1page Summary and Diagram -Improv Bus Wk3 Assgnmnt

________________________________________________________________________________________________________________ HBS Professor Steven C. Wheelwright and writer William Schmidt prepared this case solely as a basis for class discussion and not as an endorsement, a source of primary data, or an illustration of effective or ineffective management. This case, though based on real events, is fictionalized, and any resemblance to actual persons or entities is coincidental. There are occasional references to actual companies in the narration. Copyright © 2011 President and Fellows of Harvard College. To order copies or request permission to reproduce materials, call 1-800-545-7685, write Harvard Business Publishing, Boston, MA 02163, or go to http://www.hbsp.harvard.edu. This publication may not be digitized, photocopied, or otherwise reproduced, posted, or transmitted, without the permission of Harvard Business School.

S T E V E N C . W H E E L W R I G H T

W I L L I A M S C H M I D T

Baria Planning Solutions, Inc.: Fixing the Sales Process

Christy Connor looked up from her computer and gave a weary sigh. As the recently hired director of North America Sales Support for Baria Planning Solutions (BPS), a consulting firm serving manufacturers, Connor knew that she would be very busy trying to improve the disappointing performance of her team. The Sales Support group’s difficulties were having a direct negative impact on the performance of the entire company. The importance of her mission was highlighted by the constant stream of calls, meetings, and emails that she had been fielding since she joined the company last month. The urgency and critical nature of the problem was summarized by a recent email from her boss, Brandon Ali, the President of North American Sales:

From: Brandon Ali

To: Christy Connor

Subject: 2010 Performance

Sent: Mon 2/21/2011 4:23 A.M.

I have again looked at the win-loss report for 2010 and I am very concerned. Of the 271 qualified new sales opportunities that arose in calendar year 2010, our win rate is now projected to be a dismal 15.5%. We had originally forecast a win rate of 17.5%. Since our customers typically sign 3-year contracts, we will be struggling for the next couple of years because we’ve missed our forecast sales productivity target. Even more worrisome is the drop in our renewal rates. We had consistently achieved a renewal

4 5 6 8 M A Y 1 9 , 2 0 1 1

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rate of around 91% to 92% over the last few years, but in 2010 it is 84%.

The Sales group directors are complaining that salespeople don’t get the timely assistance that they need from the Sales Support group. While your team is partly organized along the same industry divisions as the Sales group, some of the directors are suggesting that your entire team be organized into industry-specific divisions in order to provide sharply focused and fully dedicated support to each Sales division. I know your people work hard, but we have apparently missed proposal deadlines for several opportunities, and each time it undermined the customer’s impression of us.

I realize that you have inherited a bit of a mess, but it is critical that you get your arms around this situation and resolve it quickly. We appear to be digging ourselves deeper into a hole with every passing week. Please have a proposal to me by next week with recommendations on how we can turn this situation around. As part of this effort, I want you to quantify the staffing, utilization and costs from your proposal based on the sales support requests for 2010 and compare it to our actual staffing and utilization in 2010.

When Connor was in business school, she had learned about analyzing service operations processes using production management techniques. Believing she could apply those techniques to the challenges at hand, she decided to investigate the scheduling and work processes for her team.

Company and Industry Background BPS, a publicly traded firm with $95 million in annual sales, helped its customers reduce

procurement costs and improve the performance of their suppliers. Through a combination of software, data analysis, project management, and consulting, BPS scrutinized its customers’ spending categories, identified sources of potential savings through initiatives such as supplier consolidation and purchase standardization, and implemented procurement and change-management projects to realize those savings. Companies offering this type of solution—sometimes referred to as spend analysis or spend management—had experienced relatively rapid growth over the last few years. BPS, founded in 1997 to take advantage of the nascent popularity of similar tools and analysis methods, was considered an early mover in the field.

