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Posts tagged ‘CPQ’

Five Ways AI Can Help Create New Smart Manufacturing Startups

smart manufacturing, AI, machine learning

AI and machine learning’s potential to drive greater visibility, control, and insight across shop floors while monitoring machines and processes in real-time continue to attract venture capital. $62 billion is now invested in 5,396 startups concentrating on the intersection of AI, machine learning, manufacturing, and Industry 4.0, according to Crunchbase.

PwC’s broader tech sector analysis shows a 30% year-over-year growth in funding rounds that reached $293.2 billion in 2021. Smart manufacturing startups are financed by seed rounds at 52%, followed by early-stage venture funding at 33%. The median last funding amount was $1.6 million, with the average being $9.93 million.

 Abundant AI startup opportunities in smart manufacturing and industry 4.0 

According to Gartner, “The underlying concept of Industry 4.0 is to connect embedded systems and smart production facilities to generate a digital convergence between industry, business, and internal functions and processes.” As a result, Industry 4.0 is predicted to grow from $84.59 billion in 2020 to $334.18 billion by 2028. AI and machine learning adoption in manufacturing are growing in five core fields: smart production, products and services improvements, business operations and management, supply chain, and business model decision-making. Deloitte’s survey on AI adoption in manufacturing found that 93% of companies believe AI will be a key technology to drive growth and innovation.

Machine intelligence (MI) is one of the primary catalysts driving increased venture capital investment in smart manufacturing. Startup CEOs and their customers want AI and machine learning models based on actual data, and machine intelligence is helping to make that happen. An article by McKinsey & Company provides valuable insights into market gaps for new ventures. McKinsey’s compelling data point is that those leading companies using MI achieve 3X to 4X the impact of their peers. However, 92% of leaders also have a process to track incomplete or inaccurate data – which is another market gap startups need to fill.

AI, Industry 4, smart manufacturing

McKinsey and the Massachusetts Institute of Technology (MIT) collaborated on a survey to identify machine intelligence leaders’ KPI gains relative to their peers. They found that leaders achieve efficiency, cost, revenue, service, and time-to-market advantages. Source: Toward smart production: Machine intelligence in business operations, McKinsey & Company. February 1, 2022.

Based on the uplift MI creates for new smart manufacturing startup funding and the pervasive need manufacturers have to improve visibility & control across shop floors, startups have many potential opportunities. The following are five that AI and machine learning is helping to create:

  1. AI-enabled Configure, Price, and Quote (CPQ) systems that can factor in supply chain volatility on product costs are needed. Several startups are already using AI and machine learning in CPQ workflows, and they compete with the largest enterprise software providers in the industry, including Salesforce, SAP, Microsoft, and others. However, no one has taken on the challenge of using AI to factor in how supply chain volatility changes standard and actual costs in real-time. For example, knowing the impact of pricing changes based on an allocation, how does that impact standard costs per unit on each order? Right now, an analyst needs to spend time doing that. AI and machine learning could take on that task so analysts could get to the larger, more complex, and costly supply chain problems impacting CPQ close rates and revenue.
  2. Using AI-enabled real-time data capture techniques to identify anomalies in throughput as an indicator of machine health. The aggregated data manufacturing operations produced every day holds clues regarding each machine’s health on the shop floor. Automated data capture can identify scrap rates, yield rates and track actual costs. However, none of them can analyze the slight variations in process flow product outputs to warn of possible machine or supply chain issues. Each process manufacturing machine runs at its cadence or speed, and having an AI-based sensor system track and analyze why speeds are off could save thousands of dollars in maintenance costs and keep the line running. In addition, adding insight and intelligence to the machine’s real-time data feeds frees quality engineers to concentrate on more complex problems.
  3. Industrial Internet of Things (IIoT) and edge computing data can be used for fine-tuning finite scheduling in real-time. Finite scheduling is part of the broader manufacturing systems organizations rely on to optimize shop floor schedules, machinery, and staff scheduling. It can be either manually intensive or automated to provide operators with valuable insights. A potential smart manufacturing opportunity is a finite scheduler that relies on AI and machine learning to keep schedules on track and make trade-offs to ensure resources are used efficiently. Finite schedulers also need greater accuracy in factoring in frequent changes to delivery dates. AI and machine learning could drive greater on-time delivery performance when integrated across all the shop floors a manufacturer relies on.
  4. Automated visual inspections and quality analysis to improve yield rates and reduce scrap. Using visual sensors to capture data in real-time and then analyze them for anomalies is in its nascent stages of deployment and growth. However, this is an area where captured data sets can provide machine learning algorithms with enough accuracy to identify potential quality problems on products before they leave the factory. Convolutional neural networks are an effective machine learning technique for identifying patterns and anomalies in images. They’re perfect for the use case of streamlining visual inspection and in-line quality checks in discrete, batch, and process manufacturing.
  5. Coordinated robotics (Cobots) to handle assemble-to-order product assembly. The latest cobots can be programmed to stay in sync with each other and perform pick, pack, ship, and place materials in warehouses. What’s needed are advanced cobots that can handle simple product assembly at a more competitive cost as manufacturers continue to face chronic labor shortages and often run a shift with less than half the teams they need.

Talent remains an area of need 

Manufacturers’ CEOs and COOs say that recruiting and retaining enough talent to run all the production shifts they need is the most persistent issue. In addition, those manufacturers located in remote regions of the world are turning to robotics to fulfill orders, which opens up opportunities for integrating AI and machine learning to enable cobots to complete assemble-to-order tasks. The unknown impact of how fast supply chain conditions change needs work from startups, too, especially in tracking actual cost performance. These are just a few opportunities for startups looking to apply AI and machine learnings’ innate strengths to solve complex supply chain, manufacturing, quality management, and compliance challenges.

How Services CPQ Helps Close Revenue Gaps

How Services CPQ Helps Close Revenue Gaps

Bottom Line: Professional services (PS) organizations need to close the gaps in their CPQ selling strategies to win more deals, capture more revenue and protect margins from ongoing price pressure.

Why Services CPQ Is Too Slow Today

When PS organizations compete in sales cycles, the first competitor to have a complete quote with accurate pricing, schedules, and an engagement plan will often win. However, getting a complete quote out fast is a major challenge for most PS organizations today. Many PS organizations manually create their quotes by taking into account a broad base of factors that include the following: talent profiles of employees and the market value of their skills; utilization rates; direct and indirect engagement costs; typical gross margins by type of engagement; and, competitive pricing. The average PS organization takes six weeks to deliver a quote or proposal. John Ragsdale’s excellent recent article Automating Services Quote-to-Cash: Emergence of CPQ for Services provides useful insights into what needs to change for PS quoting and selling to increase its velocity.

