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High-Output Management for Remote Teams and Companies Part II – ReadWrite

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High-Output Management for Remote Teams and Companies Part II - ReadWrite


In the first installment of this two-part series, we looked at the characteristics of high-performance remote teams. We discussed the key methods I use to ensure my teams are in the best possible position to perform at the highest level.

I explained my process for setting quarterly goals, communicating those goals to the entire organization, and how every level of the company has OKRs that tie into the larger objectives. I also shared my thoughts on check-points and how we use OKRs and check-ins to stay on track and identify any problems as early as possible.

High-Output Management for Remote Teams and Companies Part II

In this second installment, we’ll dive into the finer points of decision-making for leaders, and I’ll be sharing how we use these principles at Turing.

Next, we’ll talk about feedback, and how honest, transparent, and immediate feedback facilitates speed and continuous improvement. Finally, I’ll give you my blueprint for establishing a high-performance organization.

The secret to making fast, but high-quality decisions 

I can’t emphasize enough how critical it is to have the right decision-making structure for your company. One attribute of a high-performance company is that the team makes fast decisions that are also correct.

Reversible vs. Irreversible decisions 

From my perspective, there are two kinds of decisions companies make; reversible decisions or irreversible decisions. Ninety-nine percent of the decisions a company makes are reversible. Only a very few, who you raise money from, who you choose as a co-founder, are irreversible.

Typically, the best approach for a company is that anybody except the CEO should make reversible decisions. If it’s an irreversible decision, the CEO makes the decision. In both cases, high-performance companies make high-quality decisions fast.

How not to suck at decision-making 

Generally, there are three ways companies can operate when it comes to making critical choices.

One way they can operate is purely top-down. For example, somebody with authority just says, hey, do this, and everybody does what they’re told. The benefit of this approach is that it’s swift.

The negative is that you don’t have enough buy-in from everybody on implementation and people don’t feel heard. Frequently, valuable insights from others in the team don’t get incorporated into the decision. So that’s not ideal. 

Have one decision-maker but consult key stakeholders

A much better approach is to have one decision-maker who consults with key stakeholders. These are people with insights and perspectives relevant to the problem. Often, there is a very high-quality decision made when all the right people are sharing their inputs.

But you will want to maintain one arbiter who weighs all the inputs and makes the call. This approach has the benefit of factoring in everyone’s expertise, and it increases the likelihood that everyone feels heard.

Product design decisions

At Turing, for some of our product design decisions, the approach I follow is the same pattern described above. Having one decision-maker — someone who is a key stakeholder. All stakeholders are consulted, then we have the decision-maker also be the person who’s responsible for implementation.

How frustrated have you been when somebody else makes the decision, but you are the person that ends up accountable for implementation? That’s not great. I believe it’s always good to have the decision-maker be the implementer and the person who owns the metrics associated with the decision. 

Decide who decides

So for our product design reviews, we use the following process.

A decision owner (could be someone from the Product team or Engineering team) reviews the design for a new feature, takes inputs from key stakeholders, and then decides. This person also owns the success metrics for that feature.

The decision can be a) good to move to implementation, b) identifies a few changes that need to be made before it moves to implementation c) decides it’s a no-go.

Once the decision is made, the decision-maker identifies the next step. E.g., “ship to staging by Feb 10th.” We track what was decided, share it with the team, and move to implementation. The decision-maker is the DRI (Directly Responsible Individual) for implementation.

You can do much of this asynchronously. At Turing, we’re using Google Docs, so our designer, Alejo, leaves the Photoshop designs in the Google Doc so the people involved can leave comments on the doc, and everybody signs off.

The beauty of this process is that it allows you to use meeting time to go over anything that is genuinely contentious or something that needs further hashing out.

Reserve synchronous meetings for resolving blockers

Synchronous meetings are used more for resolving any bottlenecks, conflicts, or anything that needs further discussion while doing the simpler stuff asynchronously. But one of the most important things is having that separation between a decision-maker and team members that provide input.

Too often, companies err by having a decision-maker but no group of people to be consulted.

So then things get into the product, and there is not enough buy-in. Afterward, people sort of complain about the decision behind each other’s backs — or follow-through is lackluster on implementation and support. 

Making decisions made by a committee is another mistake companies make.

Everybody will try to get on the same page and reach a consensus. The problem is that getting to an agreement can be very costly for a startup because you can lose so much time. Purely democratic decision-making does not work for fast-moving technology companies.

That’s why I call my approach a reversible decision — because 99% of all company decisions are reversible. Keep in mind that you should be making a lot of reversible decisions knowing full well that some of them will fail, and you can always internalize the learning and move forward. 

