Archery Hunters Will Use Cheaper Gear

It’s no secret, hunting gear (clothes included) seem to rise every year. Is it inflation? Is it greed? Just how it is? Regardless, gear is now becoming a luxury. With the U.S. average salary around $63,000, you can see how buying four climbing steps for $500 just isn’t going to fit the budget. The reality here is that you don’t need expensive gear to kill deer. And because of that reason, I believe hunters are going to use what they have already or buy cheaper gear for the field.

Archery Hunters Will Hunt Lower

I don’t think anyone knows where the true legend of why you need be 20 feet in the air while bowhunting. However, I think it’s safe to say the real answer to “how high” is “it depends”. I’ve been a long believer that you always need to be higher than 20 feet to not be in a whitetail’s vision, but I’m rethinking that. Especially since last year when I harvested 8-point 5 feet off the ground (see video below). So maybe it’s more so how do you blend in versus being out of view completely.

Another perspective is that hunting low reduces the risk of serious injury, setup and take down time. This allows one to be more mobile in my opinion. Having said that, hunting low also poses a completely new challenge of hunting as well. If you’re interested in hunting lower, there are popular hunters such as Cody D’Acquisto that explain well why you don’t need to be two stories high all the time.

Also, climbing low means less steps you need to buy to climb – so it’s a money saver too.

Archery Hunters Will Dabble in Traditional Bows

Like hunting low, traditional bows have started to become popular as well. I think the challenge of killing a deer with one of these weapons, like a triad, will be the next step in many matured hunting careers. Full transparency, I do believe that once people realize how difficult it is, the trend will soon shift back to compound and crossbows; thus the “dabble” in the headline.

Killing Bucks without Tech Is the New Brag

As the hunting sector become flooded with technology such as cell cameras and drones, it has made hunting big bucks somewhat easier. With that being said, I think the new brag will be people saying they killed their buck without such technology. In tandem with reducing tech use in the woods, I believe woodsmanship will start to creep back into today’s hunters’ skillsets as well. In short, I think more people will be analyzing deer droppings and tracks than waiting at home for pictures on their phone.

Next 6-7 Years is Prime Time for Killing Big Bucks

This prediction is a little out there and quite honestly just a personal life anecdote. I believe that if you want to kill a big buck, especially on public land, the next 6-7 years are going to be a good time. Why? Because there are going to be less hunters out there.

Don’t get it twisted though. The drop in hunters is not because of loss or lack of interest; it revolves around the fact that millennials are starting to have families, new babies, work, and careers. These individuals do have a passion for hunting but will prioritize life – again – for the next few years until they have less responsibilities. On top of that, the boomers are getting older. So, hunting pressure in theory, would decrease, leaving you with more land to hunt.

And there you have it, five predictions about the future of archery hunting. Hopefully you enjoyed it!

Be Comfortable with Change

Photo by le vy: https://www.pexels.com/photo/red-and-green-tree-leaves-on-a-sunny-day-668553/

While you don’t necessarily need to be comfortable with change, you at least need to come to grips with the fact that it is omnipresent. Change is going to be encountered in all areas of your work: the software you use, the team you have, the requirements of the project, even your current responsibility and roles.

If you spend your hours complaining about every change that happens in a day, you’ll probably never have any time to do the actual work. Though easier said than done, something that may help is to view through an opportunity lens for each curveball that comes your way. Instead of complaining about what problems change is causing, see it as a chance to make the work or outcome better. This idea might even be mentally healthier for you as well.

Communication Skills

Photo by SevenStorm JUHASZIMRUS: https://www.pexels.com/photo/123-let-s-go-imaginary-text-704767/

Another important thing I learned was that you need to be well-versed in communication. This means utilizing soft skills, being able to provide clarity in ambiguity, and communicating clearly in various channels such as email or instant messaging tools.

Looking back in my career, I’ve worked with individuals that have hardcore opinions in the IT world, but it’s still scoped relatively to IT topics. As a TPM though, I’m working with a litany of different areas such as management, legal, and people from all over the world. These are people from completely different cultures, backgrounds, and may have personal issues I’m not aware of. You can imagine the differences of lingo, energy, and formalities in meetings. Boil it down, being good at talking or writing with anyone is vital to keep conversations efficient and productive.

