Building a successful startup by complying with the 5 T's

The key areas for entrepreneurs to prioritize as they build their businesses from the ground up.

Entrepreneurs’ jobs, goals and strategies will be different every quarter, if not day. You’re aiming to create or accomplish something that’s never been done. You’re going through growing pains and looking to reinvent yourself and your company to ensure you’re delivering a solution with unbeatable, undeniable competitive value.

This might sound intuitive, but successful entrepreneurs are the ones who embrace failures, surround themselves with great mentors and take responsibility on every level. Successful entrepreneurs are agile and open to reinventing and adapting. They must be coachable. They’re able to maintain balance for long-term growth and stability. They set boundaries with themselves to not become too affected or disappointed by the highs — like successful fundraising — or the lows — like losing a vital customer. If you get too drilled down with problems and allow the lows to hit you hard, you’ll undoubtedly miss out on opportunities to expand your vision.

Having the prowess to ID problems that will come your way in advance is the make or break of a successful entrepreneur. No one hands you a crystal ball, so as you look to grow your startup, you need to maintain control, not lose it, as you bring on more hires. Having transparency and insight on every level rather than losing touch when you have "bigger fish to fry" will give you the visibility needed to make informed decisions. Developing a system where transparency is offered to you consistently will provide you with the key ingredient — an ability to ID pending problems and address them in advance, not in retrospect.

Here are five must-have T's to set yourself up for startup success:

The Talent

Why do you have the best team to win? What complementary skills does each founding member have? Often, your founding team isn’t the right team to scale with. Individuals who serve you well in the early stages might not be right in the growth stage. This reality can be hard to swallow, so being agile and knowing when to pivot is key. Verbit, an AI transcription service, was founded by a speech expert, an engineer who could scale our product and me, who brought the business skills to recruit talent and convince investors and customers to join our journey. These three angles allowed us to be versatile and build the groundwork to succeed. The team has changed greatly since, but those first few hires are critical.

The Technology

What gives you an edge? Can you provide unlimited scale? What about profitability? Are you a must-have technology that eliminates manual processes? Understanding these factors allows you to articulate your offering to investors and customers and develop your marketing strategy. For technology to be successful, it should be hard to imitate. Investors don’t want to back you without understanding your competitive landscape and your technology’s benefits. Think about your tech and how you’ll leverage it and communicate its widespread usage and perks.

The Timing

In 2011, I faced transcription challenges as a lawyer and wanted to solve them. I didn’t pursue it then as the tech wasn’t mature enough and the timing wasn’t right for training a speech algorithm. If I started Verbit then, the company would be unlikely to be where it is today.

Take another example: Better Place was established years ago to do what Tesla is doing now. It was launched before the market was ready and went bankrupt. It wasn’t the right timing. Seeing the success of Tesla now, it’s clear how critical timing can be. It ultimately comes down to a gut feeling: You need to be with the trend at the beginning, but not too soon before the tech is mature enough or the market isn’t ready. 

The Team culture

As Peter Drucker says, “Culture eats strategy for breakfast.” You need smart, dedicated people who execute in the same direction and contribute to a healthy culture. Strategy can be strong, but your team must be aligned. Jeff Lawson of Twilio articulates the importance of establishing core values and a framework on how to articulate them. For me, it was about:

• Collaboration: We only succeed together.
• Winners: We must be motivated to achieve our goals.
• The joy of creation: We’re all working hard, but if we’re not having fun what we’re doing won’t work well.

Instill your values into your employees daily, but doing surveys to make sure your values match is key.

The Total addressable market

To be attractive, you need to showcase that your business is meaningful. Its valuation is set by the market. How big is your market? Entrepreneurs make their careers about building something big and meaningful. What impact can you make? The market for my company is $30 billion, which helped us make the case that we would reach $1 billion in revenue in the next five years. Simply put, smaller markets have less value. Consider that as you strategize, and don’t be afraid to tweak your original ideas and tap into greater use cases.

With the right talent, technology, timing, team culture and an understanding of the market, you’re primed to be more successful. You’re nothing without a good foundation, a story to bring to the market and people who challenge you and complement your own skill set. As a former IDF paratrooper, arming myself with these assets is the most backed and supported I’ve felt approaching a battlefield — even if it’s just the high-tech startup one.

