Day in the Life of a Management Consultant: Three Real Days
Three management consultants wrote down everything they did on one ordinary workday. An MBB associate on a Monday in Houston who started the day on a 6 AM flight and ended it remaking a slide at 11:30 PM in a Marriott. A Big 4 manager on a Thursday in the San Francisco office who spent four hours in meetings and three hours on a deck nobody will see. A boutique consultant on a Wednesday at a bottling plant in rural Ohio who argued with a plant manager about changeover times and ate lunch standing next to a palletizer. Same title on the business card. Very different Wednesdays.
These characters are composites, built from dozens of real accounts, interviews, and community threads. The people aren't real. The experiences are.
Cole's Monday
Cole
Alarm. Dark. My apartment in the West Village is quiet because nothing in New York is happening at 4:45 AM except me and the bodega guy on the corner, who I've never spoken to but who nods at me on Mondays because he sees me leaving with a suitcase every week. The nod is the longest relationship I have with anyone in my building. Shower. Dress. The shirt I'm wearing today was ironed by the hotel dry cleaning service last Thursday. I picked it up on my way out and it's been hanging in my closet since. $4.75 for a pressed shirt feels expensive until you calculate how long it takes to iron a shirt yourself at 5 AM when your hands are still waking up. That math works out in the hotel's favor.
Uber to LaGuardia. The driver's name is Rashid and he doesn't make conversation, which at 5:20 AM is the highest form of hospitality. I check email on my phone. Fourteen new messages since I went to bed at 11 PM. Most are calendar invites for meetings at the client site this week. One is from the engagement manager, Danielle, with a subject line that says "Pre-read for Monday steerco." The pre-read is a 42-slide deck that I need to review before a 10 AM meeting. It's 5:20 AM. The meeting is in four and a half hours. The deck is 42 slides. I start reading it in the Uber.
Gate B34. United flight to IAH. Boarding group 1 because the firm's corporate travel program has status. I'm in seat 3C, aisle, which is my seat on every Monday morning flight. I've been in 3C approximately 80 times. The flight attendant, whose name I don't know but whose face I recognize, hands me a water without asking. We have an unspoken arrangement. I open my laptop before the door closes. I have roughly two hours and 40 minutes of flight time to: finish the pre-read (25 minutes), update the market sizing model with weekend data pulls (45 minutes), and draft three slides for the competitive landscape section that Danielle asked for on Friday (90 minutes). That's 160 minutes of work. The flight is 165 minutes. The math leaves five minutes for the bathroom and zero minutes for contemplation. This is fine. Monday flights are not for contemplation.
Houston. Hobby Airport. Uber to the client's headquarters in the Energy Corridor. The building is a glass tower that looks like every corporate headquarters built between 2005 and 2015. Our team room is on the 14th floor, a conference room that the client gave us four weeks ago and that now contains: a whiteboard with a framework that hasn't been erased in three weeks, a printer that jams on slide 7 of every document, six laptop chargers in a tangle under the table, and a bowl of individually wrapped peppermints that the client's admin, Barb, refills every morning. I don't know who eats the peppermints. The bowl is always half full. This is one of the minor mysteries of consulting that I've stopped trying to solve.
Team sync. Danielle, me, and two analysts: Kira and Amit. Danielle runs through the week. Monday: steerco at 10 (the partner, Thomas, presents our progress to the client's leadership team). Tuesday: stakeholder interviews with the VP of Exploration and the head of Midstream Operations. Wednesday: working session to finalize the cost reduction waterfall. Thursday: partner review of the final deliverable draft. Friday: I fly home. Danielle asks me where I am on the competitive landscape. I say "80%." This is a lie. I'm at 65%. "80%" means "I know what the remaining work is and I can finish it today if nothing interrupts me." "65%" means "I know what the remaining work is and I cannot finish it today because something will definitely interrupt me." The difference between 80% and 65% in consulting is the difference between confidence and honesty, and the culture rewards confidence.
