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Sales process engineering
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 | This article possibly contains original research. (April 2016) |
Sales process engineering is the systematic design of sales processes done in order to make sales more effective and efficient.[1]
It can be applied in functions including sales, marketing, and customer service.[1]
History
[edit]As early as 1900–1915, advocates of scientific management, such as Frederick Winslow Taylor and Harlow Stafford Person, recognized that their ideas could be applied not only to manual labour and skilled trades but also to management, professions, and sales. Person promoted an early form of sales process engineering. At the time, postwar senses of the terms sales process engineering and sales engineering did not yet exist; Person called his efforts "sales engineering".[2]
Corporations the 1920s through 1960s sought to apply analysis and synthesis to improve business functions. After the publication of the paper "If Japan Can... Why Can't We?", the 1980s and 1990s saw the emergence of a variety of approaches, such as business process reengineering, Total Quality Management, Six Sigma, and Lean Manufacturing.
James Cortada was one of IBM's management consultants on market-driven quality. His book TQM for Sales and Marketing Management[3] was the first attempt to explain the theory of TQM in a sales and marketing context. Todd Youngblood, another ex-IBMer, in his book The Dolphin and the Cow (2004)[4] emphasized "three core principles": continuous improvement of the sales process, metrics to quantitatively judge the rate and degree of improvement, and a well-defined sales process.[4] Meanwhile, another executive from IBM, Daniel Stowell, had participated in IBM's project known as the "Alternate Channels Marketing Test." The idea was to incorporate direct response marketing techniques to accomplish the job of direct salespeople, and the initiative was quite successful.[5]
Paul Selden's "Sales Process Engineering, A Personal Workshop"[6] was a further attempt to demonstrate the applicability of the theory and tools of quality management to the sales function.
Rationale
[edit]The sales decision process is a formalized sales process companies use to manage the decision process behind a sale. SDP "is a defined series of steps you follow as you guide prospects from initial contact to purchase."[7]
Reasons for having a well-thought-out sales process include seller and buyer risk management, standardized customer interaction during sales, and scalable revenue generation. Approaching the subject from a "process" point of view offers an opportunity to use design and improvement tools from other disciplines and process-oriented industries.[8]
Relationship to other methodologies
[edit]Sales process engineering is distinct from, yet related to, several other business improvement and sales methodologies. Its primary distinction is a focus on designing and improving the overall, repeatable system of selling, rather than focusing on individual skills or techniques.[9]
Business process improvement
[edit]Sales process engineering applies the principles of business process re-engineering and quality management, historically used in operations and manufacturing, directly to the sales function.[10]
- Six Sigma: Like Six Sigma, sales process engineering aims to reduce process variability and defects to create more predictable outcomes. While Six Sigma identifies and eliminates defects in manufacturing to improve product quality, sales process engineering identifies and eliminates inefficient activities or failure points in the sales cycle to improve forecast accuracy and conversion rates.[11]
- Total quality management: The methodology shares philosophical roots with TQM, which advocates for continuous improvement and customer focus across all of an organization's functions. Sales process engineering can be seen as a formal application of TQM principles to the specific domain of sales.[12]
Sales techniques
[edit]Sales process engineering is distinguished from sales techniques or methodologies that guide a salesperson's behavior during customer interactions. If sales techniques are about how an individual salesperson sells, sales process engineering is about designing the framework in which they sell.
For example, methodologies like solution selling or consultative selling focus on training salespeople to act as advisors who diagnose customer needs and recommend solutions.[13] These are skill-based approaches that exist within the larger, structured framework defined by sales process engineering. An engineered sales process would define the stages, criteria, and activities required (e.g., "Needs Assessment Stage"), while the consultative selling technique would be the method the salesperson uses to execute that stage effectively.[10]
See also
[edit]References
[edit]- ^ a b Selden 1997, p. 23.
- ^ Dawson 2005.
- ^ Cortada, James (1993). TQM for Sales and Marketing Management. McGraw-Hill. ISBN 0-07-023752-2.
- ^ a b Youngblood 2004.
- ^ Stowell, Daniel (1997). Sales, Marketing, and Continuous Improvement. Jossey-Bass. pp. X. ISBN 0-7879-0857-6.
- ^ Selden 1997.
- ^ Marketing [m.o.] Strategic Marketing Process eBook. Moderandi Inc., 2009
- ^ William H. McNeese and Robert A. Klein (1991). Statistical Methods For The Process Industries. Milwaukee, WI: ASQC Quality Press. ISBN 0-8247-8524-X.