Spend analysis was once the near-exclusive domain of smaller, specialty solution providers like BPS. During the past several years, however, several large software and consulting firms, including SAP and Accenture, have entered the market, leading to consolidation among smaller firms. BPS, which originally served the U.S. energy sector exclusively, had survived by expanding its industry coverage and capabilities through the acquisition of other narrowly focused industry-niche providers. In 2007 BPS acquired a firm that primarily served the government sector, including federal and state agencies and some large municipalities and nonprofit organizations. In 2008 BPS acquired two more firms, one serving a range of manufacturing companies and another that primarily served the retail sector.

While BPS initially allowed the acquired firms to continue operating semi-autonomously, the company had since worked hard to integrate parts of each operation where synergies could be achieved. The amount of effort required had not been trivial. While all four firms provided solutions that addressed the same types of customer needs, the similarities ended there. In addition to serving different industries, the firms had entirely different technology platforms, service delivery processes, and even different fiscal year end-dates. Most of the pressing integration work was complete by the end of 2009, although some technology migration projects were still in the works. By 2010, BPS commanded a respectable 18% share of the market, but in a highly competitive market BPS could not afford to lose any momentum in sales growth.

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Recent Performance The company’s performance in 2010 was extremely disappointing in both new client attainment

and existing client renewals. Exhibit 1 identifies the original and latest forecast for the sales opportunities that were qualified in 2010. BPS categorized all sales opportunities into one of four types:

New Sale: a new opportunity with a company that is currently not under contract with BPS.

Renewal: a renewal of a contract with an existing customer. The terms of the contract can be materially different from the original contract, but there is often a significant amount of overlapping scope between the two contracts.

Expansion: an expansion of the services delivered to an existing customer even though the customer’s current contract is not near its renewal date.

Pilot: a special type of New Sale in which a company engages BPS in a short-duration pilot in order to get more exposure to the BPS solution in the context of an actual project. Pilots often enter the New Sales pipeline at the completion of the pilot project.

The most recent update to the sales forecast in Exhibit 1 was mid-February, 2011. By this time BPS knew with certainty the outcome of all of the Renewal opportunities from 2010 and could make a very good forecast of the outcome of the New Sale, Expansion, and Pilot opportunities. The total number of opportunities in 2010 was higher than originally estimated, but the win rate was now projected to be much lower than anticipated in most opportunity categories. Although the Sales Support group was not entirely to blame for the lower win rates, it was widely recognized that the team had difficulties meeting proposal deadlines and this had prevented BPS from putting its best foot forward in several selling situations.

Organization of North American Sales Although BPS served customers on a global scale, its direct sales force focused on companies in

North America. BPS had several sales partnerships that allowed it to penetrate foreign markets, and many of BPS’s North American customers utilized the BPS solution outside of North America. BPS’s sales partners typically required very little support during their sales cycles, and when they did it was delivered by the product management team, leaving the North American Sales organization to focus on its primary objective: drive new sales and renewals in North America.

The North American Sales organization was structured into three groups—Sales, Sales Operations, and Sales Support (see Exhibit 2). The Sales group, led by Chuck Dee, had four units organized by the four major industry sectors that BPS served:

Energy, including oil and gas companies and utilities.

Government, including all federal, state, and local government agencies, as well as a handful of large nonprofit organizations.

Manufacturing, covering companies in chemicals, construction, diversified manufacturing, electronics, high technology, and transportation.

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Retail and Other. While this sales division consisted mostly of large retail and wholesale operations, it was also used as a catch-all for any sales opportunity that BPS pursued which did not fit neatly into the other sales divisions

The industry alignment of the Sales group was a legacy of BPS’s acquisition strategy, but the sales leadership believed that it was extremely useful to maintain this industry orientation.

The Sales Operations group, led by Jane Albright, was responsible for competitive intelligence, win-loss analysis, sales training, staffing, and managing the sales force compensation plan. While this group was not directly involved in any sales opportunities, it served a pivotal role in building the infrastructure for a successful sales force. Albright and Dee were sometimes at odds over how the sales force should be structured. Dee felt that all of the teams in the Sales Support group should be aligned by industry sector, effectively providing fully dedicated support for the Sales group. Albright believed that such a structure would require a large increase in staff. She and the former director of Sales Support—Christy Connor’s predecessor—had successfully lobbied for the current hybrid organization of the Sales Support group.