Author: Tom Livne

Source: Entrepreneur

The differences in AI applications at the different phases of business growth

We see companies applying AI solutions differently, depending on their growth stage. Here are the challenges they face and the best practices at each stage.

A growing number of companies are seeking to apply artificial intelligence (AI) solutions, whether they want to launch disruptive products or innovate the customer experience. No matter how business is approaching their strategy, they’ll need to label massive amounts of data, like text, images, audio, and/or video, to create training data for their machine learning (ML) models.

Of course, AI isn’t developed with a one-size-fits-all approach. We find that companies apply different strategies based on their size and stage of growth. Over the past decade, we’ve seen companies leverage AI solutions and encounter challenges along the way, as they come to us for data labeling, or the data enrichment and annotation that is required for training, testing, and validating their initial ML models and for maintaining their models in production.

• Startup companies tend to apply narrow AI to tackle specific problems in an industry where they have deep domain expertise. They typically lack data, especially labeled data that is primed and ready to be used for ML training. They may be challenged by choosing the right data annotation tools, and many lack the expertise or funding to build their own data labeling tools.

• Growth-stage companies are using AI solutions to enhance customer experience and drive greater market share. They typically have a fair amount of data and domain expertise, and they may even have the capabilities to build or customize their own data labeling tool, although perhaps without features like robust workforce analytics. At this stage, navigating competing priorities can be a challenge, where technical resources can be easily stretched and operations staff can get dragged into performing low-value data tasks. The companies in this stage that are applying AI most effectively are those that are giving thoughtful consideration to their customers and missions, focusing on their core competencies, and offloading what makes sense to outside specialists.

• Enterprise companies typically are using AI in one of two ways: incorporating AI into a product or using it to innovate business processes to generate better efficiency, productivity, or profit margins. Larger companies often have plenty of data and extensive in-house technical and data expertise. They are spending millions of dollars on data and AI, but siloed communication across products and departments can make it difficult to get a unified snapshot of the data landscape and where there are opportunities for AI to improve the business. In general, enterprise companies are not as advanced on the data maturity curve as they’d like to be.

As companies of all sizes seek to apply AI solutions, the one component that is more important now than ever is the role people play in the process. Data preparation is a detailed, time-consuming task, so rather than using some of their most expensive resources, data scientists, a growing number of companies are using other in-house staff, freelancers, contractors and crowdsourcing to get this massive amount of data work done.

Best practices for AI solutions implementation

At the end of the day, it takes smart machines and skilled humans in the loop to ensure the high-quality data that performant AI models require. That’s a crucial dynamic when you consider some of the real-world challenges the technology is in a position to help solve. From the ability to identify counterfeit goods or reduce vulnerability to phishing attacks, to training autonomous vehicles with hardware upgrades that make them safer, it’s quality data that makes AI truly valuable.

For companies that are looking to apply or develop AI solutions, here are a few best practices we’ve identified that can help ensure efficient, productive data operations: 

• Secure executive support: Leadership is a key factor in success, and lack of leadership leads to 87% of data science projects failing to make it to market.

• Incorporate data science early: Companies that consider data science and data engineering early in their process will see the most success.

• Collaborate often: Direct access to and clear communication with the people who work with data makes it easier to adjust tools and process (e.g., guidelines, training, feedback loops), which can positively impact data quality and the overall success of an AI project.

• Be prepared for surprises: Developing AI is iterative, and change is inevitable. Companies should consider their workforce and process thoughtfully to ensure each one can provide the flexibility and agility they will need to facilitate innovation quickly while maintaining accuracy along the way. When you realize you’re going to need more labeled data than planned, and quickly, it’s critical to have the right foundation for quality at greater levels of scale.

AI requires a strategic combination of people, process and technology

At any stage of growth, it’s important to understand how to strategically combine people, process, and tools to maximize data quality, optimize worker productivity and limit the need for costly re-work. Leveraging best practices from companies that work with data can put an organization in the best position for success as the AI market continues to grow and new opportunities emerge.