- ^ Johnston, Mark W.; Marshall, Greg W. (2016). Sales Force Management: Leadership, Innovation, Technology. Routledge. p. 52. ISBN 978-1-317-38522-7.
Sales process focuses on the various stages of the sales cycle, while sales methodology is a philosophy of selling that guides the behaviors and tactics used during those stages.
{{cite book}}: Check|isbn=value: checksum (help) - ^ a b Selden 1997, p. 23.
- ^ Webb, Michael J. (2006). Sales and Marketing the Six Sigma Way. Prentice Hall Professional. pp. 45–47. ISBN 978-0-13-186082-5.
{{cite book}}: Check|isbn=value: checksum (help) - ^ Agnihotri, Rajan; Rapp, Adam; Andzulis, James "Mick"; Gabler, Colin B. (2014). "The role of the sales force in the service-dominant logic". The Marketing Review. 14 (3): 237–257. doi:10.1362/146934714X14024778816723.
This movement of TQM in sales led to a new way of managing sales organizations that involved a process-orientation...
- ^ Bosworth, Michael T.; Holland, John R. (2004). CustomerCentric Selling. McGraw-Hill. p. 15. ISBN 978-0-07-142545-6.
{{cite book}}: Check|isbn=value: checksum (help)
Bibliography
[edit]- Dawson, Michael (2005), The Consumer Trap: Big Business Marketing in American Life, Urbana, Illinois, USA: University of Illinois Press, ISBN 0-252-07264-2.
- Selden, Paul H. (1997), Sales Process Engineering: A Personal Workshop, Milwaukee, Wisconsin, USA: ASQ Quality Press, p. 23, ISBN 0-87389-418-9.
- Youngblood, Todd (2004), The Dolphin And The Cow: How To Sell More Faster With Sales Process Engineering, YPS Group.
- Kreindler, Phil (2016), Customerized Selling®: Learn How Customers Want You To Sell, Infoteam Sales Process Consulting AG, ISBN 978-3-033-05471-4.
Sales process engineering
View on Grokipediafrom Grokipedia
Sales process engineering is the systematic application of industrial engineering, quality management, and Theory of Constraints principles to transform the sales function from a traditional, autonomous activity into a measurable, manageable, and scalable process focused on maximizing the flow of sales opportunities.[1] This approach emphasizes standardizing procedures, dividing labor among specialized roles, and centralizing scheduling to eliminate waste, reduce cycle times, and increase throughput—defined as revenue minus totally variable costs—while improving customer service and management control.[1] Originating in the mid-1990s through the work of Paul H. Selden, it adapts manufacturing process improvement techniques to sales environments, particularly in business-to-business contexts, to address inefficiencies like uneven workloads, low activity levels among salespeople, delays in quote generation and internal approval processes, and slow lead response times. These delays often cause sales teams to lose deals to competitors, as buyers in competitive markets expect rapid responses and may lose interest, choose more agile alternatives, or award the business to the first responsive vendor.[2]
Research highlights the critical importance of speed in sales processes: responding to a lead within the first 5 minutes increases the probability of qualifying the lead by 21 times compared to waiting 30 minutes, and approximately 50% of sales go to the vendor that responds first.[3]
Key components of sales process engineering include identifying critical variables such as appointment volume, opportunity queuing via an indexing formula (Relative Value × Probability × (1 + Appointments Pending) + Overdue Days), and performance metrics tied to business development rather than closing rates.[1] Unlike conventional sales management, which often relies on individual commissions and qualification gates, this methodology promotes team-based structures where salespeople focus primarily on high-value interactions like appointments, supported by coordinators for administrative tasks.[1] Benefits include scalable growth, with reported increases in throughput of $850 to $2,000 per appointment slot, and reduced variability in sales outcomes by synchronizing activities across the pipeline.[1]
In practice, sales process engineering involves a step-by-step methodology: standardizing core sales activities, implementing division of labor, introducing centralized scheduling, and continuously monitoring flow to prioritize high-potential opportunities.[1] It has been applied in industries requiring complex sales cycles, such as manufacturing and services, to align sales efforts with broader organizational goals like cost reduction and revenue optimization.[2] As sales environments evolve with digital tools, this framework provides a foundation for integrating technologies to further enhance process efficiency without compromising relationship-building aspects of selling.[4]
The initial stage involves defining and standardizing the key activities in the sales process, such as lead generation, appointments, needs assessment, and closing. This ensures consistency across all iterations, eliminating variability from ad-hoc practices and allowing for measurable improvements in cycle times and efficiency. Standardization draws from quality management techniques to create repeatable procedures tailored to business-to-business sales cycles.[1] Stage 2: Implementing Division of Labor
Next, labor is divided among specialized roles to optimize efficiency and reduce waste. Salespeople focus primarily on high-value interactions like business-development appointments, while coordinators handle administrative tasks, promotional teams manage opportunity generation, and technical specialists address solution design. This specialization, inspired by manufacturing principles, aims for salespeople to conduct approximately 4 appointments per day or 20 per week, enhancing focus and throughput.[1] Stage 3: Introducing Centralized Scheduling