Steerco. This is the weekly steering committee meeting where Thomas presents our progress to the client's SVP of Strategy, a man named Craig, and two of his direct reports. The room has a 75-inch screen, a speakerphone shaped like a UFO, and seven people, four from the client side and three from ours (Thomas, Danielle, and me; Kira and Amit stay in the team room). Thomas presents. He's smooth. He's been doing this for 18 years and the delivery is practiced without being rehearsed. The slides I built last week are on the screen. The market sizing slide, which took me six hours, gets about 90 seconds of discussion. Craig nods. One of his direct reports, a woman named Vanessa, asks a question about the assumptions behind the North American shale gas forecast. Thomas turns to me. This is my moment. I've been sitting here for 20 minutes waiting for exactly this. I answer the question. I know the answer because I spent four hours on Saturday pulling EIA data and building a sensitivity table. Vanessa nods. Thomas moves on. The total duration of my contribution to this 60-minute meeting was approximately 45 seconds. But those 45 seconds are the reason I flew here this morning.
Back in the team room. Slide work. The competitive landscape section needs three more slides: a competitor profile for the client's main rival (a Houston-based E&P company with $8 billion in revenue), a market share trend chart, and a strategic positioning map. The competitor profile requires data from three sources: public filings (10-K and proxy statement), an industry report from Wood Mackenzie that costs $4,500 and that the firm purchased for this engagement, and an expert interview transcript from a call we did last week with a former VP at the competitor. I pull data from all three, cross-reference, and build. This is the work. This is what "management consulting" actually is, on a minute-by-minute basis, when nobody's watching. It's a person in a conference room with a laptop, three PDFs, an Excel model, and PowerPoint, trying to synthesize information that exists in multiple formats into one slide that tells a story a C-suite executive will understand in 30 seconds.
Lunch. The client has a cafeteria. It's decent. I eat a chicken Caesar wrap and a bag of chips at my desk in the team room because Danielle wants to see the competitor profile slide before the end of the day and I lost 45 minutes to the steerco. Kira eats with me. She's 24, six months into her first consulting job, and she has the specific kind of energy that comes from not yet knowing how long this goes. She asks me if it gets easier. I say "you get faster." This is true and it's not the same as easier, but the difference is something she'll figure out on her own timeline.
Expert interview. Amit and I dial into a call with a former drilling operations manager who now consults independently. The firm pays $750 per hour for this call through an expert network called GLG. The man's name is not disclosed to us; he's "Expert 7" in our system. Expert 7 knows more about the client's competitive environment than our entire team combined. He's worked in this basin for 22 years. In 45 minutes, he gives us: the competitor's actual well costs (which differ from the public filings by about 15%), their capital allocation philosophy (described as "drill the best rock first and worry about reserves replacement later"), and his assessment of their management team ("competent but conservative, won't move on an acquisition unless it's accretive in year one"). I type while he talks. Amit takes backup notes. When the call ends, I have four pages of notes that will become one and a half slides. Four pages to 1.5 slides is approximately the compression ratio of consulting. You gather 10 pounds of information and deliver 1 pound of insight.
Danielle reviews my competitor profile slide. She likes the structure but wants me to sharpen the "so what." The "so what" is consulting language for: what does this information mean for our client's decision? The data is necessary but not sufficient. The slide has to answer the question the data raises. In this case: the competitor is well-capitalized but conservative, which means the client has a window to move aggressively into the western acreage before the competitor decides to act. That's the "so what." Danielle points to the box where it should go. I write it. She reads it. She says "tighter." I rewrite it. She reads it again. She says "good." The exchange takes 12 minutes. The rewriting takes another 20. Thirty-two minutes to produce two sentences. Those two sentences will appear on the screen for approximately 15 seconds during Thursday's partner review. The ratio of production time to display time is roughly 128 to 1.
The client side of the floor empties out between 5 and 5:30. You can feel the building exhale. The elevators get busy. The parking garage hums. Our team room stays occupied. Amit is building a financial model. Kira is formatting a waterfall chart. Danielle is on a call with Thomas about Thursday's deliverable. I'm on slide two of three for the competitive landscape. The building is empty and we're still here. This is not unusual. This is Tuesday through Thursday every week. The client goes home at 5:30 because they work here. We stay because we don't. Our Marriott room is not home. It's a room with a bed and a desk and a TV I'll turn on for background noise at 10 PM. Staying at the client site until 7 or 8 PM is preferable to staying at the Marriott until 7 or 8 PM because at least here there are other people and a printer and Barb's peppermints.