Author: Paul Christianson

Source: Dataconomy

Useful advice for entrepreneurs who consider starting a microbusiness

Right now, with inflation and interest rates rising, many aspiring entrepreneurs are reconsidering plans to launch new businesses. It is, they believe, the wrong time to go all-in on a new venture. And for those with grand plans and ambitions, that may be true. But that doesn’t mean entrepreneurs have no choice but to sit on the sidelines until economic conditions improve.

Instead of trying to start a resource-intensive new startup, they can instead work toward founding a microbusiness. Microbusinesses are, after all, the most common type of business in the US, accounting for 74.8% of all private-sector employment. And they’re quite easy to start. Here are four technology tips for entrepreneurs wishing to try their hands at starting a microbusiness.

Embrace Automation Early On

One of the biggest keys to running a successful microbusiness is to always look for ways to do more with less. And there’s no better way to accomplish that than by turning to automation. That’s why entrepreneurs should embrace automation early on in their business journey and look for ways to utilize it in every aspect of their operation. After all, time is money, and in a microbusiness – every dollar saved goes straight into the entrepreneur’s pocket.

Some of the most effective types of automation for microbusinesses include:

• Social media and marketing automation
• Accounting automation
• Scheduling automation
• Form automation

The idea is to put as many of the day-to-day tasks involved with running the microbusiness on autopilot – freeing up the entrepreneur to handle work that leads directly to revenue.

Leverage Virtual Office Technology

For most businesses, the two biggest cost drivers are labor and real estate. Microbusinesses don’t have high labor costs, and they can all but eliminate real estate costs by virtualizing their offices. In most cases, there’s no business justification for maintaining a physical office space. Instead, an entrepreneur behind a microbusiness can go fully remote and connect with other employees or freelancers via video, voice, or text chat when necessary.

But to make a virtual office setup work, it’s important to come up with ways to maintain customer relationships without the physical component they often have in a traditional office environment. In other words, it’s necessary to replace face-to-face meetings with other, all-digital customer outreach efforts. Some of the best ways to do so include:

• Holding invite-only live customer video events
• Providing live online training and knowledge-sharing sessions
• Organizing virtual networking events

Be a Cloud-native Business

Flexibility is one of the key assets of a microbusiness that allows them to compete in today’s economy. It means they can often be nimbler and customer-responsive than bigger competitors. That makes it easy for microbusinesses to innovate and bring new products and services to market as fast as possible. But flexibility doesn’t equal capability.

To make the most of their flexibility, microbusinesses have to be able to develop new capabilities at a moment’s notice and discard parts of their operations that are no longer viable. But that gets increasingly harder to do if there are significant technology investments involved. The solution, though, is simple: don’t own your technology stack.

Instead, microbusinesses should aim to be cloud-native. A cloud-native business eschews costly on-premises hardware and software solutions. In their place, they rely on contracted access to cloud-based solutions that they can add to or subtract from at a moment’s notice. For example, instead of maintaining a costly mail server to support communications, they’d perhaps start with a free business email address and then turn to a cloud email provider like Outlook.com or Gmail to scale up when the need arose.

The reason this is so important is that it can help a microbusiness keep their costs and capabilities closely aligned with the work they’re doing at a given moment. It’s a way of eliminating unnecessary spending during lean times while preserving the ability to pivot when clients come calling with new requests.

Consider Hardware as a Service

Last but not least, any microbusiness would do well to try and contain its IT hardware costs by exploring hardware as a service (HaaS) options. They’re typically made available by managed service providers (MSPs) as an option for their customers. By leasing IT equipment rather than buying it, microbusinesses can cut major capital costs that they’d ordinarily face to get up and running.

Instead, they pay predictable monthly fees to cover their technology needs and don’t have to worry about complex depreciation formulas and the like. Plus, the costs of most HaaS offerings are cheaper than the cost of purchases when you consider the short replacement cycle of business technologies these days. Plus, payments for leased hardware are almost always 100% tax-deductible, making them the perfect option for a lean-running microbusiness.

The Right Business at the Right Moment

Right now, as economic uncertainty mounts, microbusinesses are the perfect entrepreneurial option to meet the moment. And the technology tips detailed above should help any entrepreneur to launch a lean, nimble, and profitable microbusiness no matter how strong the economic headwinds become. By putting them to work early on, they’ll help to contain costs and improve capabilities at every turn – leading to a successful launch and a sustainable future.

Author: Philip Piletic

Source: Datafloq