Getting Services CPQ Right Is Hard

Gaps that drain revenue and margin grow wider when PS organizations attempt to use product-centric CPQ platforms to sell services. Too often, PS organizations attempt to wedge their quoting, pricing, and revenue management into a product-based CPQ system – and get mediocre results at best. Earlier in my career, I led a product management team that defined, created, and launched a quoting system for professional services inside a large IT organization. The most valuable lessons learned from that experience include the following:

  • PS bundles only work if they have simple, solid direct cost structures. Adding a synthetic SKU that represents a PS bundle only works for the most simple, automated PS engagements. Think of those PS engagements with long-standing direct cost structures that are simple, clear and easy to implement. Attempting to group PS bundles can easily lead to quoting mistakes that drain margin when a product-centric CPQ system is used for PS.
  • The greater the differences in PS revenue management, the more the need for a new CPQ platform. Many PS organizations are making a mistake by attempting to make product-centric CPQ platforms work for their unique costing, pricing, and selling needs. My team and I learned that the more a PS revenue model is unique and one-of-a-kind, the more it requires a unique CPQ platform.
  • Getting product-based CPQ rules and constraint logic right is hard in PS. Our teams’ biggest challenge in recycling IT’s CPQ app for PS was how difficult it was to get the rules-based engine to work for the wide variety of variables in a common service engagement. Rules created for transaction velocity needed to be reworked for greater variety. PS engagements didn’t follow a common logic structure like a product, making the constraint logic code only somewhat usable.
  • Only launch after CRM and Revenue Management integration is complete. Our team was handed a project that had languished in IT for nearly a year because PS selling teams wouldn’t use it. The problem was that the quoting module ran batch updates to a series of databases to get customer records and fetch the latest price tables off of a mainframe. In addition, CPQ wasn’t connected in real-time to CRM or Revenue Management.

Closing Long-Standing Services CPQ Gaps

The more a Services CPQ app can close the gaps between CRM, PSA, Revenue Management, and CPQ apps and their workflows, the more effective it will be stopping margin and revenue leakage. Having APIs that share data in real-time between CRM, PSA, and Revenue Management within each quote creation session has the potential to save thousands of hours a year. FinancialForce’s recently announced Services CPQ shows how a platform-based integration strategy works. The following graphic shows how revenue potential increases as a Services CPQ’s systems become more integrated.

How Services CPQ Helps Close Revenue Gaps

FinancialForce’s approach to taking on the challenge of providing an enterprise-grade Services CPQ is noteworthy for several reasons, including the following:

  • Real-time visibility and control of Services CPQ Effectiveness. Having Services CPQ, PSA and Revenue Management on the same Salesforce platform provides the visibility and control PS sales managers need to track quoting effectiveness by program, geography, customer segment, and rep. The more real-time the data integration across these systems the greater the potential for revenue growth in existing accounts and winning new ones.
  • Changing professional services quotes in real-time without impacting sales cycles is possible. Due to the integrated design of Services CPQ, one change made anywhere on a quote will replicate through the entire system and change all related factors immediately.
  • Getting in control of professional services engagement dates and utilization rates by associates helps reduce time-to-market and assures better time-to-customer performance. Keeping track of the myriad of factors that influence a services quote using a manually-based process is too slow for how quickly engagements are decided. Instead, having a single, unified data model that can track effectiveness and provide updates on how they impact engagement project plans is needed to excel at selling with Services CPQ. Adopting an agile CPQ strategy that relies on an integration thread to unify all systems is the secret to scaling and selling more with an agile approach to services CPQ.
  • Pricing needs to be one of the core strengths in an integrated Services CPQ platform. Realizing how a customers’ requested changes to a professional services engagement will impact costs and margins gives PS teams with an integrated system a formidable pricing advantage. FinancialForce’s approach to solving the Services CPQ challenge shows the potential to take on this challenge and provide its PS customers with the insights they need to upsell engagements – and not lose margin doing it.
  • A must-have for any Services CPQ platform is support for channel partner collaboration and team quoting. For any Services CPQ to scale up and deliver its full potential value, there needs to be support for customizing partner selling experiences while providing for team selling and quoting. FinancialForce solves this by relying on the Salesforce platform. By closing the gaps between the systems Services CPQ relies on, the channel selling teams and partners gain greater flexibility in defining customized products.

Conclusion

Services CPQ needs to scale out on a platform to achieve its full potential by providing the analytical insights to track engagement lifecycles and customer lifetime value by engagement. FinancialForce has proven they can do this in their Spring 2021 release. Taking on the most challenging aspects of a Services CPQ architecture starts by providing insights and guidance on how best to optimize the mix of associates and their utilization and billing rates, locations of each engagement, margin threshold levels, and the expected duration of each engagement. Additionally, the world’s leading professional services organizations could use an automated Services CPQ solution as many of them don’t rely on enough data, letting revenue leakage happen without knowing it.

 

What’s New In Gartner’s Hype Cycle For CRM, 2019

  • Worldwide enterprise application software revenue totaled more than $193.6B in 2018, a 12.5% increase from 2017. CRM made up nearly 25% of the entire enterprise software revenue market.
  • 72.9% of CRM spending was on software as a service (SaaS) in 2018, which is expected to grow to 75% of total CRM software spending in 2019.
  • Worldwide spending on customer experience and relationship management (CRM) software grew 15.6%, from $41.7B in 2017 to $48.2B in 2018, and is projected to reach $55.2B in 2019.
  • Salesforce dominated the worldwide CRM market with a 19.5% market share in 2018, over double its nearest rival, SAP, at 8.3% share, according to Gartner’s market share estimates.
  • CRM revenue in 2018 is comprised of software and services revenue from Customer Service and Support (35.7%), Sales (25.9%), Marketing (25.4%), and Digital Commerce (13%). These four categories together comprise the customer experience and relationship management market, according to Gartner.

