Coolfront, an innovative mobile application for HVAC, plumbing, and electrical contractors, was facing a significant challenge in managing an overwhelming number of inbound leads. Despite their successful marketing efforts, the small sales team was unable to keep up with the volume of leads, resulting in many potential opportunities falling through the cracks. The sales team was overburdened and unable to effectively follow up with all the leads, leading to a backlog. The challenge was to find a way to sort through the leads, identify the most promising ones, and ensure timely follow-up without overstretching the already strained sales and marketing team.

Stivers Ford Lincoln, a family-owned dealership in Montgomery, Alabama, was facing a significant challenge in improving sales and lead qualification. The dealership was struggling to boost sales during a period when consumers were cutting back on big-ticket purchases like cars. With a small inventory compared to mega-dealers, Stivers needed to work smarter, pursue leads more efficiently, and deliver a customer experience that would convert one-time buyers into lifetime customers. However, with an increasing number of car shoppers requesting quotes online, the Business Development Center (BDC) at Stivers found it challenging to manually capture and nurture these leads until the prospect was ready to speak with a salesperson. The old model of simply adding more people to the BDC was not working, leading to many dead deals.

CAKE, a Sysco company, was faced with the challenge of reaching out to over 425,000 Sysco customers using a 'cold emailing' approach. This task was equivalent to the work of 10 sales development representatives. The challenge was further compounded when CAKE was acquired by Sysco, a $48 billion food services leader. The acquisition necessitated a shift in CAKE's sales strategy from an outside sales approach to a purely inside sales model. This meant that CAKE had to introduce its high-tech offerings to restaurant operators virtually, while emphasizing its relationship with Sysco. The company also had to nurture relationships with potential customers and secure the best time for a CAKE sales representative to contact the customer.

IBM, a 105-year-old company, has been traditionally focused on in-person selling of technology services and products. However, with the rise of digital channels, the company faced the challenge of integrating digital marketing into its established sales-centric model. This was particularly difficult due to IBM's long-established infrastructure, which was dated and burdened with custom enhancements. The company needed to transition to a more modern, global management platform while avoiding custom enhancements. Additionally, IBM needed to change the mindset of its marketers to view the customer’s journey as something much broader and more flexible. Another major challenge was the low rate of phone-ready leads being brought in through digital channels.

Extreme Networks, a leading provider of software-driven networking solutions, faced a significant challenge in fully leveraging their marketing investments. Despite generating a large number of sales leads through tradeshows, webinars, and other events, the company struggled to systematically follow up with each lead. This was due to the sheer volume of leads and the lack of resources to engage with each one individually. The inability to effectively follow up on these leads meant that potential sales opportunities were being missed, and the return on marketing investments was not as high as it could be. The challenge was to find a way to engage with every single lead, nurture their interest, and convert them into sales opportunities.

Boch Automotive Dealerships, a prominent automotive dealer in New England, was grappling with the challenge of striking the right balance in their follow-up process. They aimed to convert quality leads into satisfied customers without overwhelming them with excessive follow-ups. As the company grew, this challenge became increasingly complex. They needed to ensure that their responses were prompt, thorough, and human-like, while also assessing the quality of incoming leads. Another significant issue was the ineffective email deliverability. Despite investing considerable time in crafting impressive emails, they were not reaching the customers as they were being filtered into spam.

Snohomish YMCA, a part of the larger Y franchise, was facing a significant challenge in re-engaging former and inactive members. In the fitness industry, clubs typically lose 50% of their memberships annually. For Snohomish YMCA, this translated to a loss of 10,000 members per year. Additionally, the club had over 12,000 untouched leads from various programs such as camp, child care, personal training, youth sports, and other a la carte programs. The club's small staff of two was unable to effectively follow up on these leads, resulting in a large pool of potential members that remained untapped.

ESET, a global IT security software and services company, faced a unique challenge in its sales structure. Unlike many businesses, ESET did not have a dedicated sales development team (SDRs). Instead, leads were qualified by marketing programs before being passed on to the sales team. This setup resulted in prospective leads remaining stagnant in the sales funnel, leading to a lower volume of sales qualified leads. The lack of a dedicated team to engage and qualify leads meant that potential opportunities were being missed, and the sales team was not able to focus on interested buyers.