Organization of the Sales Support Group During BPS’s acquisition spree it initially maintained the structure of each firm’s sales team and

sales support functions. Since these predecessor firms were industry-focused, the sales force and support staff were originally organized by industry as well. In 2008 BPS hired Albright to serve as the director of Sales Operations and provide a consistent administrative and organizational infrastructure that each sales team could leverage. One of Albright’s first contributions was to help streamline the Sales Support group, consolidating some sales support functions into teams that served all industries and leaving one function, Proposal Support, with staff dedicated to each industry. When Connor asked Albright about the rationale for this structure, she replied:

After BPS completed its string of the acquisitions the firm was under tremendous pressure to get costs under control. Of course the market downturn that began in 2008 added another level of urgency to the situation. We felt that it was imperative, however, to maintain our industry-centric, consultative sales process. The only way we could hope to legitimately achieve this was to keep critical elements of our sales organization organized by industry so they would continuously be immersed in industry issues. After looking hard at the sales support function we decided that we could streamline the team and maintain an industry focus with the hybrid model that exists today. Data Engineering, Data Analysis, and Pricing do not require any meaningful industry-specific expertise, but there are some real benefits to having Proposal Support staffed with experts in the customer’s industry. There may still be issues that need to be ironed out, but I remain convinced that the hybrid structure is critical for us to effectively balance staffing constraints against the requirements for industry expertise.

Exhibit 3 provides a diagram of the process flow for the Sales Support group. The four teams in the group have the following responsibilities:

Data Engineering: collect data from prospects, transform data into a standard format, examine data for consistency and quality, and resolve any data irregularities.

Data Analysis: process data through BPS spend analysis software and identify opportunities for cost reductions and supplier performance improvement.

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Proposal Support: validate, quantify, and prioritize cost/performance opportunities; develop configuration of software, project management, and consulting to address the identified opportunities; and assist the salesperson in developing and pitching proposal.

Pricing: develop a pricing proposal in accordance with sales strategy, including options for risk- sharing pricing, which tied the payments that BPS received from the customer to the results BPS delivered to the customer.

This type of hybrid team structure did appear to be unique in the market. Most companies roughly the same size as BPS in the spend-analysis space had organized their sales support teams entirely by geography. Having an industry focus allowed BPS to distinguish itself from other mid- sized competitors through a deeper understanding of industry-centric issues, and put the firm at parity with small single-industry and large diversified competitors.

Dee took a different view on the situation. He felt that a hybrid structure didn’t go far enough and was adamant that his team was losing opportunities because the Sales Support team wasn’t able to meet its deadlines. He made his position clear when Connor met with him, saying “Since some of the Sales Support teams are shared across sales divisions they don’t feel the urgency or the ownership that is necessary to push proposals across the goal line.”

Solution Selling Process BPS had adopted a solution-selling process several years ago as customers—who had recently

come to enjoy unprecedented competitive choice in buying business solutions—began demanding greater assurances that any solution that BPS proposed would achieve its promised cost reductions and performance improvements. The new selling process was supposed to meet this demand and thereby lead to significant increases in sales and renewal rates by providing tangible performance guarantees to customers in a timely fashion.

Solution-selling was essentially a consultative sales process. It shifted a considerable amount of effort from the post-contractual to the pre-contractual stage. Clients provided BPS with detailed data for analysis, and BPS invested significant resources to gather and properly analyze the data. Typically both parties signed nondisclosure agreements prior to data collection and often a letter of intent. The end result was a highly detailed and execution-ready proposal that explained the services BPS would deliver, the precise projects that BPS would implement, the timing of the project milestones, the resources required from the customer, and any risk-sharing pricing or performance guarantees BPS would provide.