Centralized scheduling is established using a coordinator and supporting software to manage appointment slots and opportunity queuing. A buffer of about 10 forward-booked days is maintained to balance workloads and prioritize high-potential opportunities via an indexing formula: Relative Value × Probability × (1 + Appointments Pending) + Overdue Days. This eliminates uneven workloads and ensures steady flow through the pipeline.[1] Stage 4: Continuous Monitoring and Refinement
Ongoing monitoring tracks performance metrics, such as throughput per appointment slot (reported at $850 to $2,000) and forward-booked days, using tools like statistical process control to identify bottlenecks and refine the process. Iterative adjustments based on data ensure sustained scalability and alignment with organizational goals like revenue optimization.[1]
Overview
Definition and Scope
Sales process engineering is the systematic application of engineering and quality management principles to the design, analysis, and optimization of sales activities, treating sales as a measurable and scalable production process rather than an ad-hoc endeavor.[1] This approach draws from methodologies like the Theory of Constraints and statistical process control to maximize the flow of sales opportunities through consistent, data-driven workflows.[5] Pioneered in the late 1990s, it emphasizes transforming unpredictable sales efforts into repeatable operations that align with organizational goals for efficiency and revenue growth.[2] The scope of sales process engineering encompasses the end-to-end workflow of sales, from lead generation and qualification to opportunity development and deal closure, while excluding unstructured or improvisational tactics that lack standardization.[1] It focuses on B2B environments where sales cycles are complex and involve multiple stakeholders, applying process-oriented techniques to reduce variability and bottlenecks without altering the underlying product or market strategy.[5] This delineation positions sales process engineering within broader business process reengineering, but it is distinctly tailored to revenue-generating functions, prioritizing throughput over isolated transactional improvements. Core components include process mapping to visualize and document sales stages, standardization to ensure uniform execution across teams, and continuous improvement cycles that use performance data for iterative refinements.[1] Process mapping identifies key steps and decision points, enabling the detection of inefficiencies, while standardization enforces protocols like appointment scheduling to maintain consistency.[5] Continuous improvement, often informed by control charts and variation analysis, fosters ongoing optimization to sustain high performance levels.[5] Sales process engineering differs from general sales engineering, which refers to a professional role providing technical expertise and demonstrations to support product sales in complex markets.[6] Whereas sales engineers focus on product-specific knowledge and customer demonstrations during transactions, sales process engineering targets the overarching structure and flow of the sales operation itself, emphasizing systemic enhancements over individual technical support.[1]Objectives and Rationale
Sales process engineering aims to establish a structured, repeatable framework that reduces sales cycle time by streamlining workflows and eliminating non-value-adding activities, thereby enabling faster progression from lead qualification to deal closure. This includes minimizing delays in lead response, quote generation, and internal approval processes to prevent lost deals in competitive markets where rapid responses are critical for capturing buyer interest. It also seeks to increase win rates through data-driven optimization of buyer interactions and quality gates, ensuring higher conversion efficiency at each stage. Additional objectives include minimizing variability in sales outcomes by standardizing methodologies across teams, which promotes consistency and predictability, and aligning sales activities closely with customer needs via targeted qualification and solution design.[1] The rationale for sales process engineering stems from the inefficiencies inherent in traditional sales approaches, which often rely on individual rep intuition and ad-hoc methods, leading to inconsistent methodologies that result in 10-20% revenue loss due to unpredictable results. For instance, salespeople in conventional setups spend only about one-third of their time on actual selling, with the remaining two-thirds consumed by non-selling tasks like administration and prospecting, severely hampering productivity. This pre-industrial style of sales management fosters bottlenecks, such as multitasking that limits business-development activity to as few as 20 appointments per week for a team of 10, underscoring the need for a systematic overhaul.[7][8][9] In competitive environments, these inefficiencies are compounded by slow lead response times and bureaucratic delays in quote generation and approvals, which extend sales cycles and cause buyers to lose interest or select more agile competitors. Statistics demonstrate the impact: responding to a lead within the first 5 minutes increases the probability of qualifying the lead by 21 times compared to waiting 30 minutes, and approximately 50% of sales go to the vendor that responds first. Manual and bureaucratic processes exacerbate these delays, reducing opportunity throughput and win rates by allowing competitors to close deals first.[10][11] Economically, sales process engineering drives cost savings by reallocating resources through division of labor— for example, reducing payroll by 18-29% in restructured teams while doubling or tripling appointment volumes— and fosters revenue growth via predictable scaling that maximizes opportunity throughput without proportional expense increases. It aligns with broader business process reengineering principles by transforming the sales function from a fragmented, artisanal operation into an industrialized process, incorporating standardization, centralized coordination, and measurable flow to achieve dramatic performance gains.[9][1]Historical Development