It’s All About Systems

Photo by Aleksejs Bergmanis: https://www.pexels.com/photo/aerial-photo-of-buildings-and-roads-681335/

And to help manage the constant state of change and ensure everyone stays aligned, I believe it comes down to systems. I found if you don’t develop systems, it can be exhausting to work in a reactive state. One key thing about successful systems though is that they need to be updated as projects mature. They can be great one day, but if you don’t adapt, you’ll find gaps start to form in the work.

Conclusion

After writing this, I thought about another topic I should touch on, and that is to ask for help. I know damn well I’m just starting out in this role, and I have no idea what I’m doing. I’m learning on the job as they say and it’s imperative for me to learn as much and as fast as I can. With that being said, I’m looking forward to all the experiences and learning lessons coming my way.

Thanks for reading!

I’ve been at Ford Motor Company for almost three years now; I was hired in as a connected vehicle data engineer and am now a prognostics technical program manager (TPM). Within that time, I can honestly say that this has been one of the best places I’ve worked at. Though there are many reasons of enjoyment, there are three areas I tend to appreciate most: learning about different cultures, the ever-changing landscape, and the different work opportunities available.  

Learning About Different Cultures

If you don’t know, I am a first-generation U.S. born Hmong American. My parents and a few of my siblings are refugees that fled from the Vietnam/Secret War. Though they have assimilated well to the American way, they never forgot about the original Hmong traditions and made sure I knew about it too. Now, I’m not sure if my proclivity to learn about culture is innate or just beat into my brain, but I do love to learn about mine and others as well.

One of the benefits of working in a multinational conglomerate is that you are afforded the opportunity to work with individuals from all over the world; Canada, Germany, China, Brazil, and India to name a few. Because of that, you get the chance (if you try) to take a glimpse into a myriad of unique cultures and lifestyles. You get to hear about the “real” things that go on in other countries; good and bad.

Photo by Quang Nguyen Vinh

A few good things I’ve learned: I learned about how some families don’t have televisions to aid their children in learning their mother tongue faster. I learned about what luthiers do (people that make string instruments). I learned about all different types of slang in other countries such as “scoops” for adult beverages in the U.K. And maybe one of my favorites, how a family moved to Brazil and changed their last name to avoid association to war.

Don’t know what it is, but something about hearing it personally just hits different than a National Geographic episode.

Ever-Changing Landscape

Photo by Pixabay

Like many (if not all) other industry sectors, the automobile space is ever-changing. Though change may seem bad and have a negative connotation associated with it; when viewed through an opportunity lens, it may be the best thing since sliced bread. Having said that, I agree – constant change can generate ambiguity, unknowns, and chaos. However, with the right team and plan, leveraging change can deliver growth, good disruption, and success. And why does this matter to me? Because it means the work is not boring for me.

I personally struggle to work well when I’m doing repetitive or mundane tasks. I will zone out, wonder about random things like why people put an “s” when they say “Meijer”, and don’t get any sense of fulfillment. However, if you throw me in the deep end and tell me to sink or swim on solving a problem, I don’t have a solution for, I am invigorated.

We need to deliver 30 new feature visualizations from scratch in Amplitude – bet!

We need to move everything from Amplitude to GCP – bet!

Oh, and you need to do all of that yourself – bet!

(bet in this context is slang for expressing confidence that I’ll complete the task)

All that to say, change can be good if that’s your jam. And quote honestly, if you want to stay (not be) successful in what you do, it’s kind of a requirement.

Work Opportunities

Photo by Pixabay

As stated earlier, I was originally hired at Ford Motor Company as a connected vehicle data engineer. Though it was stimulating work, I felt I could’ve provided more impact for the company. Eventually, there was an opportunity to move into a space where I could deliver more impact as a TPM, and that’s where I am now. Honestly, the stars kind of aligned for me – right place, right time. Having said that, there was (and still is) an absurd number of opportunities that I could have tried to capitalize on.

As the prior topic stated, the landscape at Ford is always changing. That ultimately requires new opportunities in all different areas that you may not have even thought about. For instance, you can do software engineering, vehicle uplifts for the government, performance racing, environmental benefits with electric vehicles, or just good ‘ole project management. The opportunities are endless if you think about it.