Beck & Masten Buick GMC, a family-owned dealership, was facing the challenge of increasing their outreach volume and engagement. Despite being one of the top Buick GMC dealerships in the nation, they were struggling to effectively engage with their leads and customers. The dealership had a large team of 27 salespeople for new vehicles and 13 for pre-owned vehicles, but they were spending a significant amount of time on tedious outreach activities. This was particularly challenging in the service side of the business, where the team was resorting to cold calling and emails to get customers to come in for service, resulting in a low engagement rate and a frustrated team.

Sutter Shared Services (S3) provides health management and administrative services to physician groups and health systems across the nation. Their target audience includes large-scale healthcare providers who want to build their own contact center and those who are looking to enhance the patient experience by delivering after-hours answering services and clinic access. However, with a steady volume of leads from trade shows, webinars, and interest outreach, it was nearly impossible for the S3 Business Development team to engage with every lead. The team initially experimented with traditional Sales models of hiring Business Development reps to handle incoming leads, but budgetary realities prevented the team from growing at a rate necessary to meet demand.

DocStar, a division of Epicor Software Management, specializes in document management and business processes management. They receive about 500 leads per month, mostly inbound leads generated through their website. To manage these leads, they score them based on demographic, firmographic and behavioral data before sending them to the Business Development team for follow-up. However, this method of lead prioritization and follow-up presented challenges. The Business Development Representatives (BDRs) had difficulty meeting their quota for the number of outreach attempts for each lead, especially when lead volume was high. Additionally, the timing of the outreach was often not optimal, being either too early or too late in the customer journey to be of value to the prospect.

IHS Markit, a $5-billion information services firm, faced a significant challenge in managing the high volume of inquiries generated by its extensive marketing efforts and media exposure. The company, which operates in key markets such as financial services, automotive, and energy, struggled to identify and elevate leads fitting its ideal customer profiles or those ready for sales engagement. The challenge was not just the volume of inquiries but also the capacity of the sales team to follow up with potential leads. The company needed a solution that could help them manage this high lead volume without adding to the headcount, while also improving customer retention and expansion.

Generating leads is a significant investment for companies, both in terms of time and money. However, many companies struggle with effectively and efficiently following up with and converting these leads into qualified opportunities for their sales teams. This was the challenge faced by CenturyLink, the third-largest telecommunications company in the U.S. The company was looking for a way to convert more warm leads, which were coming in from a variety of inbound and outbound channels, into prospects.

The Los Angeles Film School, a renowned institution known for its personalized student relationships, faced a significant challenge in its marketing department. The school's marketing team was tasked with following up with potential students who had shown interest in the institution. However, the team was falling short of its established goal of making seven touches per lead, with an average of only 1.6 touches being made. This shortfall was identified by Ben Chaib, the VP of Admissions and Marketing, who noted that the lack of sufficient follow-ups was hindering the school's ability to convert leads into actual students. The challenge was to find a way to increase the number of touches per lead, thereby improving the lead conversion rate and ensuring more consistent conversions.

The customer, a global leader in the design, marketing, and distribution of premium lifestyle products, was facing several challenges. They wanted to respond faster to market opportunities and supply disruptions by transforming their end-to-end planning capabilities. They required a scalable solution that would allow them to postpone decisions on quantity, model, destination, price, and flow, thereby reducing inventory risk by providing transparency and flexibility. The company was also struggling with rapid identification of actions between product lead times and market closure, and there was a lack of alignment on planning and buying strategies. Furthermore, due to the volatile nature of the fashion industry, they were constantly facing optimization challenges regarding the timing and quantity of raw material purchases, dye lots, cutting, etc. to ensure customer demand is met. Lastly, with multiple brands, locations, distribution channels, and suppliers, effective communication and efficient work in a low-touch digital environment focusing on exception management was difficult.

The company, a global leader in engineered joining technologies, was facing significant challenges in its supply chain management. With over 10,000 customers in approximately 100 countries, the company was grappling with frequent capacity constraints and core planning problems. The lack of forecast visibility was a major issue, with the forecast inaccuracy being high and lagging a few months behind as a standard. This led to a strong need for demand signal improvement to ensure correct capacity adjustments. Additionally, the company was experiencing material and capacity constraints due to a lack of visibility into the capacity load for the 3-5 month horizon. The company was also unable to conduct real-time scenario planning and could not evaluate the financial impact of scenarios. Furthermore, they lacked the ability to evaluate the supply chain supportability of the different scenarios.