Origins
Sales process engineering originated in the late 1990s as an application of quality management principles to the sales function, building on earlier foundations in scientific management and industrial engineering. Paul H. Selden introduced the concept in his 1997 book Sales Process Engineering: A Personal Workshop, which adapted tools from quality improvement, such as process mapping and statistical control, to standardize and optimize sales activities.[2] This work was further elaborated in his 1998 article "Sales Process Engineering: An Emerging Quality Application" published in Quality Progress, positioning sales as a measurable process amenable to systematic engineering, similar to manufacturing.[12] The approach drew inspiration from 20th-century developments, including Frederick Winslow Taylor's scientific management principles from the early 1900s, which emphasized workflow optimization, and W. Edwards Deming's Plan-Do-Study-Act (PDSA) cycle developed in the 1940s–1950s for continuous improvement and reducing variability. Earlier efforts, such as Charles Wilson Hoyt's 1912 Scientific Sales Management and Elmer Wheeler's 1937 empirical testing of sales techniques in Tested Sentences That Sell, laid groundwork by treating sales as analyzable operations, though without the integrated engineering framework of SPE. Post-World War II operations research and quantitative models for sales allocation in the 1950s also influenced the field's evolution toward data-driven methods.[13][14][15][16]Key Milestones and Evolution
The late 1990s and early 2000s saw sales process engineering evolve through integration with emerging technologies and methodologies. The rise of sales force automation (SFA) tools in the 1980s and customer relationship management (CRM) systems, such as Siebel Systems founded in 1993 and Salesforce launched in 1999, provided foundational data-tracking capabilities that enabled the practical implementation of SPE principles like process visibility and metrics.[17][18] A significant advancement occurred in the early 2000s with Justin Roff-Marsh's development of a Theory of Constraints (TOC)-based approach to SPE. Through his consultancy Ballistix and 2009 whitepaper "Sales Process Engineering," Roff-Marsh emphasized maximizing sales throughput by addressing bottlenecks, division of labor, and centralized scheduling, transforming sales into a scalable industrial process. This was detailed in his 2014 book The Machine: A Radical Approach to the Design of the Sales Function.[1][19] From the 2010s onward, SPE has incorporated agile methodologies, promoting iterative sales processes with feedback loops to adapt to customer needs and market dynamics. Concurrently, advanced CRM analytics have supported real-time optimization, with metrics like sales velocity—calculated as (number of opportunities × average deal value × win rate) / sales cycle length—becoming essential for measuring and engineering throughput. Empirical studies have demonstrated CRM's role in enhancing SPE behaviors, such as opportunity management.[20][21][22]Core Principles
Systematic Engineering Approach
Sales process engineering adopts a systematic engineering mindset by applying scientific and mathematical principles to the design and refinement of sales workflows, treating sales as a controllable process rather than an unpredictable art form.[23] This approach, pioneered by Paul H. Selden, emphasizes empirical analysis to identify inefficiencies, such as bottlenecks in customer interactions, and uses data-driven tools to optimize outcomes like revenue generation.[2] At its core, sales process engineering employs systems thinking to view the sales function as an interconnected system of stages, including prospecting, qualifying leads, and closing deals, where each phase produces outputs that serve as inputs for the next.[23] This perspective reveals dependencies and feedback mechanisms, such as how poor lead qualification affects closing efficiency, enabling engineers to model the entire sales pipeline as a unified entity rather than isolated activities.[24] By mapping these interconnections, practitioners can anticipate systemic impacts, ensuring that improvements in one area, like prospecting accuracy, propagate benefits throughout the process. The methodology incorporates an iterative design cycle, adapting the Plan-Do-Check-Act (PDCA) framework—originally developed by W. Edwards Deming for quality improvement—to sales contexts through repeated cycles of planning process changes, implementing them, measuring results, and acting on insights for refinement.[25] In practice, this involves testing variations in sales tactics, such as alternative qualification criteria, and using feedback loops from real-time data to iteratively enhance process reliability and adaptability.[26] This continuous refinement fosters resilience against market shifts, with PDCA's origins in manufacturing quality control providing a proven foundation for sales applications.