Conclusion

Ford and it’s employees are awesome. I get to learn about other people’s cultures, the work keeps you sharp, and you probably can work in an area of interest.

Thanks for reading!

Licenses

First, let’s talk about hunting licenses. In Michigan, after the purchase of a base license for $10, the average Joe can purchase up to 12 whitetail tags at $20 a pop; a combo license that allows you to harvest two bucks and 10 universal antlerless licenses (otherwise known as doe tags). According to the Michigan Department of Natural Resources (DNR), in 2022, there was an estimated 516,336 hunters that were issued licenses at an average of 2.2 (fun fact, I personally average four tags a year). Round it up, I’ll call it total of three tags, which I am assuming is a combo and a doe. (Side thought – I’m presuming people are purchasing the combo because there are certain DMUs that allow you to tag a buck or doe, depending on the season). 

• Base License – $10
• Combo Deer License – $40 
• Antlerless Deer License – $20

Total: $70

Hunting Gear

Secondly, now that people have purchased their licenses, let’s talk about everything else you need to hunt. I’m referring to guns and bullets, bows, arrows, broadheads, and awesome camouflage clothes. Assuming this is a new hunter that is going to hunt archery and gun seasons, I’m going to ballpark some of these items:

• Gun – $500
• Ammunition – $2/round @ 20 rounds a box = $40
• Bow – $700
• Arrows – $100
• Broadheads – $60
• Hunting Clothes – $500 (this is bare bones cheapest clothes that will get you through all seasons)

Total: $1,900

The Trip

Thirdly, you probably aren’t going to drive an electric vehicle to the woods, yet. Therefore, I’m going to assume you’ll need gas for your car, you’ll need snacks when you get to the gas station, food for the trip, hotels/AirBnB/housing, and other items to get to your destination, survive, and get back home. Again, I’ll ballpark for a two day trip where one way is 100 miles:

• Gas – $3/gallon * ( 100 Mile Trip / 20 MPG ) * 2 Trips (to the woods and back) = $30
• Snacks – $20
• Food – $50
• Housing – $100/night

Total: $200

The Post-Hunt Services

Fourthly, now that you killed two 180” bucks and a monster 5 year old doe, you may be in need of taxidermist or processing services. For simplicity and a bit of reality, I’m going to calculate services for one of the bucks:

• Taxidermist – $600
• Processing – $200

Total: $800

Conclusion

Now, if you add up all the totals, you’ll get something like $2,970 for a very successful two day whitetail hunting trip in Michigan – for someone that needs to buy everything new. It can be argued that items such as bullets/arrows/clothing can last a long time. Regardless, the $2,970 may not seem like a lot. However, if you multiply only the cost of a base license with three deer licenses for the 516,336 Michigan hunters in 2022, that’s $36,143,520 alone! And that is why hunting is good for the economy. Imagine including all the other items listed above for each hunter.

Also, after writing this post, I’ve come to realize that even though most of the time I’m sitting during the hunting season, these costs are precisely why I’m penniless.

It’s the 2:30 PM on October 1st and it’s pushing 80 degrees. The light blue sky has a handful of clouds but the sun’s heat is still making me excessively sweat. I’m contemplating whether it’s worth the effort in hunting tonight, but I make the decision to go to the edge of a swamp that borders a horseshoe looking pond. The only intel I have from a previous speed-scout mission is an old rub a single hoof-print. 

I slip on my rubber boots, throw my Lone Wolf Custom Gear (LWCG) .5 stand on my back, and start making my way into the woods. I slowly creep through the lowland deciduous area until I reach my tree. By this time, I’m assuming mosquitoes have sucked nearly 30% of my blood through their proboscis. When I unpack all of my gear, I realize this is my first time climbing a tree with the LWCG and Tethrd One sticks. In previous years, I would’ve finagled my way to complete my setup as quick as possible. However, I decide to take my time to develop a new repeatable process for the future. Probably an hour later, I’m finally sitting in my stand and ready to hunt. 