Leave the client site. Uber to the Marriott. Check in. Room 614. I've had room 614 before. Or maybe it was 612. They're identical. The carpet is beige. The desk is laminate. The window overlooks a parking lot and, beyond it, a Chili's. I've eaten at that Chili's twice. Both times were mistakes I made out of hunger and proximity. I order room service instead: a burger and a Coke. The burger costs $24 with delivery fee and gratuity. I expense it. The firm's per diem for Houston is $75 per day for meals. The burger is within budget. This is one of the few moments in consulting where the math works in my favor.
Call my girlfriend, Noor. She's in New York. She's a physician assistant at an urgent care clinic in Brooklyn. She works 12-hour shifts three days a week and has four days off. On her days off, she does the things I would do if I were home: grocery shopping, cooking, going to the park, seeing friends. She describes her Tuesday to me and it sounds like a life I have theoretical access to but practical access to only 2.5 days a week. She asks how the steerco went. I tell her about the 45 seconds. She says "that's a lot of flying for 45 seconds." She's right. I don't say she's right because the 45 seconds are the reason the firm charges the client $1.2 million for this engagement and the 45 seconds are the reason I'll eventually get promoted and the promotion is the reason the MBA debt makes sense. I say "yeah, but they were good seconds." She laughs. The laugh is worth more than the per diem.
Open the laptop. Third slide. The strategic positioning map. This is a 2x2 matrix (because everything in consulting is a 2x2 matrix; I once tried a 3x3 and was told it was "too complex for the audience," which is a polite way of saying "executives can only process four quadrants"). The axes are "capital intensity" and "operational efficiency." I plot six companies. The client is in the upper-left quadrant, which in this framework means high capital intensity and moderate efficiency. The "so what" is that the client is spending more than its peers to produce comparable results, which means there's a cost optimization opportunity. I know this. Danielle knows this. Thomas probably knows this intuitively. The slide's job is to make the knowing visible and credible. Data makes intuition defensible. That's the product.
Send the three slides to Danielle. She'll review them in the morning. Close the laptop. Brush teeth. The Marriott toothpaste is a small tube that's identical to every other Marriott toothpaste I've used in two years. I set the alarm for 6:30 AM, which is generous by Monday standards but tomorrow is a client site day with no morning flight, so the extra hour feels like a gift. Turn off the lights. The parking lot is orange under the sodium lamps. The Chili's sign is off. Somewhere in this hotel, Amit and Kira are probably still working. Or they're asleep. Or they're lying in the dark thinking about the model and the chart and the steerco and the Thursday deliverable and wondering if the version of themselves that applied to this job knew what the job actually was. I think about this for approximately four minutes. Then I think about Noor's laugh. Then I sleep.
Paige's Thursday
Paige
N-Judah to the office. I live in the Outer Sunset because it's the only neighborhood in San Francisco where a one-bedroom costs less than my monthly student loan payment. The train takes 38 minutes to the Financial District. I use the time to clear email. 22 messages since midnight. Nine are FYI threads I'm cc'd on. Four are meeting invites. Three require actual responses. Six are from the internal systems (expense report reminders, compliance training due dates, a firm newsletter I've never opened). I respond to the three that need responses and delete the six system emails. The remaining nine FYI threads I skim for anything that affects my work today. Two of them do. The rest I mark as read, which is consulting's version of a polite nod.
Office. Floor 22. The San Francisco office is open plan with assigned neighborhoods but not assigned desks. I sit in the same spot every day: the desk nearest the window in the strategy neighborhood, facing north, with a view of the Transamerica Pyramid and, on clear days, Alcatraz. Today is not clear. The fog is thick and the window shows gray. I set up my laptop, plug in the monitor, and open the three documents that define my Thursday: the project plan for my current engagement (a healthcare payer, virtual, no travel, which is why I'm in the office and not at a client site), a 34-slide deck that needs to be ready for the partner review tomorrow morning, and a proposal for a prospective engagement that the partner, Sandra, asked me to draft by end of day.