New technologies are proliferating across the CRM landscape, driven by the need every business has to understand, communicate, serve, and strengthen customer relationships. Gartner’s decision to create its first-ever Hype Cycle for CRM Sales Technology, 2019, reflects the widening spectrum of new technologies being introduced to improve sales effectiveness while improving operational efficiency. Gartner’s Hype Cycle for CRM Sales Technology, 2019 is based on an update to their Hype Cycle for CRM Sales, 2018.  Gartner’s definition of Hype Cycles includes five phases of a technology’s lifecycle and is explained here.  The Gartner Hype Cycle for CRM, 2019, is shown below:

Details Of What’s New In Gartner’s Hype Cycle For CRM, 2019

  • Four new technologies are on the Hype Cycle for CRM, reflecting enterprises’ need for greater integration of diverse systems and the demand for more predictive and prescriptive analytics-based insights. The four technologies include the following:
    • Blockchain for lead generation. Gartner sees the potential for blockchain to provide a decentralized peer-to-peer network model that supports exchanging data to the highest bidders using smart contracts. Gartner predicts this approach reduces or in some cases eliminates the need for a centralized authority such as a data intelligence solution. It also allows for a new ecosystem of managing, sharing and monetizing data for revenue-generating purposes.
    • Knowledge graphs for sales. The ability to build an AI-enabled knowledge model of real-world entities and their relationships to one another, expressed in a data schema, shows potential to increase sales effectiveness. Gartner predicts this emerging technology provides organizations with the ability to create data-driven sales organizations using graphs arranged in a network of nodes rather than in tables of rows and columns. The significance is the ability to correlate sales activities and benchmark against performance metrics in a more digestible and insightful way, which is often too complex for human analysis.
    • Digital adoption solutions. Gartner sees potential in this technology to improve the adoption of multiple tools across a selling and marketing organization. Digital adoption solutions enable sellers to onboard more quickly and improve productivity.
    • Relationship intelligence. By relying on machine learning, sales organizations can map out their universe of network connections, both internal and external, to identify potential avenues of engagement with any prospect or client. Gartner sees this as useful in its ability to provide warm introductions or even referrals for revenue-generating activities while reducing sales cycles.
  • Gartner predicts the following five technologies will deliver the most significant transformational benefits to selling organizations in 2 years or less. The five most transformation technologies in the near term are the following according to Gartner:
    • CPQ Application Suites
    • Digital Content Management for Sales
    • Lead Management
    • Partner Relationship Management (PRM)
    • Price Optimization and Management for B2B
  • The following CRM technologies have gained wide usage and adoption in the last year, as reflected by their position on this year’s Hype Cycle. Data intelligence solutions for sales, CPQ application suites, digital content management for sales, and sales KPI analytics are among the most adopted mature technologies on the hype cycle today.
  • Visual configurators have moved at a much faster pace to mainstream adoption along the Hype Cycle this year. Gartner credits visual configurators’ rapid adoption rate to how the majority of them are now embedded or easily integrated with configure, price, quote (CPQ) applications, or in digital commerce sites. State-of-the-art visual configurator are enabling engineering, production, and sales to become real-time collaborators in creating new products. For additional insights into visual configurators, please see How To Make Complex CPQ Selling Simple With Visual Configurators published earlier this week.
  • Algorithmic guided selling is now listed as obsolete. Gartner has re-assigned this technology as it’s now an embedded core capability in many CPQ and sales force automation (SFA) applications. By doing this, Gartner is saying it is doubtful algorithmic guided selling applications will be sold stand-alone in the future.
  • Social for sales and predictive B2B marketing analytics are off the CRM Hype Cycle. Gartner has chosen to merge them into the data intelligence solutions for sales market. Social for sales is more of a process, not a technology market. The majority of social for sales-based strategies are executed over social networks that have the audience and scale to make them succeed, with LinkedIn being an example. Gartner believes the predictive B2B marketing analytics vendor landscape has shrunk and is not a viable market long term, as they have seen inquiries regarding market share in this area steadily drop in this area since 2016.
  • Gartner is seeing two main drivers of investment and innovation in CRM in 2019 and beyond. The first is digital optimization or a process and program of using digital technology to maximize existing operating processes and business models. The second is predictive/prescriptive-enabled technology or technology using capabilities such as machine learning that provides predictive signals and prescriptive “next best action” recommendations. Please see their research note, 4 Key Insights from the Gartner Hype Cycle for CRM Sales Technology, 2019, for additional details.

Sources:

4 Key Insights From the Gartner Hype Cycle for CRM Sales Technology, 2019, published October 2, 2019

Hype Cycle for CRM Sales Technology 2019, July 10, 2019 (Client access required)

How To Make Complex CPQ Selling Simple With Visual Configurators

Bottom Line: Realizing visual configurators’ full potential starts by enabling engineering, production, and sales to become real-time collaborators in creating new products.

2D, 3D, Augmented Reality (AR), Mixed Reality (MR), and Virtual Reality (VR) visual configurators are proliferating across the Configure, Price, and Quote (CPQ) landscape today. Manufacturing marketing teams say they are the most effective lead generation technology they have, responsible for 40%+ growth in Marketing Qualified Leads (MQLs) this year alone. Sales VPs and Chief Revenue Officers (CROs) are seeing from 9% to 30% improvements in deal close rates and over 90% increases in quote accuracy. Visual configurators deliver shock-and-awe to prospects and drive more leads and deals.

Product Models Need To Scale, Driving Greater Collaboration

The good test of any product configurator is whether it can scale from assemble-to-order (ATO) to Engineer-To-Order (ETO) while enabling real-time collaboration between engineering, production, and sales. A given products’ many attributes and options defined by engineering in their PLM system need to be consistent with manufacturing’s work instructions and Bill of Materials (BOM) in their ERP system. And the visual configurator sales & marketing is using needs to reflect, in real-time, what engineering defined in PLM and what manufacturing’s ERP system can build. Product models serve as the master data that enables real-time collaboration between engineering, manufacturing, and sales.

Visual configurators need to push beyond the veneer of delivering shock-and-awe and enable real-time collaboration between PLM, ERP, and CRM & CPQ systems to achieve their full potential. Visual configuration providers need to pursue the goal of enabling engineering, manufacturing, and sales to be collaborators in creating accurate products and challenge themselves to deliver the following:

  • Improve sales performance while increasing margin per deal by providing only the options that are the most buildable at the lowest cost.
  • Eliminate disconnects between what engineering designed and what manufacturing can produce leads to more sales at higher gross margins.
  • Close product configuration gaps and improving fulfillment speed and product quality, creating greater customer loyalty and follow-on sales.
  • Automatically propagate product and design changes across all functional areas to accelerate new products to market while improving product quality.
  • Real-time fine-tuning of new product features to the model level that specific customers want becomes possible when engineering, manufacturing, and sales are collaborating in real-time.
  • Update work instructions and BOMs in real-time based on changes customers make in product visualizations.
  • Improve the balance of revenue across configurable products to sell higher-margin models based on real-time collaboration between PLM, ERP, CRM, and CPQ systems.
  • See in real-time how changes in product design, Bill of Materials (BOM), and delivery dates impact the financial performance of a manufacturer.

