| Course | DBAX 9101C Business Consulting Research Project Stage 1 |
|---|---|
| Week | Week 4 |
| Paper type | Diagnosis check |
| Length | About 750 words, 5 pages |
| Format | APA 7 student paper |
| School | Walden University |
| Program | Doctor of Business Administration (DBA) |
| Updated | October 2026 |
Free sample paper for DBAX 9101C Week 4
Testing the Sponsor's Diagnosis Before Accepting It: A Diagnosis Check Setting "the Reps Cannot Sell Digital" Against Three Rival Explanations Using the Printer's Own Sales, Proposal and Commission Records
Student Name
Walden University
DBAX 9101C: Business Consulting Research Project Stage 1
Instructor Name
Month Day, Year
Testing the Sponsor's Diagnosis Before Accepting It: A Diagnosis Check Setting "the Reps Cannot Sell Digital" Against Three Rival Explanations Using the Printer's Own Sales, Proposal and Commission Records
The Diagnosis Under Test
Clients rarely arrive undecided. My client's sales vice president, at a Milwaukee commercial printer, is sure that digital service revenue lags because the salespeople cannot sell digital. If that diagnosis is right, it makes predictions the firm's records can test: salespeople should pitch digital services rarely and, when they do, lose more often than they win; and the shortfall should be spread across the sales force rather than concentrated in a few accounts. This paper checks those predictions alongside three rival explanations, before the study accepts any cause.
The Rivals
The first rival is compensation. Salespeople earn commission on the gross margin of printed jobs; digital services carry a lower commission rate because they include outside costs such as postage. A salesperson choosing where to spend time would favor print. The second rival is access: the people who buy campaigns are marketing managers, while salespeople mostly know print buyers in purchasing. The third is the offering itself: services may be priced and bundled so that customers struggle to compare or approve them. Ulaga and Loveland (2014) found that firms moving into services faced all three kinds of problem, not only sales capability.
What the Records Show
Table 1
Predictions Checked Against Last Year's Records
| Explanation | Prediction | Record | Result | |
|---|---|---|---|
| Capability | Low win rate on digital proposals | 48 digital proposals; 19 won | Win rate 40 percent, similar to print's 43 percent; not supported | |
| Capability | Shortfall spread evenly across reps | Two of seven reps produced 71 percent of digital revenue | Concentrated; partly contradicts | |
| Compensation | Few digital proposals relative to print | 48 digital against 610 print proposals | Supported | |
| Access | Digital buyers differ from print contacts | In 44 of 61 digital accounts, the buyer was in marketing; most reps' CRM contacts are in purchasing | Supported | |
| Offering | Proposals stall at pricing or approval | 11 of 29 lost digital proposals stalled waiting for customer approval of a quote | Partly supported | |
Records from the client's customer relationship management system and commission reports, shared under the engagement agreement.
Reading the Results
The capability diagnosis is weakened but not dismissed. When salespeople do propose digital services, they win about as often as they win print work. That pattern argues against a general inability to sell. The concentration of digital revenue in two salespeople could reflect skill, but both of them, it turns out, came to the firm from agencies and already knew marketing managers. That points as much to access as to capability.
Compensation and access are both supported. Salespeople propose digital services far less often than print, which fits a commission plan that rewards print. And the buyers of digital services sit in a different department from most salespeople's contacts. Tuli et al. (2007) found that solutions require relationships with several people in the customer firm, which fits this result.
What the Check Does Not Settle
Records cannot show why salespeople propose digital so rarely. Low proposal counts fit the compensation explanation, but they also fit an access problem or a lack of confidence. Interviews with salespeople will be needed to separate them. Nutt (1999) found that decisions failed more often when managers settled on one diagnosis early; leaving several open is deliberate.
Limits of the Records
The records have their own weaknesses. The customer relationship system depends on salespeople logging contacts, and two of the seven admit they log only their main contact at each account, which could understate how many reach marketing staff. Proposal counts include only formal quotes, so a salesperson who mentions digital services in conversation but never sends a quote appears to have done nothing. And one year of records may reflect unusual conditions; the digital team lost its designer for four months last spring. I will request the previous year's records to see whether the same pattern holds, and I will treat the table as a reason to investigate, not as a finding, until the interviews explain what the numbers cannot.
Telling the Sponsor
I shared the table with the vice president before writing it up. The initial reaction was skeptical, but the vice president agreed that the win-rate figure was surprising and that the two strongest digital sellers had come from agencies. We agreed the study would examine compensation, access and the offering alongside capability, and that the vice president would see each finding before the president does.