If the solution-selling process proceeded as intended, customers gained by having a clear understanding of the benefits of the BPS solution and guaranteed performance targets. BPS gained by having clearly communicated expectations, which increased the customer’s confidence in the BPS solution and dramatically improved the likelihood of attaining the guaranteed performance targets (which are costly to BPS if not achieved). Assuming the customer agreed to move forward to a contract, the process also benefited both parties in all but eliminating the need for further extensive contract negotiations.

The solution-selling process required the Sales Support team to devote substantial upfront effort to develop a proposal. Team members tracked the time they spent on each sales opportunity. Exhibit 4 provides a summary of the time required for each Sales Support function across the different types of opportunities. Regardless of the large workload associated with the process,

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everything had to be completed in a timely fashion. Customers and prospects were unwilling to significantly delay their solution selection choice due to the vagaries in the selling process of a single vendor. The competition in the market was stiff and vendors had to be responsive with a high quality proposal or risk early elimination.

Feedback on the process from BPS customers and prospects varied widely. While some companies greatly appreciated the in-depth analysis and the greater confidence that it engendered in the BPS solution, others complained that BPS “didn’t have their ducks in a row” by the time of the sales presentation. In some cases, the BPS sales team has had to delay the presentation by days or even weeks. Dee shared a recent experience with Connor:

I was on a call just last month with one of my salespeople trying to convince a prospect to give us more time on a proposal review session. The prospect was polite but made it clear that they were on a strict schedule and we had to either present on time or drop out of the running. He was willing to give us a day or two, but we needed two more weeks. Unfortunately the Sales Support team just couldn’t pull all the moving parts together in time. We presented what we had, but it was not well received. This was not a last minute project either…we had a full four weeks of advance notice.

Members of the Sales Support group were all too aware of the criticisms that had been leveled against them. While they believed that the solution selling process could be quite effective in helping the company win sales opportunities, they also believed that the expectations placed upon the team could be unrealistic. Connor had one-on-one discussions with each member of her team in order to better understand the pressures that they faced. As one team member put it:

Our workload is crazy. Some weeks I have a reasonable amount of assignments and I can readily meet all of my obligations. In other weeks I have such a backlog of requests that I find myself working late every night and over the weekend. I love the fast pace, but when it gets really busy I am forced to explain that the sales deadlines won’t be met without cutting corners on the analysis…and sometimes not even then! My husband has given up trying to schedule family activities during those times and takes to referring to me as his “shadow” wife.

Other team members echoed these comments and blamed the group’s difficulties on issues over which they felt they had little control, including lack of visibility into the sales pipeline, being brought in late on contract renewals, and sales support requirements that varied widely from one sales opportunity to the next.

Demands on the Sales Support Group With the exception of renewals, sales opportunities arose randomly within a quarter. Some of the

sales divisions tended to be busier than others across quarters, which seemed like an artifact of the different fiscal year ends of the predecessor companies and the differing selling seasons among industries.

Renewals were based on the expiration date of the customer’s current contract. The Sales Support team typically entered the planning process for a renewal about 5 weeks prior to the renewal date, and the renewal presentation with the customer was usually scheduled to take place 2 to 3 weeks after that; this left the team 2 to 3 weeks to conduct the analysis for the renewal. By conducting the analysis as close to the renewal date as possible the team could utilize the very latest information

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on the current engagement with the customer. The four steps in the sales support process for renewals had average times to completion of 8 hours, 12 hours, 22 hours, and 4 hours respectively (see Exhibit 4), which seemingly could be completed in ample time before the customer presentation.

Initially Connor suspected that her team may simply be under-staffed, but she set aside this suspicion as she dug into data on the frequency and composition of the support requests that the team received in 2010. To gauge staff utilization in roles that had variable effort levels (exactly the situation that the Sales Support group faced) the company used a rule of thumb: if a function utilized less than 70% of its capacity, it was considered at “low” risk of being caught short of staff due to the variable nature of the work. Utilized capacity between 70% and 85% represented “medium” risk, and between 85% and 100% “high” risk. When utilized capacity exceeded 100% the function was obviously already “over” capacity. Connor summarized the number of requests that her group received by industry sector in each quarter of 2010 (see Exhibit 5) and created annual summaries of the requests for 2009 and 2010 (see Exhibit 6). As a first draft of the analysis Ali had requested, Connor used this data and the information on mean process times to create a rough estimate of her group’s annual staff utilization levels (see Exhibit 7). She compared these utilization levels to the company rule of thumb and it appeared at first blush that her team wasn’t being stretched too far.