Predicting Visual Configuration’s Future

Shortening cycle times from product concept to completed product is the secret to succeeding with visual configuration. And when each manufacturing cycle time has its cadence or speed depending on how little or much a customer wants a product customized, visual configurators need to flex and deliver what customers want when.

Companies defining the future of visual configuration today include CDSDERWID, and SAP Visual Enterprise. These three companies are defining the future of visual configuration by enabling real-time integration between PLM, ERP, CRM, and CPQ systems.  I recently spoke with John Major, CEO of CDS to get his insights into what’s driving visual configuration’s success today.  “What we’re seeing in the marketplace now are two things. One is the clients want to understand how our visual configuration solution is going to fit into their change management as it’s rooted in PLM, because to any manufacturer, PLM reigns supreme,” he said. He continued, “The second is about staffing. When you’re a manufacturing company, and you buy a visual configurator toolkit that requires you to create your app, a few things happen. You need to staff up a software team to now run that toolkit and write development. So your long-term cost is fairly significant versus a company that can deliver an entire solution at scale.” 

CDS is partnering with eLogic, who is regarded as the leading system integration partner in CPQ and product configuration and is considered a global leader in delivering business solutions for manufacturers across SAP configuration technologies and Microsoft Dynamics 365, Power Platform & Azure. Together they are delivering next-generation visual configuration solutions for their shared clients. Examples of the work they are doing are shown below:

  • Real-time model updates keep engineering, manufacturing, and sales in sync. When customers are designing a new product in a CPQ session, the model is updated in real-time and saved, so engineering, manufacturing, and sales can see how their changes affect the product. An example of this is shown below:

  • When the product is configured “to scale,” 2D proposal drawings are automatically generated, and the product model is updated in real-time, making augmented reality visualizations possible. 3D models are also made available in a variety of CAD formats. Additionally, an Augmented Reality model is created that can be placed in any virtual environment. What’s noteworthy is that while the model’s appearance is changing, all relevant changes to the work instructions and BOM are happening in real-time using the SAP Visual Enterprise

  • When product models are the catalyst enabling real-time collaboration between engineering, manufacturing, and sales, selling into the aftermarket becomes profitable. Aftermarket selling has a complexity all its own. Taking on the challenge of shortening cycle times from product concept to completed products in the market is what’s needed today. The example below shows a piece of equipment selected in CPQ, then rotated, zoomed in, and exploded to see the internal components. Internal parts can now be selected, quoted, ordered and delivered for replacement.

Conclusion

Visual configurators are capable of so much more than they are delivering today. It’s time to graduate beyond the shock-and-awe stage, which has been very successful in driving leads, generating MQLs, and closing deals. It’s time to get down to the hard work of making all those impressive models buildable at scale and profitable. And that comes by doubling down efforts at shortening cycle times from product concept to completed product. That’s the true north of this market and the secret to succeeding. Getting engineering, manufacturing, and sales collaborating using product models as a single source of truth is the best place to start.

How To Improve Your CPQ Pricing Strategies

Manufacturers can get more than their fair share of channel sales and margins by improving price management for every dealer, distributor, and reseller they sell-through. It’s possible to expand earnings by 50% on slight increases in volume when pricing is consistent channel-wide. McKinsey’s latest research on the topic, Pricing: Distributors’ Most Powerful Value-Creation Lever, shows how the highest performing distributors use pricing to create value. For manufacturers competing for more sales through distributors, they share with competitors, improving their channel partners’ margins is the single best strategy to win more sales and long-term loyalty.

  • A 1% price increase yields a 22% increase in Earnings before Interest & Taxes (EBITDA) margins for distribution-based businesses.
  • It would take a 7.5% reduction in fixed costs to achieve the same 22% increase in EBITDA that a 1% increase in pricing achieves.
  • A distribution-based business would need to increase volume by 5.9% while holding operating expenses flat to achieve the same impact as a 1% price increase.
  • Channel partners are more loyal to margin than manufacturers, which is why price management needs urgent attention on CPQ roadmaps.

CPQ Strategies Need To Deliver More Margin Back To The Channel

The typical manufacturer who has over $100M in sales generates 40% or more of their sales through indirect channels. The channel partners they recruit and sell through are also reselling 12 other competitive products on average. Which factors most influence a distributor or channel partner’s decision to steer a sale to one manufacturer versus another?  The following are the steps manufacturers can take now to improve price management and drive more channel sales:

  • Upgrade the pricing module in CPQ to deliver more than configurable price lists to include pricing waterfalls, automated approval levels for pricing requests, and discounts. Distributors drive more deals to manufacturers whose CPQ systems are designed to give them greater freedom in tailoring pricing to every customer and selling situation they have. Automating approval levels using machine learning-based supervised algorithms that serve as pricing guardrails on every quote a channel partner creates is proving effective at delivering a 1% price increase which drives margin back to resellers. The more a manufacturer can make margins flow back to its channel partners, the faster the channel partners can grow. The following graphic from McKinsey’s latest pricing research illustrates why.

  • Distributors will drive more deals to manufacturers who automate pricing approvals, guiding their sales teams to the largest and most profitable deals first. One of the best ways to compete and win more deals through channel partners is to achieve the ambitious goal of delivering pricing approval within seconds on a 24/7 basis. Pricing needs to provide guardrails that guide channel sales reps to the largest, most profitable, and most ready-to-buy new and aftermarket sales opportunities. Manufacturers capturing more channel sales are relying on machine learning-based pricing systems that optimize price approvals while recommending only those new and aftermarket deals that will drive a 1% or greater price increase. Machine learning is making solid contributions to automating pricing approvals. It’s proving most effective when it is balanced with the flexibility of responding to subjective competitive situations where pricing on specific products need discounts to win deals in aggregate. The following workflows from Deloitte explain how this is being accomplished today:

  • Helping distributors solve sales compensation problems by improving price management drives more deals in the short-term and keep distributors in business long-term. Distributors start out building their sales comp plans on volume and growth alone. The problem is comp plans reward revenue growth at the expense of profits. That’s making it harder every year for distributors to stay in business. Manufacturers delivering new pricing management and optimization apps in their CPQ platforms need to provide real-time guidance on margin potential by the deal, pricing waterfall logic that includes margins, contract pricing overrides for margins and more if they are going to help their distributors stay in business.

Conclusion – Pricing Is the Engine Powering CPQ’s Market Growth Today

Manufacturers who excel at growing indirect product and services revenue through channels realize that every one of their channel partners is more loyal to pricing and margins than any specific vendor they resell. Providing a CPQ application or platform they can personalize, and automate workflows is just the beginning. The bottom line is that manufacturers need to put more intensity into improving pricing today if they’re going to hold onto the distributors they have and attract new ones.