Embrace feedback loops for continuous improvement

High-performance organizations have a strong culture of feedback and continuous improvement. Ideally, once a month, you must take some time to internalize areas for improvement to go faster.

At Turing, for example, I have a document that’s solely focused on the next improvements.

I call the document the “Next Improvements Diagnosis.” What I try to capture are all the negative things that can happen within my company. A trial can fail, or a developer can fail a customer’s interview. Or, for some reason, collaboration breaks down.

What we do is track every single case of any fail happening. Then we try to understand why this error occurred? How could we have detected the problem earlier, and how can we prevent it from happening next time?

Instill a culture that learns from failure

One of the hardest things to do in a startup is to have a culture that learns and improves from failures without falling into the blame game or feeling too negative about it. 

When I see these things breaking down, this may seem odd, but I have a big smile inside me because the most challenging part of building a high-growth company is if you can’t find the headroom to go faster.

I love when we find big, meaty problems because solving them means unlocking a lot more growth and business value. (Rubbing hands together with glee.)

It’s also helpful to keep the team focused on the positive outcomes of some of these adverse situations to learn from them and get stronger.

Do you analyze your lessons?

Too often, non-high-performing cultures fall into the trap where people are saying, “It’s not my fault; it’s that person’s fault.” Failing to analyze lessons from failures and therefore never improving is even worse. 

If you are still on the first level — you’re not even tracking all these failures; you’re only showing things going up and to the right.

Track failures to get better more quickly

But I want to track every single failure where we didn’t deliver on our promise to a developer or a commitment to a customer and use this data to keep getting better continuously. High-performance cultures share a common attribute of continuous improvement and constantly leveling up.

How to build a high-performance organization – a simple blueprint

How do you distill everything I’ve written into a simple blueprint that makes it simpler for your team and your company to perform to your utmost? 

It’s simple but not easy. Here’s your cheat sheet:

  1. Make sure everyone understands what high-performance looks like. Remember, high-performance teams, establish clear goals, write them down, share them widely and then meet or exceed them.
  2. Leadership at the team and the company level should establish the next set of objectives, makes sure that everyone in the company understands what we’re doing, why we’re doing it, and how we’ll measure success.
  3. You’ve developed a method of creating checkpoints and making adjustments when you see something isn’t going as planned.
  4. Write everything down. Writing simplifies, clarifies, and makes it easier to drive alignment. Writing also makes it easier to refine ideas through iteration and feedback, so your final version keeps getting better.
  5. There’s a clear decision-making process that secures buy-in from all involved parties, but with a single decision-maker who’s responsible for implementing the decision, tracking performance, and determining what needs to happen next.
  6. Be sure to create a culture that embraces failure and leverages mistakes to unlock untapped speed.
  7. Never become complacent. High-performance teams and companies focus on identifying areas for improvement and continuously working to better themselves and deliver on plan and on schedule.

Final thoughts

Building a high-performance team is not something that happens overnight. I’ve worked for years to develop the skills that have enabled me to attract the right kind of people and hone them into a highly productive, collaborative, and unified team. I have an outstanding executive team that has helped me distill these lessons and contributed to this blueprint.

Becoming the sort of leader that inspires people to build a great product and company that can change the world isn’t an endpoint; it’s a continuum.

You won’t start this process at the top

Remember — you’ll be bad at this before you’re mediocre and mediocre before you’re good and good before you’re great. But at each stage in your process, you should be able to see where you want to go.

By applying the techniques I’ve outlined above, you’ll be on your way to getting high-output management for your remote teams and companies.

Image Credit: krakenimages; unsplash; thank you!

Jonathan Siddharth

Jonathan is the CEO and Co-Founder of Turing.com. Turing is an automated platform that lets companies “push a button” to hire and manage remote developers. Turing uses data science to automatically source, vet, match, and manage remote developers from all over the world.
Turing has 160K developers on the platform from almost every country in the world. Turing’s mission is to help every remote-first tech company build boundaryless teams.
Turing is backed by Foundation Capital, Adam D’Angelo who was Facebook’s first CTO & CEO of Quora, Gokul Rajaram, Cyan Banister, Jeff Morris, and executives from Google and Facebook. The Information, Entrepreneur, and other major publications have profiled Turing.
Before starting Turing, Jonathan was an Entrepreneur in Residence at Foundation Capital. Following the successful sale of his first AI company, Rover, that he co-founded while still at Stanford. In his spare time, Jonathan likes helping early-stage entrepreneurs build and scale companies.
You can find him Jonathan @jonsidd on Twitter and jonathan.s@turing.com. His LinkedIn is https://www.linkedin.com/in/jonsid/

Politics

Fintech Kennek raises $12.5M seed round to digitize lending

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Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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