Some time has passed and I’ve only seen a squirrel feeding on acorns at the very top of an oak tree. I’m thinking that maybe two hours have passed; I look at my phone and it’s only 4:30. I sigh, whisper some cuss words, and chalk it up to the heat affecting my perception. Becoming squirmy, I figured I’d stand but I realize my LWCG sidekick is attached to my seat so I can’t lift my seat. If I do, I don’t have anything to hold my bow. Feeling more frustrated, I find myself moving around way too much for deer hunting and decide to hold my bow in my hand for the time being so I can stand. 

Eventually, I cool down mentally but the sun’s heat still remains. Around 6:00 PM, I catch a doe moving in the swamp; it’s headed directly towards me. I thought, this is my chance to shoot something on camera. I point my camera in the direction I expect the doe to come out of and patiently wait. Ten minutes later, nothing shows up and I’m a little discouraged. But what do you know, just as I give up, I see the doe slowly making its way into this little acorn patch. As I’m watching it, I notice that even though the leaves are dry, the deer’s footsteps make no sound; it’s mind-boggling. I shake out of my self-talk and turn the camera on. I find it incredibly difficult to capture the deer in frame, all while trying to get ready for the shot. It’s either I draw my bow and the doe is out of my camera’s view or the deer is finally in frame but I can’t make a move. Eventually the deer wanders off in the thicket and I wallow in my hunting videography skills.

It wasn’t until 7:00 PM until I saw the next deer. It was a shooter 8-point buck that made a circle around me. Mind-blown that he didn’t venture through thick cover, but instead, traveled through the most open area. My thought of being in my location was to border thick trails and use the horseshoe shaped pond and the swamp as a pinch point; but I didn’t consider deer would use the very edge of the pond as a trail. Just 10 yards out of my comfort zone, I couldn’t believe it. I watched as it slowly made its way around me, stopping every few steps to check for danger by looking off in the distance and smelling the wind with its nose. Again, I wallow, but in my poor tree selection. 

Quickly after the buck disappears, a group of does make their way through opposite of the buck. I no longer have interest in anything without antlers – at least the size of the 8-point. I sit and watch the does graze until dark. I turn on my headlamp, make my way down the tree, pack up, and walk towards my truck to head home.

Though no arrows were released from my bow, it was still pretty cool to have all those deer encounters. Frustrated in a tree is probably a lot better than doing many other things. 

Until the next hunt.

I get to his house house, we leave, and half-way into the drive, the winter storm comes. The roads are starting to become icy and there’s about 20 yards of visibility through the falling snow. All of us are already thinking “we should turn around and call it quits”. But then, on the other hand, we’re already halfway, why not just keep going since it’ll take the same amount of time to get home as it will to get to Grand Rapids? We all decide to proceed and hope for the best.

We eventually make it. It’s about 6:30 AM and I see a couple boats already on the river. The wind and snow is blowing at near tornado speeds, the cloudy skies are still making it dark, and I’m trying to slip the end of a 6 pound fluorocarbon leader through the eye of a size 6 Raven Speciality Hook using the dim lit streetlight. At this point, I have no idea why we’re out here, but I proceed to get my Lamiglas Redline pole set up and start fishing.

For about two hours, I’m moving up and down the bank trying all different egg patterns, hook sizes, leaders, colors, variations – you name it; nothing seems to be working. By this time, the river has a considerable amount of boats, but no one seems to have solved what the fish want yet. Even so, I try to enjoy the brisk weather and the beautiful sound of people arguing – my guess is that someone has parked their boat a little too close to someone else’s. In my opinion, the shouting adds that perfect touch, the chef’s kiss, to fishing in a concrete jungle.

Thankfully, within the next hour, I notice the boats are starting to net fish. I’m thinking maybe the fish gods have granted us a window of opportunity. I clear some line off my reel and reset everything. I pull out my go to setup, drift fishing an 8mm Bloop Master Roeshi bead on a size 6 Raven Speciality Hook. A few casts later, I’ve got my first steelie on.

It peels 30 yards off my reel and we end up at a standstill for a minute or so. I’m trying to pull this buck in, but he won’t budge – he’s also leveraging the river current to his advantage. I notice boats starting to move around and I didn’t want my line to get caught by them, so I do a quick little prayer in hopes my line doesn’t snap and I start forcing this fish in. A few minutes later, I’ve got a fresh steelie on land and I feel like a million bucks.