Pricing is the primary catalyst driving the CPQ market’s growth as well. According to Gartner, the CPQ grew 36% in 2017, reaching $1.084B with the majority of growth attributable to cloud-based solutions. It’s no wonder CPQ is considered one of the hottest CRM technologies for the foreseeable future, projected to grow at a 25% Compound Annual Growth Rate (CAGR) through 2020. Supervised machine learning algorithms capable of providing guardrails in real-time for every potential deal a reseller sales representative has is what’s needed to protect a distributor’s margins. Winning more deals with channel partners starts by respecting how vital margins are to their success and improving pricing management as part of a broader CPQ strategy that delivers results.

Sources:

Configure, Price, and Quote (CPQ) Capabilities: Why the right CPQ capability is key to transitioning to a flexible consumption model, 8 pp., PDF, no opt-in, Deloitte, 2019.

Pricing: Distributors’ Most Powerful Value-Creation Lever, McKinsey & Company, September 2019.

What Needs To Be On Your CPQ Channel Roadmap In 2019

Bottom Line:  Adding new features to your CPQ channel selling platform directly benefits your resellers and channel partners, driving greater revenue, channel loyalty, and expansion into new markets.

Personalization Is Key To CPQ Succeeding In Channels

Sustaining and strengthening relationships across all indirect selling channels succeeds when dealers, multi-tier distributors, resellers, intermediaries, and service providers each can personalize the CPQ applications and platforms they use. Larger dealers, distributors, and resellers are adept at personalizing CPQ selling portals by the various roles in their organization. Personalization combined with a highly intuitive, configurable interface improves CPQ applications’ ease of use, enabling channel partners to get more done. The more intuitive and easy a CPQ application is to use, the more channel partners rely on it to place orders. When distributors are representing, on average, 12 different manufacturers,  the one with the most intuitive, easily used CPQ system often gets the majority of sales.

Another aspect of personalization is defining levels of resellers. When many organizations first launch their CPQ channel selling strategies, one of the first requests they have is to organize all channel partners into performance categories. Differentiating channel partners on sales performance, customer satisfaction, and aftermarket revenue then gamifying how every one of them can move up a level is proving to be very effective at increasing channel sales. Competing with one another to be the top reseller for the manufacturing and service companies lifts an entire channel network to higher performance.

Every dealer, multi-tier distributor, reseller, intermediary, and service provider also has a unique way of selling that works best for their business. Another must-have feature on any CPQ channel roadmap is greater workflow flexibility to support increasingly complex, IoT- and AI-enabled configurable products. Smart, connected products are the future of manufacturing and channel sales. Capgemini estimates that the size of the connected products market will be $519B to $685B by 2020. Workflows like the one shown below of an internal sales rep using a multichannel CPQ system to order a customized product are due for a refresh to support even greater flexibility for more channels and greater product options.


Most Valuable Features For A CPQ Channel Roadmap In 2019

There’s a direct link between how effective a CPQ platform is across multi-tier distribution networks and the productivity of sales teams using them. 83% of sales teams are using CPQ apps today based on Accenture Interactive’s recent study, Empowering Your Sales Force: It’s Not Just Automation, It’s Personal (8 pp., PDF, no opt-in). There’s ample evidence that the more effective a CPQ platform is at equipping dealers, multi-tier distributors, resellers, intermediaries, and service providers, the greater the sales they achieve. The 2019 B2B Buyers Survey Report, by DemandGen in collaboration with DemandBase, found that B2B buyers are more likely to purchase from sales representatives who demonstrate a stronger knowledge of the solution area and the business landscape (65%) compared to competitors. B2B buyers also give high praise for sales teams who can provide quotes quickly and respond to their inquiries promptly (63%), in addition to providing higher-quality content (61%). Each of these benefits is derived from a CPQ platform that can scale across every phase of the selling lifecycle.

The following are the key features needed on CPQ channel roadmaps in 2019 to stay competitive and scale sales and revenue on pace with market growth:

  • Greater personalization for each type of partner portal supported by real-time integration to CRM and ERP systems, designed to scale for sales team turnover across multi-tier distribution networks. Channel partners’ sales teams tend to churn quickly, and it’s best to design in intuitive, easily configured portals by sales role to help new hires get up to speed fast. Channel sales associates are typically the fastest-churning area of any selling business. With greater personalization comes the need for greater integration to provide the data needed to enable partner portals to have a greater depth of functionality. The following graphic from Deloitte’s recent study, Configure, Price, and Quote (CPQ) Capabilities illustrates this point:

  • Support for multi-tier pricing, price management, price optimization, price enforcement, and special workflows, including Special Pricing Requests (SPR). Baseline CPQ platforms support price management and have successfully transitioned multi-tier distribution networks off of Microsoft Excel spreadsheets to a single pricing model that scales across all products and channels. Consider adopting advanced pricing logic to support SPRs so sales operations teams don’t have to do this process manually. In manufacturers who have transitioned from manual to automated SPR approvals, average deal sizes have increased over 60%, and productivity jumped over 76% according to a recent Gartner survey.
  • Augment advanced product configuration tools by making them more intuitive and easier to use to sell the more advanced products in your catalog. It’s time to push the boundaries of CPQ channel selling systems to sell more complex products and drive greater revenue and margins. Forward-thinking manufacturers are taking a virtual design and 3D-based design approach to accomplish this. Enabling channel partners to take larger orders for more complex products is paying off.
  • Upgrade guided selling strategies to be more than catalog-based selection systems, mining customer data using machine learning to see which products they have the greatest propensity to buy when. It’s time to migrate off of the guided selling systems that are selecting products from catalogs that may deliver the best gross margins or have a traditionally high attach rate with the product the customer is buying. Machine learning is making it possible to provide greater accuracy and precision to recommendations than ever before.
  • Improve the usability of sales promotions, rebates, and most importantly, Market Development Funds (MDF). It’s amazing how much time manufacturers are spending manually handling MDF claims today. It’s time to automate this area of the CPQ channel roadmap and save thousands of hours and dollars a year while enabling resellers to get reimbursed faster or get the funds they need to grow their businesses.
  • Contract management is a must-have for CPQ channel roadmaps today. Integrating a cloud-based contract management system into a CPQ platform is vital for taking one more step towards an end-to-end quote-to-cash workflow being in place. Real-time integration to contract management can save days of waiting for contract approvals, all leading to more closed deals and faster, more lucrative sales cycles.
  • Manufacturers can realize greater revenue potential through their channels by combining machine learning insights to find those aftermarket customers most ready to buy while accelerating sales closing cycles with CPQ. Manufacturers want to make sure they are getting their fair share of the aftermarket. Using a machine learning-based application, they can help their resellers increase average deal sizes by knowing which products and services to offer when. They’ll also know when to present upsell and cross-sell offers into an account at a specific point in time when they will be most likely to lead to additional sales, all based on machine learning-based insights. Combining machine learning-based insights to guide resellers to the most valuable and highest probability customer accounts ready to buy with an intuitive CPQ system increases sales efficiency leading to higher revenues.