First meeting. Weekly team check-in with my case team: two consultants, Ravi and Ines, and one analyst, Tomas. We're in week six of an eight-week engagement helping a mid-size health insurance company redesign their provider network strategy. The work is interesting in the way that consulting work is interesting, which is: the problem is real, the data is messy, and the client's internal politics make the optimal solution politically impossible, so we're engineering a second-best solution that's analytically defensible and organizationally achievable. Ravi walks us through the network adequacy analysis. Ines has the financial impact model. Tomas has a 14-slide appendix of supporting data that will never be presented but must exist in case the client asks a question during the steerco that requires backup. I call this the "iceberg work." The client sees 20% of what we build. The other 80% exists below the waterline, invisible, holding the visible part up.
Solo work block. I'm supposed to have 90 minutes of uninterrupted time to work on the deck for tomorrow's partner review. In practice, I get 40 minutes before a Slack message from Sandra interrupts me. She wants to add a new section to the proposal I'm drafting. The prospective client mentioned "digital health integration" on a call yesterday and Sandra thinks we should include a two-slide perspective on it. I agree it's a good idea. I disagree that it's a good idea today, when I also have a 34-slide deck due tomorrow morning. But Sandra is a partner and my performance review is in April. The math of professional survival always wins. I spend 25 minutes drafting the two new slides for the proposal. Then I go back to the deck. The 90-minute block is now 55 minutes and my coffee is cold.
Meeting two. Client check-in via Zoom. This is a 30-minute call with the client's project lead, a VP named Danette, where we preview what we'll present at next week's steerco. Danette is sharp and direct, which makes these calls efficient but occasionally uncomfortable. She looks at the provider network map and says "this doesn't match what we see internally." This means our data source (a public CMS provider file) disagrees with the client's internal credentialing database. Both are correct. They're just measuring different things. I explain the discrepancy. Danette says "can you reconcile them?" I say "yes." This means Tomas will spend tomorrow running a 40,000-row data match between two databases that use different NPI formatting conventions, and the reconciliation will take approximately eight hours and will change the final numbers by roughly 2%. But the 2% matters because Danette will present these numbers to her CEO and the CEO will ask where they came from and Danette needs to be able to say "they match our internal data." The 2% is a credibility cost, not an analytical cost. We pay it because the alternative is a client who doesn't trust our numbers.
Lunch. The office has a micro-kitchen with snacks, beverages, and a salad bar that rotates between four options, all of which taste like someone described salad to an AI and the AI did its best. I eat a Mediterranean-ish bowl at my desk while reviewing Ines's financial impact model. The model has 18 tabs, 6 scenario toggles, and a dashboard that produces the key output: "network optimization saves the client $23 million annually." That number will appear on slide 8 of the steerco deck in font size 42 inside a navy blue box. Eighteen tabs of Excel compressed into one number in a box. That's the compression ratio for the day. Information goes in large and comes out small and the small version is what the executive remembers.
Meeting three. Internal "practice area" call. This is a monthly meeting where all the managers in the healthcare strategy practice share updates on their engagements. There are 11 of us on the call. Each person gets five minutes. The purpose is ostensibly knowledge sharing. The actual purpose is visibility: letting the senior leadership of the practice see what each manager is working on, how it's going, and implicitly, who should be considered for promotion. I give my five-minute update on the provider network engagement. I use phrases like "on track for deliverable" and "client engaged and responsive" and "potential follow-on opportunity." These phrases are true. They're also curated. The version of this engagement that I describe on the practice call is the version where things are going well. The version where Danette questioned our data and Tomas has an eight-hour reconciliation project and the partner review deck is only 60% done does not make the practice call.
Meetings four and five, back to back. A 30-minute mentoring session with an analyst in a different practice who I was assigned as a "buddy" during his onboarding. He asks good questions. I give honest answers, which is unusual in a firm where most mentoring advice is calibrated for career optimization rather than truth. He asks if consulting is worth it. I say "it depends on what you want it to buy you." He nods. He doesn't know what he wants it to buy him yet. He will in about two years. Then a 30-minute meeting with the proposal team for the prospective engagement. Sandra walks us through the client's priorities. I present the two slides I drafted this morning. She says "good, add one more on the implementation approach." That's three more slides, total, due tomorrow. The deck for partner review is now competing for time with the proposal. Both are due tomorrow. One is my job. The other is my future. I need to do both.