The customer, a leading global supplier to the automotive and industrial sectors, was facing significant challenges in managing the quality and accuracy of OEM forecasts. The company was unable to leverage external market drivers to predict demand and was heavily reliant on Excel. This resulted in high variability in the quality and accuracy of forecasts. Additionally, there was a lack of demand alignment across OEM forecasts, which were stored in multiple Excel sheets. The company also had access to external market data from providers such as IHS, but was unsuccessful in leveraging this data to improve demand planning. Furthermore, capacity checks were done manually in Excel, which resulted in the lack of a layer of intelligence on top of the execution system (SAP APO).

The marine electronics company, a specialist in providing navigation, marine instruments, and fish finding equipment to both the recreational and commercial marine sectors, was facing significant challenges in its supply chain management. The company was unable to integrate commercial, supply, and demand planning due to many siloed processes, leading to lost sales and excess inventory. The lack of end-to-end (E2E) visibility and the inability to respond to changing market dynamics further exacerbated the situation. The company was unable to create true E2E visibility across the supply chain due to a variety of disconnected planning systems operating in a siloed environment. Additionally, the company frequently experienced both inventory excess and shortages, with only 10% of the SKUs having healthy inventory across the network. The forecast accuracy for demand, especially in connection to new product introduction, was rather low.

A world-renowned retailer of musical instruments and equipment, with nearly 300 stores across the U.S. and a top-ranking direct sales website, was struggling with its merchandise planning system. The system was unable to keep up with the brand and channel needs, leading to disconnected planning processes and suboptimal decision-making. The retailer was grappling with managing sales for a mix of new and existing products. The existing processes were focused solely on the retail brick and mortar channel and were built in Excel spreadsheets, which were cumbersome and prone to human error. There was no holistic view of 'Open to Buy' across the enterprise. Furthermore, the company was missing alignment between pre-season planning and in-season forecasts as the processes were disjointed, non-standardized and managed in silos. The company also wanted to plan the growth and penetration of private label business and strengthen partnerships with top vendors.

The customer, an online retailer of office equipment, was facing challenges with their inventory management and delivery services. They were importing and delivering products directly to local distribution centers (DCs), which put each DC at risk of having excess inventory or running out of stock. The company was trying to mitigate these risks by building a replenishment center and delivering products from this center to each DC. However, the accuracy of their received sales plan was low and relied heavily on lagging indicators. Additionally, truck loading planning was done manually, a time-consuming process that often resulted in miscalculations of the required number of trucks. Lastly, the management of the minimum order quantity and complicated ordering conditions, considering the container’s capacity, were managed in Excel, which was not efficient.

The case study revolves around a leading producer of rolled aluminium and a global leader in beverage can recycling, which also serves customers in automotive, consumer electronics, construction, foil and packaging. The company has a complex, multi-stage production process that includes both internal and external operations. The challenge was to align these operations to maximize performance and streamline production. The company was also looking to reduce its carbon emissions. The planning processes were previously carried out via Excel, which was not efficient enough. The flow of information between the company and its operational partners was also crucial for driving performance improvements.

The multi-brand beauty retailer, operating over 600 stores across the Americas, was facing significant challenges in its planning process. The company was unable to collaboratively plan between central and local teams and conduct real-time scenario planning. The existing Merchandise Financial Planning (MFP) ecosystem was a combination of a legacy planning tool, data exports, and disparate Excel spreadsheets, leading to inefficiency throughout the planning process. The company's margin planning, a critical link to their global financial performance, was also problematic as they could not plan and review margin components and impacts. Furthermore, the marketing, sales, finance, and supply chain functions were operating in relative silos, each having their own assumptions and versions of the truth.

The company, a global leader in direct selling of beauty, household, and personal care products, was grappling with significant challenges in its supply chain management. The primary issue was the inability to sense demand and supply disruptions in a timely manner, which hindered their response to these disruptions. This was further complicated by a lack of coordination between the commercial, financial, and supply chain functions, leading to disjointed operations and decision-making. The company also lacked the capability to conduct real-time scenario planning, which prevented them from evaluating the financial impact of various scenarios and assessing the supply chain supportability of different scenarios. The marketing, sales, finance, and supply chain functions were operating in silos, each with their own assumptions and versions of the truth.