Conclusion

Now that the solutions exist for resellers to simplify CPQ selling strategies, it’s up to each manufacturer to decide how competitive they want their channel partner roadmap to be. Any given manufacturer’s quoting and configuration tools today are competing with 11 others on average for a reseller’s time, it is clear that roadmaps need a refresh to stay competitive. Suggested options include offering greater personalization, multi-tier pricing and a more thorough approach to price management, advanced product configuration support, revamped guided selling strategies and improved usability of sales promotions, rebates, and Market Development Funds (MDF). Manufacturers need to prioritize each of these features relative to their product- and revenue-specific goals by channel. A fascinating company who has deep expertise in designing, implementing, and scaling analytics, service, sales, IoT, and CPQ solutions for manufacturers is eLogic. The company’s mission is to enable manufacturers to achieve the highest value customer engagement and product & service lifecycle performance. eLogic is regarded as the leading system integration partner in CPQ and product configuration and is considered a global leader in delivering business solutions for manufacturers across SAP configuration technologies and Microsoft Dynamics 365, Power Platform & Azure.

CPQ Needs To Scale And Support Smarter, More Connected Products

  • For smart, connected product strategies to succeed they require a product lifecycle view of configurations, best attained by integrating PLM, CAD, CRM, and ERP systems.
  • Capgemini estimates that the size of the connected products market will be $519B to $685B by 2020.
  • In 2018, $985B will be spent on IoT-enabled smart consumer devices, soaring to $1.49B in 2020, attaining a 23.1% compound annual growth rate (CAGR) according to Statista.
  • Industrial manufacturers will spend on average $121M a year on smart, connected products according to Statista.

Succeeding with a smart, connected product strategy is requiring manufacturers to accelerate their IoT & software development expertise faster than they expected. By 2020, 50% of manufacturers will generate the majority of their revenues from smart, connected products according to Capgemini’s recent study. Manufacturers see 2019 as the breakout year for smart, connected products and the new revenue opportunities they provide.

Industrial Internet of Things (IIoT) platforms has the potential of providing a single, unified data model across an entire manufacturing operation, giving manufacturers a single unified view of product configurations across their lifecycles. Producing smart, connected products at scale also requires a system capable of presenting a unified view of configurations in the linguistics each department can understand. Engineering, production, marketing, sales, and service all need a unique view of product configurations to keep producing new products. Leaders in this field include Configit and their Configuration Lifecycle Management approach to CPQ and product configuration.

Please see McKinsey’s article IIoT platforms: The technology stack as a value driver in industrial equipment and machinery which explores how the Industrial Internet of things (IIoT) is redefining industrial equipment and machinery manufacturing. The following graphic from the McKinsey explains why smart, connected product strategies are accelerating across all industries. Please click on the graphic to expand it for easier reading.

CPQ Needs To Scale Further To Sell Smart, Connected Products

Smart, connected products are redefining the principles of product design, manufacturing, sales, marketing, and service. CPQ systems need to grow beyond their current limitations by capitalizing on these new principles while scaling to support new business models that are services and subscription-based.

The following are the key areas where CPQ systems are innovating today, making progress towards enabling the custom configuration of smart, connected products:

  • For smart, connected product strategies to succeed they require a product lifecycle view of configurations, best attained by integrating PLM, CAD, CRM, and ERP systems. Smart, connected product strategies require real-time integration between front-end and back-end systems to optimize production performance. And they also require advanced visualization that provides prospects with an accurate, 3D-rendered view that can be accurately translated to a Bill of Materials (BOM) and into production. The following graphic is based on conversations with Configit customers, illustrating how they are combining PLM, CAD, CRM and ERP systems to support smart, connected products related to automotive manufacturing. Please click on the graphic to expand it for easier reading.

  • CPQ and product configuration systems need to reflect the products they’re specifying are part of a broader ecosystem, not stand-alone. The essence of smart, connected products is their contributions to broader, more complex networks and ecosystems. CPQ systems need to flex and support much greater system interoperability of products than they do today. Additional design principles include designing in connected service options, evergreen or long-term focus on the product-as-a-platform and designed in support for entirely new pricing models.
  • Smart, connected products need CPQ systems to reduce physical complexity while scaling device intelligence through cross-sells, up-sells and upgrades. Minimizing the physical options to allow for greater scale and support for device intelligence-based ones are needed in CPQ systems today. For many CPQ providers, that’s going to require different data models and taxonomies of product definitions. Smart, connected products will be modified after purchase as well, evolving to customers’ unique requirements.
  • After-sales service for smart, connected products will redefine pricing and profit models for the better in 2019, and CPQ needs to keep up to make it happen. Giving products the ability to send back their usage rates and patterns, reliability and performance data along with their current condition opens up lucrative pricing and services models. CPQ applications need to be able to provide quotes for remote diagnostics, price breaks on subscriptions for sharing data, product-as-a-service and subscription-based options for additional services. Many CPQ systems will need to be updated to support entirely new services-driven business models manufacturers are quickly adopting today.

Which CRM Applications Matter Most In 2018

 

According to recent research by Gartner,

  • Marketing analytics continues to be hot for marketing leaders, who now see it as a key business requirement and a source of competitive differentiation
  • Artificial intelligence (AI) and predictive technologies are of high interest across all four CRM functional areas, and mobile remains in the top 10 in marketing, sales and customer service.
  • It’s in customer service where AI is receiving the highest investments in real use cases rather than proofs of concept (POCs) and experimentation.
  • Sales and customer service are the functional areas where machine learning and deep neural network (DNN) technology is advancing rapidly.

These and many other fascinating insights are from Gartner’s What’s Hot in CRM Applications in 2018 by Ed Thompson, Adam Sarner, Tad Travis, Guneet Bharaj, Sandy Shen and Olive Huang, published on August 14, 2018. Gartner clients can access the study here  (10 pp., PDF, client access reqd.).