After resetting my Lamiglas pole with the same setup, I cast a handful of times, and I’m on again! I’m thinking to myself what are the odds of catching TWO steelies this quick? After I set the hook, I see this hen leap out of the water as if it was trying to jump over the dam itself. It makes a quick 15 yard run, but I go back to my previous strategy and force this fish in before my line is caught by any moving boats. After a few minutes, I’ve got a beautiful silver bullet hen in a net. What success.

After that, I felt like my day was complete. I slowly reset my gear and take a five minute breather by conversing with my neighboring fisherman that came all the way from Detroit. I told him that it’s cool with me if he wants to come closer. It seems the fish are on my side of the drift anyway. I also enjoy watching other people catch fish. After some conversation, I cast and as I’m ready to start reeling in – fish on!

I’m laughing at myself for two reasons. First, how ignorant I may look to others for catching fish so quickly. If I saw myself, I’d be thinking there was some illegal snagging going on. And secondly, I’m cracking up because I’ve never been so lucky before; I’m confident this has nothing to do with skill at this point. Anyway, like the first hen, this second hen does a ton of splashing and spinning, but I eventually get it in the net. I had my three for the day and told my neighbor to come fish my spot and wished him luck. I think he might’ve actually had a couple on, but couldn’t bring them in.

My buddies fish for a couple of hours and decide to call it. Before I left, I had to take a quick picture of this ridiculous trip:

Thanks for reading! Tight lines, everyone!

The Data

In an EAV model, data would look something like this:

Using Pivot Function

Using the pivot function in T-SQL, your code would look something like this:

The logic is simple enough to understand, but you would need to kind of double the work to ensure your source query has all the attributes and also list them in the pivot query. You would also need to ensure your aggregate function works with your data. For instance, MAX() wouldn’t work with bits.

Using Max Function and Case Statements

The second way, which is kind of a hack way in my opinion, is to create a case statement for each attribute and then do a max function on each case statement. Here’s the first step broken down:

Adding the max function allows you to pull forward the maximum value for each column/attribute because all the other rows should be blank or null:

This way is a little more intuitive in my opinion and I find that it’s easier to join this data to other queries. This pattern wouldn’t work though if you have more than one row for each attribute per grouping. However, if that’s the case, your EAV model probably needs some changes.

Hopefully that helps. Happy coding!

The First Trip

The target river was the Pere Marquette. I honestly don’t fish this popular river much, so I had to reach out to my buddy Justin for one of his spots because I had no idea where to go – so thanks Ja! The idea was to get to a spot on the river before the sun came out so I could make the hike and hit a handful of areas I thought seemed like they were holding fish. I only had until around noon before I needed to make the drive back home. At a minimum, even if I didn’t fish, I wanted to at least find some areas for future fishing trips. Plan was set, all I had to do was carry it out.

It was around 4:00 AM and I’m already in my truck, ready to go. I type in the spot that I want to go into my map app and start taking off. Long story short, it wasn’t the correct spot at all. I ended up on the side of the road, adjacent to someone’s private property. At that point, I had no internet service so I couldn’t remap to where I needed to be. I just knew I had to go north, so that’s what I did.

Unfortunately, going north wasn’t working because I ended up getting stuck at deadends in these small lakeside neighborhoods. Thankfully, forty-five minutes later, my driving leads me to the top of a hill where I received internet service. I plug in my correct spot and take off. By the time I get to where I wanted to go, the sun was out and parking lot was half-full.

Even though I was late, I still managed to get out to a couple of spots I wanted to check out. I also managed to get a snapshot of this part of the water:

The Second Trip

It’s early February and I reach out to a few of my friends to see if they want to tag along. Only one of my buddies had time to go. So 4:30 AM, we’re already on the road. We’re thinking it’s going to be cold, there won’t be a lot of people there, and we should be the first people there. After nearly a 3 hour drive, there were already two vehicles in the parking lot; I applaud them of their dedication.

It’s about 7:30ish and the temperature was hovering around 12 degrees fahrenheit; quit chilly. I honestly didn’t dress for this temperature, but in my defense, the weatherman said mid 40’s. I figured I’d just keep moving around to keep my body warm.