Solo work. The office is at its afternoon energy level, which in consulting is the period between the last meeting and the beginning of the evening work session. People are at their desks, headphones on, typing. The open plan means I can see 40 people from my seat, all doing some version of what I'm doing: building decks, updating models, responding to Slack messages, and occasionally staring at the fog through the window while their brains process something they can't type yet. I work on the partner review deck. Slides 12 through 22. Each slide takes 15 to 30 minutes. The ones with charts take longer because the formatting in PowerPoint is adversarial. PowerPoint does not want the chart to look the way I want the chart to look. We negotiate. PowerPoint usually wins.
The office thins out. Ravi leaves at 5:45. Ines left at 5:30. Tomas is still here because he's 24 and doesn't have anywhere he needs to be, which is the honest truth about why junior consultants work late: not because the firm demands it (it mostly doesn't, explicitly), but because the alternative is going home to an apartment where your roommate is also a consultant who's also still at the office. I stay until 6:30 finishing the deck. Twenty-eight of 34 slides done. The remaining six I'll finish at home tonight between 8 and 10 PM, after I eat something and pretend to have an evening.
N-Judah home. The fog hasn't lifted. The train is half empty, which is one of the small mercies of leaving the office at 6:30 instead of 5:30. I stand near the door and look at my phone. Esteban texted at 4: "Dinner?" I respond: "Yes but after 8, working late." He responds with a thumbs-up emoji. The thumbs-up is the emoji of a person who has accepted something they don't love but won't fight about because fighting about it doesn't change the meeting schedule. I get home at 7:40. The apartment smells like garlic, which means Esteban is cooking, which means dinner is being handled and I can sit on the couch for 15 minutes and be a person. Being a person for 15 minutes before becoming a slide machine again is the bargain I've made with this career. Some days the bargain feels fair. Today it feels like a Thursday.
Dinner. Pasta with garlic and broccoli rabe. Esteban tells me about a student who wrote a personal essay about his dog that made the whole class cry. I tell him about the 2% data reconciliation. He says "that sounds important" in the tone of a person who is being kind about something he doesn't fully understand. I love him for this. After dinner I clear the table, open the laptop, and finish slides 29 through 34. The deck is done at 9:50 PM. I send it to Sandra with a note that says "ready for review." She responds at 10:04 PM with "thanks, will look in the AM." I close the laptop. The day contained seven meetings, approximately 14 hours of work if you count the train email time, three distinct work products, and one dinner with a person I love who deserves more than the 40 minutes I gave him between the garlic and the laptop. I turn off the lights. The fog is still there. Tomorrow is Friday.
Oscar's Wednesday
Oscar
Up. Coffee. My wife, Theresa, is already awake because our son, Ben, is four and four-year-olds have no concept of reasonable wake-up times. Ben is eating cereal and watching something animated that involves a talking dog. I drink coffee and review my notes from yesterday's data pull. I pulled production data from the plant's ERP system (SAP) for the last 18 months. The data is in a spreadsheet that has 14,600 rows and 23 columns. Each row is a production run. Each column is a metric: start time, end time, product SKU, line number, quantity produced, quantity rejected, downtime minutes, downtime reason code, changeover start, changeover end, operator ID, and twelve other fields that matter to someone but not to me today. Today I'm looking at three columns: changeover start, changeover end, and product SKU. I'm trying to answer one question: how long does it take this plant to switch from one product to another, and does the time vary by product type? This sounds simple. It took me four hours yesterday to clean the data enough to ask the question because the changeover reason codes are inconsistent (sometimes "changeover" is coded as "CHNG," sometimes as "C/O," sometimes as "setup," and once, memorably, as "Gary went to lunch"). Gary, I've learned, is the line lead on Line 3.
Drive to Chillicothe. 90 minutes from Cleveland. I-71 South to US-23. The drive is flat, agricultural, and meditative. I listen to a podcast about lean manufacturing that Theresa finds deeply boring and that I find mildly interesting, which is the precise interest level required for a 90-minute commute. Brown steel-toed boots in the passenger seat. I put them on in the parking lot. The plant is a single-story building, about 180,000 square feet, surrounded by a gravel lot and a loading dock with four bays. The air smells like carbonation and industrial cleaner. I've been here for three weeks. I know where the good bathroom is (the one near the maintenance office, not the one near the break room). I know which vending machine takes cards (only the one on the east side). I know that the plant manager, Dan Kowalski, arrives at 6 AM and is in a better mood if you don't approach him before his second coffee, which happens around 7:15.