Connor considered cross-training her staff so people could pitch in wherever the workload was the greatest. After looking at the annual utilization levels she had pulled together, it wasn’t clear, however, that cross-training would provide much benefit. She asked Albright about this, but the response was deflating:

We explored cross-training in the past and it was a bit of a disaster for two reasons. First, the skill sets across the four functions on your team are very different, which makes most types of cross-training ineffective and cost-prohibitive, with a couple of exceptions. We found that Data Engineers could be cross-trained as Data Analysts, and vice versa, at a per-person cost of approximately one month of salary and benefits, but neither type of resource could become proficient at proposal support or pricing. The Proposal Support team members could be cross-trained to support multiple industries at a per-person cost of approximately three weeks of salary and benefits, but Chuck has a very low tolerance for that idea—he feels it’s moving us further away from his desired organization structure. As for the Pricing team members…well, let’s just say it is best to leave them focused on pricing issues.

Second, the cross-trained team members were most effective when they stayed in each role for at least three months. When we shifted people into roles for shorter time periods, their productivity went way down.

Next Steps Connor reviewed her notes. There were a number of actions that BPS could try. Should she hire

more resources? Abandon the industry-focused sales support team structure? Reorganize to a fully industry-centric organization as Dee requested? Attempt to streamline the solution-selling process? Give up on solution-selling altogether? Try novel cross-training tactics? Or was there a more effective way to improve the team’s performance? The challenge was determining what course of action would actually work. Connor considered the irony of asking Ali to extend the due date for getting him a proposed solution. She knew he wouldn’t agree—which made her empathize even more with the people on her team.

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Exhibit 1 Forecast New Revenue from 2010 Opportunities, Excludes Contracts Not Up for Renewal

Opportunities Win Rate Annual

Revenue

Average Duration

(years) Total Contract

Revenue ($) Original Forecast for 2010a New Sale 250 17.5% $250,000 3 $ 32,812,500 Renewal 117 90.0% $250,000 3 $ 78,975,000 Expansion 60 90.0% $ 75,000 3 $ 12,150,000 Pilot 80 25.0% $ 50,000 1 $ 1,000,000 Total 507 $ 124,937,500 Latest Forecast for 2010b New Sale 271 15.5% $225,000 3 $ 28,353,375 Renewal 117 83.8% $250,000 3 $ 73,534,500 Expansion 53 90.0% $ 70,000 3 $ 10,017,000 Pilot 103 22.0% $ 50,000 1 $ 1,133,000

Total 544

$ 113,037,875

a Original Forecast was finalized in May 2010.

b Latest Forecast was updated in February 2011.

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Exhibit 3 Sales Support Process Flow

Exhibit 4 Sales Support Time by Function (hours)

New Sale Renewal Expansion Pilot Mean All Sales Support Requests in 2010 271 117 53 103 1-Data Engineering Min 12 4 9 8 Max 85 21 77 65 Mean 24 8 22 20 Standard Deviation 16 3 15 13 Weighted Mean Process Time 20 2-Data Analysis Min 11 7 9 3 Max 80 31 55 29 Mean 24 12 16 10 Standard Deviation 15 4 10 4 Weighted Mean Process Time 18 3-Proposal Support Min 18 8 11 6 Max 155 61 107 42 Mean 44 22 29 12 Standard Deviation 30 9 20 9 Weighted Mean Process Time 32 4 - Pricing Min 4 3 2 3 Max 24 8 16 17 Mean 8 4 6 6 Standard Deviation 3 1 2 2 Weighted Mean Process Time 7

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Exhibit 5 Requests for Sales Support, by Quarter (count)

