The Hawk Tuah Bitcoin

Error!  You’re right. Does not compute. Hawk Tuah does not belong in the same sentence with Bitcoin.

Hailey Welch was an overnight internet sensation because of a sassy bar-hopping response caught on Instagram. She leveraged the notoriety to start a podcast and then launch a celebrity memecoin, $HAWK. $HAWK instantly surged to $490M market cap. Just as quickly, it crashed. Insiders sold their bags quickly. The rug was pulled out from under unsuspecting investors. Maybe investors is the wrong word here. Speculators, perhaps. Marks, maybe.  

The Fall of $HAWK

The value of this token collapsed by over 93% within 15 minutes when insiders dumped their shares!  It’s unclear whether Welch was also a victim of her celebrity status, but very few profited. The vast majority of the total supply of the tokens was centralized in just 10 interconnected wallets. Only 3% was available for public sale.  This means that prices could be easily manipulated by relatively few holders. BTW, this information is easily discoverable because $HAWK used blockchain technology.

Memecoins like these have been available for over a decade. Tokens like these have no value as currency but have value through trading. You’ve heard of many of the names associated with these tokens: Kaiten Jenner, Floyd Mayweather Jr, Andrew Tate, Donald Trump, Melania Trump. Scams are common, and there are few regulations. The SEC does require proper disclosure when promoting cryptocurrencies.

The First Memecoin

Dogecoin (unrelated to the Department of Government Efficiency), created in 2013, was the first memecoin. It is still around and differs from many that followed it in several ways:  Dogecoin is

  • Decentralized
  • Leverages blockchain proof-of-work
  • Unlimited supply, mined fairly
  • Accepted as payment in some transactions

Memecoins are not Cryptocurrency

At first glance, it might be easy to confuse memecoins with cryptocurrencies. Both use blockchains. Both are digital. Both can be bought and sold. The similarities are only superficial.  

Cryptocurrencies vs. MemeCoins
CryptocurrencyMemeCoins
Designed forFinancial use or blockchain applicationsEntertainment, speculation, or a joke
ExamplesBitcoin, EtheriumDOGE, $TRUMP, $MELANIA
Used forPaymentsSocial media
ControlDecentralized, no central controlCentralized in small group; depends on its creators
SupplyScarcity, Bitcoin capped at 21 M, deflationary asset like goldOften unlimited supply
VolatilityVolatile, but long-term growth; Blackrock and other financial institutions include crypto in their investment portfoliosVolatile, prices driven by hype; price easily manipulated by creator
Investment RiskInstitutional adoption; high risk; government regulationHigh risk; scams are prevalent
ValueMay be a small part of a diversified portfolio for long-term investmentEntertainment

Cryptocurrencies have gained legitimacy. Tesla and Microstrategy have a significant portion of their corporate investments in crypto. They consider it a long-term investment strategy and plan to weather the ups and downs. Memecoins are more like trading cards. They’re great if you’re a fan.    

Crypto and Memecoins Compared to Collectible Coins

I have some coins in my collection. One is a University of Michigan silver coin (1 Troy ounce .999 pure silver) commemorating the Wolverines’ 1989 NCAA Final Four championship season. It might be worth $50 on eBay if I can find a U of M fan. The other coin is a $100 gold piece minted by the Canadian Mint in 1987 in commemoration of the Calgary Olympics. One seller on eBay is currently offering the same coin for $2,000. Canadian dollars.  

I hate to cheapen it, but the U of M coin is more like a Memecoin. It has no real purchase value as currency.  It has value to someone who follows Michigan basketball. Because it is a physical coin, unlike a digital asset, it also has some intrinsic value due to the metal. The Canadian coin is more like Bitcoin. It has value as currency. It has a face value that would be accepted at any restaurant or bar. Because it is uncirculated and had a limited production run, it has additional trading value.  

$HAWK Recovery

To be fair, while some investors did lose everything, $HAWK has recovered from the rug pull. In fact, both Coinmarketcap, the world’s most-referenced price-tracking website for cryptoassets, and the community is bullish on $HAWK.  Welch’s rapid rise was interrupted by her foray into crypto.

Hailey Welch rode the viral wave to crypto, launched $HAWK, and watched it fly…then nosedive. Now she’s back online, and people are watching.

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As the BI space evolves, organizations must take into account the bottom line of amassing analytics assets.
The more assets you have, the greater the cost to your business. There are the hard costs of keeping redundant assets, i.e., cloud or server capacity. Accumulating multiple versions of the same visualization not only takes up space, but BI vendors are moving to capacity pricing. Companies now pay more if you have more dashboards, apps, and reports. Earlier, we spoke about dependencies. Keeping redundant assets increases the number of dependencies and therefore the complexity. This comes with a price tag.
The implications of asset failures differ, and the business’s repercussions can be minimal or drastic.
Different industries have distinct regulatory requirements to meet. The impact may be minimal if a report for an end-of-year close has a mislabeled column that the sales or marketing department uses, On the other hand, if a healthcare or financial report does not meet the needs of a HIPPA or SOX compliance report, the company and its C-level suite may face severe penalties and reputational damage. Another example is a report that is shared externally. During an update of the report specs, the low-level security was incorrectly applied, which caused people to have access to personal information.
The complexity of assets influences their likelihood of encountering issues.
The last thing a business wants is for a report or app to fail at a crucial moment. If you know the report is complex and has a lot of dependencies, then the probability of failure caused by IT changes is high. That means a change request should be taken into account. Dependency graphs become important. If it is a straightforward sales report that tells notes by salesperson by account, any changes made do not have the same impact on the report, even if it fails. BI operations should treat these reports differently during change.
Not all reports and dashboards fail the same; some reports may lag, definitions might change, or data accuracy and relevance could wane. Understanding these variations aids in better risk anticipation.

Marketing uses several reports for its campaigns – standard analytic assets often delivered through marketing tools. Finance has very complex reports converted from Excel to BI tools while incorporating different consolidation rules. The marketing reports have a different failure mode than the financial reports. They, therefore, need to be managed differently.

It’s time for the company’s monthly business review. The marketing department proceeds to report on leads acquired per salesperson. Unfortunately, half the team has left the organization, and the data fails to load accurately. While this is an inconvenience for the marketing group, it isn’t detrimental to the business. However, a failure in financial reporting for a human resource consulting firm with 1000s contractors that contains critical and complex calculations about sickness, fees, hours, etc, has major implications and needs to be managed differently.

Acknowledging that assets transition through distinct phases allows for effective management decisions at each stage. As new visualizations are released, the information leads to broad use and adoption.
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Reports and dashboards are crafted to deliver valuable insights for stakeholders. Over time, though, the worth of assets changes.
When a company opens its first store in a certain area, there are many elements it needs to understand – other stores in the area, traffic patterns, pricing of products, what products to sell, etc. Once the store is operational for some time, specifics are not as important, and it can adopt the standard reporting. The tailor-made analytic assets become irrelevant and no longer add value to the store manager.