References
Nutt, P. C. (1999). Surprising but true: Half the decisions in organizations fail. Academy of Management Executive, 13(4), 75-90. https://doi.org/10.5465/ame.1999.2570556
Tuli, K. R., Kohli, A. K., & Bharadwaj, S. G. (2007). Rethinking customer solutions: From product bundles to relational processes. Journal of Marketing, 71(3), 1-17. https://doi.org/10.1509/jmkg.71.3.001
Ulaga, W., & Loveland, J. M. (2014). Transitioning from product to service-led growth in manufacturing firms: Emergent challenges in selecting and managing the industrial sales force. Industrial Marketing Management, 43(1), 113-125. https://doi.org/10.1016/j.indmarman.2013.08.006
Reading the DBAX 9101C Week 4 instructions
Week 4 asks you to test your client's diagnosis before accepting it. State the diagnosis as a claim and derive predictions the client's records could confirm or contradict. Identify at least two rival explanations and their predictions. Check all predictions against records in a table, reporting the evidence and the result for each. Read the results for what they establish and what they cannot. Describe weaknesses in the records themselves. Explain what interviews or further data will be needed to separate explanations that the records leave tied. Close by describing how you shared the results with your sponsor and what was agreed about the causes the study will examine.
How the DBAX 9101C Week 4 example is put together
The paper restates the capability diagnosis as predictions. A section introduces compensation, access and service design as rivals, citing Ulaga and Loveland. A table checks five predictions against proposal, revenue and contact records. A section shows the win rate argues against a general inability to sell, and that the two strongest digital sellers came from agencies. A section finds compensation and access supported, citing Tuli and colleagues. A section names what the records cannot show, citing Nutt. A section lists record weaknesses, including incomplete contact logging and a four-month designer vacancy. A closing section reports the sponsor's agreement to examine all four explanations. Each prediction is labeled supported, partly supported or not supported, so the sponsor can read the verdicts quickly.
DBAX 9101C Week 4 rubric: what earns full marks
Strong checks turn the client's belief into testable predictions and treat rival explanations with equal care. A table linking each prediction to a specific record carries the most weight. Reporting results that cut against the sponsor's view, as well as those that support it, shows independence. Distinguishing what records establish from what they cannot shows judgment. Naming weaknesses in the records demonstrates rigor. Planning interviews to separate tied explanations shows design thinking. Sharing results with the sponsor and recording the agreement shows consulting skill. Checks that only confirm the client's view, rely on anecdote or overstate what records show earn lower marks. Writing predictions before looking at the records is the habit faculty most want to see, because it prevents the reading from bending to fit.
DBAX 9101C Week 4 help from the desk
Ask what would be true in your client's records if the sponsor's diagnosis were right, and write those predictions down before you look. Then do the same for two or three other explanations. Pull the records and fill in a table. Expect some results to surprise you. Ask what each record can and cannot show; activity logs, for example, depend on staff entering them. Many students look only for evidence that supports the sponsor, which makes the study an expensive confirmation. Others dismiss the sponsor's view entirely after one contrary figure. Share the table with your sponsor in person. Our writers can help you turn a diagnosis into predictions and choose records that test them.
Get a DBAX 9101C Week 4 example written to your instructions
Send the Week 4 prompt and rubric along with the client's diagnosis as they stated it and any evidence they offered for it. A diagnosis check on a comparable claim, with decomposition, ratings and fairly stated rivals, is back within 24-48h, and the first one is free. It audits an invented diagnosis, so your client's own figures never leave the relationship.
More DBAX 9101C papers and DBA samples
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- DBAX 9101C Week 2: Client Problem Statement
- DBAX 9101C Week 3: Researchable Restatement Paper
- DBAX 9101C Week 5: Client Stakeholder Map
- DBAX 9101C Week 6: Usable Answer Note
- DBAX 9101C Week 7: Consulting Scope Boundary
- DBAX 9101C Week 8: Client Access Statement
- DBAX 9101C Week 9: Consultant Independence Note
- DBAX 9101C Week 10: Consulting Peer Read
- DBAX 9101C Week 11: Consulting Stage 1 Document
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- DBAX 8151 Week 4: Evidence Appraisal Paper
- DBAX 8101 Week 4: Targeted Framework Revision
- DBAX 8006 Week 4: Bounded Position Memo
DBAX 9101C Week 4 questions, answered
Where can I find a free DBAX 9101C Week 4 sample paper?
The diagnosis check, with its prediction table, is open to read below without paying.
What diagnosis does the DBAX 9101C Week 4 paper test?
That the salespeople cannot sell digital services.
What was the digital win rate?
40 percent, close to print's 43 percent.
Which explanations did the records support?
Compensation and customer access.
What did the sponsor agree to?
Examining compensation, access and service design alongside capability.