[27] Standardization techniques form a cornerstone, involving the creation of defined roles, scripted interactions, and decision trees to minimize variability and human error across sales teams.[23] For instance, operational definitions for stages like lead qualification establish uniform criteria, such as specific buyer signals, allowing consistent execution regardless of individual salesperson styles.[26] These tools, including standardized workflows documented in flowcharts, promote repeatability and scalability, reducing training time and enabling rapid onboarding while preserving essential flexibility for unique deals.[24] A holistic view integrates cross-functional elements, ensuring seamless handoffs between sales and supporting areas like marketing for lead generation or operations for fulfillment.[23] This approach aligns the sales system with broader organizational goals, such as incorporating marketing's customer insights into sales scripts to enhance trust-building, thereby creating a cohesive value delivery chain that sustains long-term customer relationships.[26] By addressing these interdependencies, sales process engineering transforms fragmented efforts into a synchronized operation that amplifies overall business performance.Metrics and Performance Measurement
In sales process engineering, metrics serve as quantitative tools to assess the efficiency and effectiveness of engineered sales processes, with a focus on maximizing opportunity flow and throughput rather than traditional closing rates. These metrics emphasize business development activities, providing actionable insights that align with the systematic design principles of sales engineering. By tracking process-specific indicators, teams can refine workflows to increase scalable revenue while reducing waste.[1] Key metrics in sales process engineering include throughput per appointment slot consumed, which measures revenue minus variable costs generated per scheduled salesperson interaction, targeting increases of $850 to $2,000 per slot. Appointment volume is a leading indicator, with targets of 4 appointments per day or 20 per week to ensure consistent activity levels. Forward-booked days track the buffer of scheduled appointments managed by coordinators, aiming to maintain full utilization without overload. Opportunity queuing uses an indexing formula to prioritize high-potential leads: where is expected throughput, is the probability of success based on milestones, Appointments Pending estimates required slots, and Overdue Days adds urgency for delayed opportunities. This formula enables dynamic prioritization to optimize flow through the pipeline.[1] Performance measurement in sales process engineering adapts quality tools like statistical process control to monitor variability in sales activities, focusing on leading indicators such as promotional coordinator pending-appointment days and technical team activity cycle times. These are collected via centralized systems to detect bottlenecks, such as low activity levels, and support continuous improvement. For context, while general B2B sales cycles average approximately 84 days as of 2025, SPE aims to reduce effective cycle times through flow optimization.[2][28]Methodology
Stages of Implementation
The implementation of sales process engineering follows a structured methodology focused on transforming sales into a scalable process by applying industrial engineering principles. This approach, developed by Paul H. Selden, emphasizes maximizing the flow of sales opportunities through standardization and specialization to increase throughput—defined as revenue minus totally variable costs.[1] Stage 1: Standardizing Core Sales ActivitiesThe initial stage involves defining and standardizing the key activities in the sales process, such as lead generation, appointments, needs assessment, and closing. This ensures consistency across all iterations, eliminating variability from ad-hoc practices and allowing for measurable improvements in cycle times and efficiency. Standardization draws from quality management techniques to create repeatable procedures tailored to business-to-business sales cycles.[1] Stage 2: Implementing Division of Labor
Next, labor is divided among specialized roles to optimize efficiency and reduce waste. Salespeople focus primarily on high-value interactions like business-development appointments, while coordinators handle administrative tasks, promotional teams manage opportunity generation, and technical specialists address solution design. This specialization, inspired by manufacturing principles, aims for salespeople to conduct approximately 4 appointments per day or 20 per week, enhancing focus and throughput.[1] Stage 3: Introducing Centralized Scheduling
Centralized scheduling is established using a coordinator and supporting software to manage appointment slots and opportunity queuing. A buffer of about 10 forward-booked days is maintained to balance workloads and prioritize high-potential opportunities via an indexing formula: Relative Value × Probability × (1 + Appointments Pending) + Overdue Days. This eliminates uneven workloads and ensures steady flow through the pipeline.[1] Stage 4: Continuous Monitoring and Refinement
Ongoing monitoring tracks performance metrics, such as throughput per appointment slot (reported at $850 to $2,000) and forward-booked days, using tools like statistical process control to identify bottlenecks and refine the process. Iterative adjustments based on data ensure sustained scalability and alignment with organizational goals like revenue optimization.[1]