So we set up our gear and head to the water. I’ve got the jitters because the water looks superb and I’m overly excited to get my line wet. Some two hours later, I’ve switched my leader to three different poundages, I’ve used every color bead in my arsenal, and I’ve gone through every type of my fly in my selection – no fish. I didn’t feel too bad though because it seemed like everyone else on the river had the same luck as I did. Regardless, I keep on fishing. Not sure what else to do, I slip on an 8mm Bloop Master Roeshi bead and tie on a size 4 Raven Speciality Hook. A few casts later, I slip on some snow on the rocks I was standing on so body naturally falls backwards. Long behold, this same movement accidentally sets a hook on a fish and I’m on! Honestly, it wasn’t a great fight, but it did take me five minutes to pull in this buck:

Excuse my amateur photos, it’s merely for a little context.

So now my spirits are up, thinking the fish are going to turn on. Three hours later with no bites, I’m contemplating whether there is any more fish in the river. Maybe I caught the only one? Thus far, I’ve only see one other pull in a fish. Is it still worth fishing? I then remember this trip is nearly a miracle, so I talk myself into figuring out what to use.

I look into my bag and realize I forgot I had tied some Pink/Fireball Pautzke’s Fire Balls. I figured, “why not?”. I hook one on and a few casts later, I can see that I’ve got a fresh steelie on the end of the line. It was an odd fight though. I was looking at my line and it was straight across me, but the fish was 45 degrees down river from me. Come to find out, my swivel caught someone else’s stuck dead line in the water. At one point I couldn’t reel in the fish anymore.

My buddy sees that I’ve got a fish on and runs over. The hen is not hovering on the edge of the drop off where shallow turns to deep. I honestly thought I might as well just break my line cause there’s no way to physically pull in the fish closer. As I’m still debating though, the fish gods had my back and the steelie for towards the shore and my buddy scoops him up. What luck. I didn’t take pictures by the water, but you can still see the silver on this after I got home:

And that concludes my first two steelheading trips of 2023. Huge fails, couple of lucky fish, and memories to share. Can’t really ask for more. Hopefully you enjoyed my stories and there are more trips this year!

Happy fishing!

Full transparency, most of my data career has been in a centralized team or a group that manages most data-related requests in a specific way. Having said that, I have some assumptions of pros and cons of working in decentralized teams.

Pros and Cons of a Centralized Team

As stated previously, most of my career was (and still) in a centralized team of some fashion. The types of teams I’m thinking are ones that are developing data products for the entire company and teams that handle data requests from all areas of the company.

Pro: Control of Data Ecosystem

When your team manages most of the data going in and out of a data product, there’s a high probability that you’ll have the upper hand on most decisions for the ecosystem. By having control, you’ll have transparency on any issue or proposal that can dramatically alter the ecosystem. You can also make decisions that is best from a data perspective.

Pro: Less Likelihood of Duplicated Work

With a centralized team, tasks should be vetted before being approved for work. In the event a new task comes down the pipeline that has already been done or has some similarity to previous work, it can be flagged as a duplicate and tossed out. Having a pinch-point for tasks can make it easier to avoid duplicate work.

Pro: Have People to Share Work With

Having a team or a colleague that has some familiarity with your work is a huge benefit. In the event that you need to take a vacation because of burnout, have too much work, or just don’t want to work on something; it can be easier to pass on the work to someone else. The opposite is possible too – maybe you take on all of part of the work from your team member.

Con: Many Different Types of Contexts

When your team is the only data team in the company or the only team doing a particular ‘thing’, there’s a high chance that you’ll be working on tasks from many different domains. Context changing across multiple departments can be challenging and honestly inefficient when it comes to completing work. The mini-ramp ups that you do to remind yourself of what you were doing may seem to take a little time, but multiply that across the number of subjects you have – it can be a decent amount of time used for the workday.

Con: Less Time to Learn About New Things

Again, with the amount of workload coming down the pipeline, there may not be as much time for professional development or time to “think outside the box”. Often times, if an architecture pattern solution works, it’s implemented over and over in order to accomplish tasks. Sometimes it’s hard to find that time to try and do something new that can provide more value or efficiency.

