let each major user and partner customize the AI advisors for their own purposes.This goes beyond simple branding and toward custom navigation, views of SKUS adding customized pricing, part numbers and inventory and finally decision based routing and analytics.Newer conversational interfaces like chat bots must be leveraged to advise customers before-during and after configuration.

  6. Barriers to Scaling: Classic CPQ licensing offers per user or per transaction pricing models that make it prohibitively expensive to scale through multi-tier channels:
    • Uncertainty in budgeting
    • High up-front costs
    • Difficulty to manage in high turnover sales and partner organizations
     

    CALL TO ACTION: Unlike classic CPQ which is focused on internal processes, newer AI Knowledge Based Platforms offer unlimited users and unlimited usage.This permits sales and marketing executives to scale a broader knowledge set rapidly throughout a world-wide sales organization and partner channel at a fraction of the time and expense of manual methods.

  7. Manual Coding versus Codeless: CPQ based on coding for customization and rules is inflexible and does not support today’s agile business requirements.

    CPQ like traditional CRM and ERP requires several months, dozens of people and often hundreds of thousands of dollars or more to implement.With AI based Knowledge Work platforms companies can build advisors that can perform CPQ and more in a fraction of the time with a fraction of the staff and for a fraction of the cost.Moreover, companies gain agility as changes are data driven and no coding is required.

    CALL TO ACTION: Business Executives must ignore “traditional” advice from IT and system integrators who say that the only way to build an enterprise application is to spend several months and potentially millions of dollars.Today business owners can create their own applications WITHOUT coding and the expense associated with it. Newer AI based solutions provide the lowest risk due to their flexibility, rapid deployment and lowest TCO.

SUMMARY – AI Based Digital Knowledge Advisors can address CPQ and More

Many companies haven’t been able to keep up with the pace of technological innovation or customer expectations. These same companies face two choices:

  1. Try to repackage and repurpose outdated “Software Hardcoded CPQ Tools”
  2. Embrace a new approach to advising customers which is “codeless, AI based and Data Driven” that can augment existing back office CPQ systems.

The benefits of an AI based Digital Knowledge Advisor are significant:

  • AI based Knowledge Advisors offer the Optimal Customer Experience and maximizes adoption– Traditional CPQ was focused on internal process efficiencies instead of customer experience and ease of doing business.
  • AI rules based systems can advise users on TCO and ROI resulting in dramatic improvements in Solutions Selling – CPQ systems focus on a single product or vendor and are not built to blend decision rules incorporating third party products and services.
  • AI Scales Knowledge and Expertise Easily – CPQ allows users to select products but does not advise users on optimal solutions in terms of business problems.  This is left to a manual handoff to product experts.
  • AI can make decisions and initiate independent requests to gather information removing 70% of the administrative work involved in sales giving you a chance to double your sales productivity – CPQ is not a decision support system or a system capable of taking action leaving numerous administrative tasks to sales.  
  • AI based systems can be personalized in numerous ways beyond basic branding – CPQ tends to be one size fits all.
  • AI Lowers TCO and removes barriers to scaling – A codeless AI based approach customizes itself based on data and eliminates needless spending of $3 in software customization for every $1 spent on the system and often removes barriers of Per User or Per Transaction pricing.
  • AI rules based deployment offers Agility and Lowest Risk – Unlike CPQ there is no coding so deployment is fast and changes can be made rapidly.
 

What is the difference between Traditional CPQ and AI based Knowledge Advisors and Bots?

AI Based Digital Knowledge Advisors can do CPQ and so much more.  Letting a company address process, solutions, scale, Customer Experience (CEX) in ways conventional CPQ never could.

 

Traditional CPQ

AI Based Digital Knowledge Advisor

Technology

Application Software

AI Based Advisor or

Knowledge Bot

Design Methodology

Design for Internal Experience and Process

Design for Customer Experience

Software Platform

Often CRM or ERP Dependent

100% Independent of CRM or ERP while 100% compatible with CRM or ERP

Rules Engine

Coding

Codeless – No software changes required to address new product areas.

Configure

Selection based interface

Product Based

Knowledge Bot for Digital Advisement (what is best or optimal)

Solution Based

Price

Single Price List

Full Pricing Engine supporting multiple Price lists per region per partner privilege or per contract.

Quote

Human Acts of Heroics over email and phone to ecosystem of partners to determine availability, discounts, incentives

Knowledge Bot for Digital Administration does 70% of rules based repetitive work for making and managing partner requests for discounts, product information, promotions, etc

Proposals and Contracts

Generation and Management of Export Documentation

Generation and Management of Export Documentation

Blending 3rdParty Offerings

100% Silo

Lego Block Like Rules Stack allows seamless blending of Knowledge Rules Blocks into a single experience.

Perfect for 3rd Party Products

Future Proof with AI Technology

No

Knowledge Bots can talk to Other Knowledge Bots or External Chat Bots.

Organizational Ownership

Back Office: IT, Engineering Manufacturing

Front Office: Customer Experience, Marketing

Adoption

Low

High

 

Have I forgotten anything? Please let me know at lswanson@exaltsolutions.com.