Dan's office. Dan is 52, has been plant manager for nine years, and has been at this company for 24. He knows more about bottling operations than I will ever know. He also knows that I'm here because the PE firm that owns the company sent me, which means, in Dan's calculus, that I'm either going to help him or get him fired. He hasn't decided which one yet. We're three weeks in and the relationship is at the stage I call "cautious cooperation," which is the stage after "hostile skepticism" and before "grudging respect." Grudging respect usually arrives around week six when the data starts showing results and the plant manager realizes I'm not here to replace him. I'm here to make his plant more profitable so the PE firm doesn't close it, which is the same goal he has. We just got there from different directions.
I show Dan my changeover analysis. The average changeover on Line 2 is 2.7 hours. On Line 4, it's 3.4 hours. The difference is partially product mix (Line 4 runs more SKUs, which means more frequent changeovers between dissimilar products) and partially procedure (Line 4 doesn't use a standardized changeover checklist, which means each operator does it differently). Dan looks at the numbers. He doesn't dispute them. He says "Line 4 has always been slower." I say "it doesn't have to be." He looks at me. This is the moment in every engagement where the plant manager decides whether the consultant is worth listening to. It lasts about three seconds. Dan says "what do you have in mind?"
Line 4. I'm standing next to the changeover that's happening right now. They're switching from 12-ounce PET bottles of a lemon-lime SKU to 20-ounce PET bottles of a cola SKU. The changeover involves: draining the flavor system, flushing the lines, adjusting the filler heads for the different bottle diameter, swapping the cap chute, changing the label roll, recalibrating the fill volume sensor, and running a test batch of approximately 200 bottles that get inspected and then dumped. I'm timing each step with my phone. The drain and flush takes 22 minutes. The filler head adjustment takes 38 minutes. The cap chute swap takes 12 minutes. The label change takes 18 minutes. Calibration and test batch: 35 minutes. Cleanup between steps: 27 minutes. Total: 2 hours and 32 minutes. That's better than the 3.4-hour average, which means this changeover is faster than average, which means some changeovers are significantly longer than 3.4 hours, which means the variance is the story, not the average.
I talk to the operator, a woman named Rosa, who's been on this line for seven years. She's fast. She's efficient. She knows where every tool is and she doesn't waste motion. I ask her what slows down the changeovers she doesn't do. She says "waiting." I ask what she's waiting for. She says "maintenance. When the filler heads stick, I call maintenance, and sometimes they come in 10 minutes and sometimes they come in 40. Depends on who's on shift." This is the kind of insight you can't get from SAP data. SAP tells me the changeover took 3.4 hours. Rosa tells me why.
Back in the conference room the plant gave me (a small room near the break room with a table, two chairs, and a whiteboard that has "DO NOT ERASE" written in red marker on the top right corner, referencing notes from a meeting that happened before I arrived and that no one can identify). I update my changeover tracking spreadsheet with this morning's observations. I add a column for "wait time for maintenance" based on Rosa's input. I'll need to pull the maintenance response time data from the work order system, which is a separate system from SAP (it's called Fiix, and it runs on a tablet that the maintenance supervisor, a man named Hector, carries around and sometimes forgets in his truck). The data integration challenge in manufacturing consulting is that the systems don't talk to each other. Production is in SAP. Maintenance is in Fiix. Quality is in a spreadsheet that the QA manager, Linda, updates manually. Scheduling is in Dave's head, which is not a system I can query.
Lunch. I eat a sandwich I brought from home, standing next to the palletizer on Line 2, watching the cases stack. This sounds uncomfortable and it is. But the palletizer area is where the line leads gather during lunch, and the conversations they have while eating are the most useful data source in the building. Today, Gary (Line 3 lead, the one whose lunch break shows up as a changeover reason code) tells me that Line 4's filler heads have needed replacement for eight months and the capital request keeps getting deferred. This is why the filler heads stick. This is why Rosa waits for maintenance. This is why the changeover average is 3.4 hours instead of 2.5. An $18,000 capital expenditure for new filler heads would save approximately 45 minutes per changeover, which at 4 changeovers per day on Line 4 is 3 hours of recaptured production time per day, which at this plant's margin per production hour is roughly $1,200 per day or $312,000 annually. The ROI on an $18,000 filler head replacement is approximately 17x in the first year. This number will go in my slide deck. The fact that I learned it while eating a turkey sandwich next to a palletizer will not.