2010

1st

Quarter 2nd

Quarter 3rd

Quarter 4th

Quarter Annual

Total Quarter Average

New Sale Energy Sector 19 17 16 20 72 18.00 Government Sector 8 18 20 8 54 13.50 Manufacturing Sector 22 27 23 34 106 26.50 Retail and Other Sectors 12 10 7 10 39 9.75 Total 61 72 66 72 271 67.75 Renewal Energy Sector 9 10 5 4 28 7.00 Government Sector 2 5 14 3 24 6.00 Manufacturing Sector 5 5 11 27 48 12.00 Retail and Other Sectors 11 4 2 0 17 4.25 Total 27 24 32 34 117 29.25 Expansion Energy Sector 2 4 4 3 13 3.25 Government Sector 1 2 5 3 11 2.75 Manufacturing Sector 4 4 3 10 21 5.25 Retail and Other Sectors 4 2 2 0 8 2.00 Total 11 12 14 16 53 13.25 Pilot Energy Sector 5 6 6 5 22 5.50 Government Sector 4 4 3 4 15 3.75 Manufacturing Sector 7 9 8 12 36 9.00 Retail and Other Sectors 12 7 5 6 30 7.50 Total 28 26 22 27 103 25.75 Total Requests Energy Sector 35 37 31 32 135 33.75 Government Sector 15 29 42 18 104 26.00 Manufacturing Sector 38 45 45 83 211 52.75 Retail and Other Sectors 39 23 16 16 94 23.50 Total 127 134 134 149 544 136.00 Renewals Won Energy Sector 8 10 4 4 26 Government Sector 2 4 11 3 20 Manufacturing Sector 4 5 10 20 39 Retail and Other Sectors 8 3 2 0 13 Total 22 22 27 27 98

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Exhibit 6 Year Over Year Requests for Sales Support (count)

2009 2010 Growth Energy Sector Requests processed New Sale 65 72 10.8% Renewal 27 28 3.7% Expansion 11 13 18.2% Pilot 15 22 46.7% Total 118 135 14.4% Renewals Won 25 26 Renewal Win Rate 92.6% 92.9% New Sales Win Rate 18.5% 16.7% Government Sector Requests processed New Sale 50 54 8.0% Renewal 23 24 4.3% Expansion 10 11 10.0% Pilot 14 15 7.1% Total 97 104 7.2% Renewals Won 21 20 Renewal Win Rate 91.3% 83.3% New Sales Win Rate 24.0% 22.2% Manufacturing Sector Requests processed New Sale 94 106 12.8% Renewal 44 48 9.1% Expansion 18 21 16.7% Pilot 32 36 12.5% Total 188 211 12.2% Renewals Won 40 39 Renewal Win Rate 90.9% 81.3% New Sales Win Rate 12.8% 11.3% Retail and Other Sectors Requests processed New Sale 37 39 5.4% Renewal 16 17 6.3% Expansion 9 8 -11.1% Pilot 24 30 25.0% Total 86 94 9.3% Renewals Won 14 13 Renewal Win Rate 87.5% 76.5% New Sales Win Rate 32.4% 15.4%

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Exhibit 7 Utilization Across Sales Support Functions

Workload (requests)

Mean Process

Time (hours)

Resources (headcount)

Fully- Loaded

Cost ($/year)

Available Work

Hoursa Utilization

Utilization Rule of Thumb

Full Year 2010 1–Data Engineering 544 20 8 $70,000 14,080 75.8% Medium 2–Data Analysis 544 18 7 $75,000 12,320 79.4% Medium 3–Proposal Support Energy Sector 135 32 3 $105,000 5,280 81.2% Medium Government Sector 104 32 3 $105,000 5,280 62.5% Low Manufacturing Sector 211 32 5 $105,000 8,800 76.1% Medium Retail and Other Sectors 94 32 2 $105,000 3,520 84.8% Medium 4–Pricing 544 7 3 $60,000 5,280 67.7% Low

a Hours per year assumption: 1,760

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