Con: Slower to Complete Tasks

When managing a big data landscape, there tends to be vague requirements from internal customers or unforeseen obstacles when trying to finish tasks. You’ll run into issues such as customers not knowing what they really want until they see something they don’t want. The other thing could be when you’re working and you find something can’t be done that was already promised. In any event, there tends to be more hurdles that need to be cleared prior to finishing the work.

Pros and Cons of Decentralized Teams

Stated before, I don’t have much experience in this realm, but I can imagine about some of the good and bad.

Pro: More Focus on Less Topics

In contrast to being on a team that “does everything”, being on team that has a luxury of pure focus on one topic or a couple of topics makes it easy stay focused on the work. This also allows one to build that muscle memory for the topic which makes it quicker to recollect most things that are related to the subject. Unless you have an incredible functioning brain, it can be difficult to perform well when you need to context switch between an infinite amount of subjects.

Pro: Easier to Expand on Current or Previous Work

Extending off the previous point, because you build that muscle memory, it can be easier to make changes to the work you’re currently working on or any previous work you’ve done. The ramp up time won’t be as much if you need a little reminder on how things work.

Pro: Complete Things Faster

Again, extending on the first point, more focus and less topic changing can make you more efficient. This should lead to faster task completion.

Con: High-Likelihood of Duplicated Work

Because you’re focused on what you’re doing, you may be doing the same thing as someone else on a different team. In actuality, it may be that you have different reasons for the outcome, but the work itself may be similar.

Con: Lack of Standards

Standards, love ’em and hate ’em; but they’re necessary. Smaller teams may be in the mindset of “getting things done” than trying to stick to best practices. Why would I need standards and worry about how all of this may fit together some day if it’s just me?

Con: Getting Help

Though you may have the benefit of focus, there will be times that there can be a heavy workload or you just need time of. As it is with having more people on a centralized team that has familiarity with your work, you may not have that benefit on a smaller decentralized team. Often times, that work will have to be on pause until you get back or have the time to work on it again. By some miracle that you find someone that has free time for you to explain all the intricacies of your data, would it still really be worth it? I often find that it’s best to hold off.

Conclusion

Taking from the title, there are pros and cons to centralized vs decentralized teams. Ultimately, I think that it depends on the work. There may be times where a centralized team makes sense because there’s a need for standards and management. There may be times when a decentralized team makes sense because there’s no need for a lot of people and focus is important. There may be times when both are needed because there is a need for structure and also a need to have a team to get things done now.

Angle of Shot

You can see on the chart that most dead shots were basically in the middle of the deer and that the ‘v-zone’ (right behind shoulder) didn’t have as many shots or most resulted in a deer that survived. What this graph fails to show is the angle of which the hunter shot the deer. Was the shot quartering-to, quartering-away, broadside, was the hunter in a tree, was the hunter in a blind, in their truck? The trajectory of the arrow isn’t shown. 

This means that shots in the green area doesn’t necessarily mean that it’ll only injure a deer. With the right angle (and gear, which well talk about later), that arrow or bullet would run through the vital area of the deer, rendering it dead. On the flip-side, that also means shots in the red area doesn’t necessarily mean it’ll kill the deer.

Penetration

Another aspect of this data that isn’t shown is penetration. Did it penetrate the body, the meat, the skin, bounce off the deer? It’s obvious that if there’s not enough penetration into the body cavity, or none at all, that deer will survive. That is why it’s vitally (pun-intended) that hunters need to do their due-diligence when hunting in understanding the distance of the animal and having the right gear to make certain shots. Let alone, confidence is also key in my opinion. Which kind of leads me to my last topic.

Confidence of Hit Location

We’ve all been through it – buck-fever. Or the physical and mental emotions a hunter may go through when hunting. Imagine, the shaking, thinking about all the things you need to do, all the things that could go right or wrong, and making sure everything is setup correctly. With all that in mind, can we really be confident that the location that was marked was exactly where they actually hit? Obviously for the kill shots, but what about the deer that were found alive or unclear. Granted finding the live deer, you could potentially determine where it was hit from the wound, but even so, was there a follow-up to update the data?

Conclusion

Like I said before, I’m sure there is a lot of truth to the chart. I wanted to provide another perspective on some topics that could be overlooked from a data perspective. In tandem, I hope that it helps hunters to learn where the deadly shots may be located depending on the different scenarios\.