Gartner continually tracks and analyzes the areas their clients have the most interest in and relies on that data to complete their yearly analysis of CRM’s hottest areas. Inquiry topics initiated by clients are an excellent leading indicator of relative interest and potential demand for specific technology solutions. Gartner organizes CRM technologies into the four category areas of Marketing, Sales, Customer Service, and Digital Commerce.

The following graphic from the report illustrates the top CRM applications priorities in Marketing, Sales, Customer Service, and Digital Commerce.

Key insights from the study include the following:

  • Marketing analytics continues to be hot for marketing leaders, who now see it as a key business requirement and a source of competitive differentiation. In my opinion and based on discussions with CMOs, interest in marketing analytics is soaring as they are all looking to quantify their team’s contribution to lead generation, pipeline growth, and revenue. I see analytics- and data-driven clarity as the new normal. I believe that knowing how to quantify marketing contributions and performance requires CMOs and their teams to stay on top of the latest marketing, mobile marketing, and predictive customer analytics apps and technologies constantly. The metrics marketers choose today define who they will be tomorrow and in the future.
  • Artificial intelligence (AI) and predictive technologies are of high interest across all four CRM functional areas, and mobile remains in the top 10 in marketing, sales and customer service. It’s been my experience that AI and machine learning are revolutionizing selling by guiding sales cycles, optimizing pricing and enabling CPQ to define and deliver smart, connected products. I’m also seeing CMOs and their teams gain value from Salesforce Einstein and comparable intelligent agents that exemplify the future of AI-enabled selling. CMOs are saying that Einstein can scale across every phase of customer relationships. Based on my previous consulting in CPQ and pricing, it’s good to see decades-old core technologies underlying Price Optimization and Management are getting a much-needed refresh with state-of-the-art AI and machine learning algorithms, which is one of the factors driving their popularity today. Using Salesforce Einstein and comparable AI-powered apps I see sales teams get real-time guidance on the most profitable products to sell, the optimal price to charge, and which deal terms have the highest probability of closing deals. And across manufacturers on a global scale sales teams are now taking a strategic view of Configure, Price, Quote (CPQ) as encompassing integration to ERP, CRM, PLM, CAD and price optimization systems. I’ve seen global manufacturers take a strategic view of integration and grow far faster than competitors. In my opinion, CPQ is one of the core technologies forward-thinking manufacturers are relying on to launch their next generation of smart, connected products.
  • It’s in customer service where AI is receiving the highest investments in real use cases rather than proofs of concept (POCs) and experimentation. It’s fascinating to visit with CMOs and see the pilots and full production implementations of AI being used to streamline customer service. One CMO remarked how effective AI is at providing greater contextual intelligence and suggested recommendations to customers based on their previous buying and services histories. It’s interesting to watch how CMOs are attempting to integrate AI and its associated technologies including ChatBots to their contribution to Net Promoter Scores (NPS). Every senior management team running a marketing organization today has strong opinions on NPS. They all agree that greater insights gained from predictive analytics and AI will help to clarify the true value of NPS as it relates to Customer Lifetime Value (CLV) and other key metrics of customer profitability.
  • Sales and customer service are the functional areas where machine learning and deep neural network (DNN) technology is advancing rapidly.  It’s my observation that machine learning’s potential to revolutionize sales is still nascent with many high-growth use cases completely unexplored. In speaking with the Vice President of Sales for a medical products manufacturer recently, she said her biggest challenge is hiring sales representatives who will have longer than a 19-month tenure with the company, which is their average today.  Imagine, she said, knowing the ideal attributes and strengths of their top performers and using machine learning and AI to find the best possible new sales hires. She and I discussed the spectrum of companies taking on this challenge, with Eightfold being one of the leaders in applying AI and machine learning to talent management challenges.

Source: Gartner by Ed Thompson, Adam Sarner, Tad Travis, Guneet Bharaj,  Sandy Shen and Olive Huang, published on August 14, 2018.

Five Ways CPQ Is Revolutionizing Selling Today

CPQ, Salesforce CPQ, enosiX SAP to Salesforce Integration Configure-Price-Quote (CPQ) continues to be one of the hottest enterprise apps today, fueled by the relentless need all companies have to increase sales while delivering customized orders profitably and accurately. Here are a few of the many results CPQ strategies are delivering today:

  • Companies relying on CPQ are growing profit margins at a 57% greater rate year-over-year compared to non-adopters.
  • 89% improvement in turning Special Pricing Requests (SPRs) into sales by automating them using a cloud-based CPQ system.
  • 67% reduction in reworked orders at a leading specialty vehicle manufacturer due to quotes reflecting exactly what customers wanted to buy.
  • 23% improvement in upsell and cross-sell revenue by having the CPQ system intelligently recommend the optimal product or service that has the highest probability of purchase and best possible gross margin.
  • CPQ strategies excel when they are designed to reach challenging selling, pricing, revenue and operational performance goals versus automating existing selling workflows.

Another factor fueling CPQs’ rapid growth is how quickly results of a pilot can be measured and used for launching a successful company-wide launch.  Pilots often concentrate on quote creation time, quoting accuracy, sales cycle reduction, automating Special Pricing Requests (SPRs), up-sells and cross-sells, perfect order performance, margin improvements and best of all, winning new customers. These are the baseline metrics many companies use to measure their CPQ performance. Throughout 2017 these metrics across industries are accelerating. There is a revolution going on in selling today.

5 Ways CPQ Is Revolutionizing Selling Today

Cloud- and SaaS-based CPQ solutions are quicker to implement, easier to customize to customers’ requirements, and available 24/7 on any Internet-enabled device, anytime. Many are designed to integrate into Salesforce, further accelerating adoption seamlessly.  The following five factors are the primary catalysts revolutionizing selling today:

  1. Designing in excellent user experiences (UX) is the new normal for CPQ apps – CPQ vendors are competing with the quality of user experiences they deliver in 2017, moving beyond packing every feature possible into app releases. This is having a corresponding impact on adoption, increasing the number of sales representatives and entire teams who can get up and running fast with a new CPQ app. The net result is reduced sales cycles, growing pipelines, and more sales reps actively using CPQ apps to increase their selling effectiveness.
  2. Integrating with legacy CRM, ERP and pricing systems in real-time are using service-oriented frameworks gives sales teams what they need to close deals faster – Legacy CPQ systems in the past often had very precise field mappings to 3rd party legacy CRM, ERP and pricing systems. They were brittle and would break very easily, slowing down sales cycles and making sales reps resort to manually-based approaches from decades before. In 2017 there are service-oriented frameworks that make brittle, easily broken mappings thankfully an integration practice in the past. With a loosely coupled service framework, real-time integration between CRM and ERP systems can be quickly be implemented and sales teams can get out and close more deals. Leaders in the area include enosiX, who are enabling their customers’ sales forces to enter sales orders into SAP directly from Salesforce, saving valuable selling time and increasing order accuracy.
  3. Competing for deals using Artificial Intelligence (AI), machine learning and Intelligent Agents are force multipliers driving greater salesSalesforce’s Einstein is an example of the latest generation of AI applications that are enabling sales reps and teams to gain insights that weren’t available before. Combining customer data with these advanced predictive data analytics technologies yields insights into how selling strategies for different accounts can customize to specific prospect needs. Selling strategies are more effective and focused when AI, machine learning, and Intelligent Agents are designed in to guide quoting, pricing and product configuration in real-time.
  4. CPQ apps optimized for mobile devices are enabling sales reps to drastically reduce quote creation times, sales cycles and increase sales win rates – For many companies whose sales teams are in the field calling on accounts the majority of the time, mobile-based CPQ apps are how they get the majority of their work done. Salesforce’s Force.com is one of the leading platforms CPQ software companies are relying on to create mobile apps, further capitalizing on the already-established levels of familiarity sales teams have with the Salesforce platform.
  5. The vision many companies have of synchronizing multichannel and omnichannel selling as part of their CPQ strategies is now attainable – One of the greatest challenges of expanding sales channels is ensuring a consistently high-quality customer experience across each. With on-premise CPQ, CRM and ERP selling systems, this is very challenging as there are often multiple database systems supporting each. This is a breakout year for omnichannel selling as cloud-based CPQ systems and the platforms they are built on can securely scale across all selling channels a company chooses to launch. Being able to track which CPQ deals emanated from which marketing program, and which channels are the most effective in closing sales is now possible.

5 Ways Real-Time Mobile Apps Delight Customers And Streamline Manufacturing

  • 2017-mobile-apps-in-manufacturingProviding real-time responses 24/7 on any mobile device anywhere is the new normal in 2017.
  • 54% of B2B companies selling online report that their customers are using smartphones to research purchases, and 52% say that their customers are using smartphones to buy online
  • The majority of CEOs (86%) see mobility as essential to creating and sustaining a competitive advantage.
  • Industrial manufacturing CEOs prioritize mobility (73%), cybersecurity (72%) and data mining and analysis (70%) as their top three priorities for attaining competitive advantage.

PriceWaterhouse Coopers (PWC) annually surveys global CEOs to learn about their current and future priorities, plans and technology adoption trends. PwC’s 18th Annual Global CEO Survey (free, no opt-in) is based on interviews with 1,322 CEOs located in 77 countries. The survey provides valuable insights into the strategic direction enterprises are taking with technology investments.

The following graphic from the report illustrates the strategic importance CEOs are placing on mobile technologies:

Competing On Accuracy, Speed And Responsiveness Is How You Win Today

CEOs at the world’s leading industrial manufacturing companies share a common focus on how to continually improve the accuracy, speed, and responsiveness of their companies using mobile technologies. A recent study by research firm Forrester shows that 54% of B2B companies selling online report that their customers are using smartphones to research purchases, and 52% say that their customers are using smartphones to buy online.

Being ready to respond with complete quotes, pricing, order status, delivery dates, updated service information on a 24/7 basis on any device anywhere is the new normal. Amazon’s ability to take orders, process, ship and deliver them in some cases all within 24 hours is driving up expectations in B2B selling too.  And a key part of making sure you can compete in 2017 and beyond is by having an integrated mobile apps strategy that provides customers the information they need when they need it.

The following are five ways real-time mobile apps delight customers and streamline manufacturing:

  1. Enabling configure, price and quoting (CPQ) apps to provide real-time updates on any device, anywhere wins more deals and keeps customers sold on doing business with you. According to a recent Gartner study, the competitor in any deal who is the first to produce a quality quote will win the deal 70% of the time. Given the competitive intensity around delivering the first, highest quality quote possible, having mobile apps that are based on real-time Salesforce and SAP integration is a must-have. From the very first interaction with any new prospect to closing a sale, having mobile apps that deliver real-time information gained through CRM and ERP integration is key.
  1. Being able to answer “When will my order ship?” anytime, anywhere on any device, at any time is what it takes to win and keep customers today. It’s time to challenge the outdated assumption that customers only want to speak with you when your legacy systems are available. The best manufacturers are modeling Amazon today, providing real-time alerts on when orders are being prepared to ship, providing e-mail and text alerts and delivery times and shipping information. Mobile apps need to be used to extend past the boundaries of legacy systems that don’t meet the minimum expectations of customers today. The CEO of an electrical machine manufacturer told me that once he was able to launch mobile apps for his customers, there was a 76% reduction in order status calls to the enterprise sales teams and 13% increase in sales the first six months these apps were available.
  1. Getting in control of quality and being able to manage customer expectations and relationships to positive outcomes with accurate data. Quality, compliance, inbound inspection and quality assurance are applications that often are isolated from CRM, ERP and customer service systems. The lack of integration between these systems wastes valuable time in getting back to customers on how best to solve quality problems and address questions they may have. That’s why it’s so important to have compliance, product quality, and quality assurance data delivered on mobile apps in a context the customer can use. Having this data available over mobile apps, enabled for customers’ use via Salesforce integration, reduces problem escalations and provides greater accuracy. Enabling quality data on mobile apps also helps to unify operations and production, giving everyone on the shop floor visibility into quality levels of order and long-term, over product lines being produced. Making data and reporting available company-wide often requires integration to SAP ERP and legacy systems, with companies including enosiX emerging as market leaders.
  1. Reducing Field Service call cancellations and delays by accurately communicating parts and staffing requirements shows respect for your customers. There is nothing more frustrating from a customer’s perspective than waiting for a field service technician to show up, only to find they don’t have the necessary parts or are told the problem was completely different than the one that needs to be solved. By enabling Salesforce integration with field service apps and providing customers with real-time alerts to their mobile devices via an app, field service calls can lead to solved problems and higher customer satisfaction faster.
  1. Providing customers with real-time updates via mobile apps on delivery dates driven by supply chain conditions helps in managing expectations while giving production planners the information they need to meet demand. Manufacturers whose business models rely on rapid inventory turns, tight production schedules, and thin margins are the leading early adopters of mobile technologies for logistics and supply chain coordination. Enabling mobile apps to provide the latest updates on Available-To-Promise (ATP), Capable-To-Promise (CTP) requires SAP integration across the Salesforce platform. Being able to provide updates on how suppliers are potentially impacting their delivery dates on orders is invaluable in managing expectations over the long-term.
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