The multinational company, specializing in sensor manufacturing for fabrication and process automation, was facing significant challenges in its supply chain management. The company lacked end-to-end (E2E) visibility across its supply chain due to a multitude of disconnected planning systems operating in silos. This lack of visibility led to suboptimal decision-making, often based on opinions rather than data-driven facts. Additionally, the planning teams were spending a significant amount of time on manual number crunching activities such as data validation, collection, and manipulation. The company was also unable to conduct real-time scenario planning and evaluate the financial impact of different scenarios. The lack of ability to assess the supply chain supportability of various scenarios further compounded the problem.

A multinational coffee roaster and retailer, with a network of over 30,000 coffee houses worldwide, was facing significant challenges in its operations. The company's baristas were spending around six hours a day on administrative tasks such as ordering, inventory management, and forecasting, which was detracting from their ability to focus on customer service. Additionally, the company was grappling with a significant food waste problem due to inaccurate forecasting. This issue was complex, as each store stocked between 500 and 5,000 SKUs, and demand volatility was influenced by factors such as weather, assortment, pricing, and local events. The company had invested in data science teams and developed proprietary algorithms to predict the impact of weather on demand and store traffic, but these were not being utilized to their full potential.

The multinational athletic apparel and footwear brand, with a global presence, was facing challenges due to its quickly changing marketplace, long lead times, and fragmented manual tools. These factors were hampering forecast accuracy and fill rates. The company was struggling with a manual, time-intensive demand forecasting process that was unable to keep pace with market trends or shape demand effectively. Additionally, there was a lack of effective and efficient planning of aggregated raw material purchases, resulting in unnecessarily long lead times and less agility to react to changing demand. The process of matching supply and demand was complex and time-consuming, and it didn’t maximize the ability to respond to market volatility or quickly rebalance inventory based on demand location.

The Indian multinational paint company, engaged in manufacturing, selling, and distributing paints, coatings, and home decor products, faced significant challenges in its procurement process. The company had to manually adjust purchase requisitions daily to keep up with the fluctuating demand and supply. This manual intervention led to errors in purchase order (PO) placement concerning quantity and timing, which negatively impacted revenue and inventory levels. Additionally, the company had to synchronize tanker scheduling with the inventory levels at plants, aligning raw material with demand. There were also instances where POs would unexpectedly be cancelled or sought to be amended by suppliers, leading to potential revenue loss or delay.

The customer, an American multinational renewable energy company with operations in over 170 countries, was grappling with significant supply chain shifts. The company was dealing with an increasing number of complex configurations in its product portfolio and a rapidly expanding customer base. The planning processes for mold capacity planning, blade manufacturing, blade transportation, and blade installation at customer sites were disconnected, leading to cost and inventory issues. The company also lacked visibility of constraints and costs from mold capacity planning to installation at customer sites. Furthermore, due to fragmented business processes and supporting systems, the planning teams were unable to collaborate across multiple functions. The legacy processes and tools resulted in time-consuming planning and reporting efforts by planners, based on snapshots of data. The planning workforce spent the majority of their time number crunching rather than intelligent planning and decision-making.

The American multinational technology company, specializing in Internet-related services and products, was facing significant challenges in managing its global data centers. The company lacked an end-to-end material requirements planning system for capacity build-out, leading to issues with on-time delivery and inventory misalignment. The company's planning process for servers and networking equipment was highly complex and unworkable, causing disruptions in their data center delivery. Additionally, the company was unable to plan for the correct technology/supplier allocation mix, leading to artificial shortages. The company's manual processes were not scalable and were impacting predictability, cost coverages, and the ability to support the exponential growth of their business.

One of the world's largest beer companies, with over 400 different beer brands, faced significant challenges in its end-to-end planning process. The company was using SAP/APO, which was not providing the desired level of accuracy in forecasting. The use of lagging indicators in the forecasting process resulted in low forecast accuracy. Additionally, the company was unable to run fast and intelligent demand and supply scenarios, leading to suboptimal decision-making. All key scenarios were developed in spreadsheets, which was inefficient and error-prone. Furthermore, key planning processes such as demand planning, supply planning, S&OP, and S&OE were all executed in silos, without the ability to connect the dots across different time horizons. This lack of integration and visibility was a major obstacle in the company's planning process.