Meeting with Dan and the VP of Operations, Sandra, who's visiting from corporate headquarters in Columbus. Sandra is here because the PE firm asked her to assess the Chillicothe plant's improvement potential. This is consulting theater at its finest: I'm presenting findings to the VP that will be presented to the PE firm that hired my firm to produce findings for the VP. The circle of accountability in PE-backed manufacturing consulting is a snake eating its own tail, and everyone in the room knows it, and nobody says it, because saying it would collapse the polite fiction that makes the engagement function.
I present the changeover data. Dan sits next to me, which is new. Three weeks ago, he sat across the table. The position change is significant. Sitting next to someone in a meeting with your boss is a signal: this person is on my team. I don't comment on it. I notice it. Sandra asks good questions. She asks about the filler heads. I present the $18,000 versus $312,000 math. She writes it down. Dan nods. Sandra says "why hasn't this been done?" Dan says "the capex request was submitted in August." Sandra looks at him. He looks at her. Something passes between them that has nothing to do with me and everything to do with a capital allocation process that deferred an $18,000 request for eight months while the plant lost $260,000 in changeover inefficiency. I stay quiet. Sometimes the most valuable thing a consultant can do is present a number and let the silence do the work.
Back in the conference room. I update my working deck with today's findings. Add the filler head slide. Add the maintenance response time data request. Write three bullets for the weekly update email to the engagement manager at my firm, Nadine, who is in Cleveland and manages the relationship with the PE firm. The bullets are: (1) changeover variance driven by maintenance response time, root cause identified as deferred filler head capex, (2) presented ROI case to VP of Ops, received positive reception, (3) next step: full maintenance response time analysis from Fiix data, expected completion Friday. These three bullets represent eight hours of work, one sandwich next to a palletizer, and three weeks of building a relationship with Dan Kowalski that progressed from hostile skepticism to him sitting next to me in a meeting. The bullets don't capture the relationship. Bullets never do.
Leave the plant. Brown boots off, sneakers on. Drive back to Cleveland. 90 minutes. The podcast is over. I call Theresa. Ben wants to tell me about a ladybug he found at preschool. He describes the ladybug for approximately four minutes with the detail and precision of a field biologist. He says it had "seven spots on one side and maybe seven on the other side but I couldn't count because it flew away." I tell him that ladybugs can have different numbers of spots and that some have no spots at all. He finds this deeply unsettling. Theresa takes the phone back and asks how the plant was. I say "good, Dan sat next to me in the meeting." She says "that's big." She knows it's big because I've been talking about Dan for three weeks and she's absorbed enough context to understand what the seating arrangement means. She's a middle school guidance counselor. She understands the politics of where people sit. I get home at 6:30. Ben shows me where the ladybug was. The spot is a leaf in the backyard that looks like every other leaf. I look at it with the seriousness it deserves. Then we go inside and eat dinner and I don't open my laptop until 8:30, which in this job is the closest thing to a boundary I know how to draw.
Frequently Asked Questions
What does a management consultant do on a typical day?
A typical day varies significantly by firm type and project phase. MBB and Big 4 consultants on client engagements generally fly to the client site on Monday morning, work 10 to 14 hour days with a mix of data analysis, stakeholder interviews, and slide building, then fly home Thursday evening. Boutique consultants may spend full days at client facilities conducting operational assessments. Across all types, documentation and slide building typically consume 40 to 60 percent of the day.
Do management consultants work from home?
Work arrangements vary by firm and engagement. Many firms have adopted hybrid models where consultants spend 2 to 3 days per week at the client site instead of the traditional 4 days. Some engagements are conducted entirely from the firm's office. On days when consultants work from home or the office, the work hours are often similar to on-site days.
How much do management consultants travel?
Traditional consulting travel is Monday through Thursday at the client site, 3 to 4 nights per week in hotels. Post-2020, many firms offer hybrid arrangements. Boutique firms with regional clients may require less overnight travel but more day trips. Most consultants report that travel is manageable for 2 to 3 years and becomes unsustainable after 4 to 5 years.