EC Column
Auto Added by WPeMatico
Time-strapped IT teams can use low-code software to drive quick growth
Many emerging and mature organizations survive or die based on their ability to scale. Scale quicker. Scale cheaper. Scale right.
Typically the IT team bears that burden — on top of countless other demands. IT teams move mountains for their organizations while scaling the tech platform as fast as possible, putting out the latest infrastructure fire and responding to countless day-to-day requests.
The most helpful gift any chief information officer or chief technology officer can give their IT teams is more time. Many people think that means adding another team member. Maybe it does in some cases (if you can find a developer in this tough job market), but giving my team Boomi’s low-code integration platform was one of the best strategic moves for HealthBridge.
The best time to use low-code is when you need to add something to your organization that isn’t unique or doesn’t drive significant business value.
As the least skilled coder on the team, low-code let me develop and deliver four customer-centric self-service portals a year ahead of schedule while my team focused on building and scaling our revenue-driving, custom platform by hand-writing code.
Low-code is quickly becoming commonplace and a popular topic among IT decision-makers. Over the last few years, the market has exploded. Gartner expects it to total $13.8 billion in 2021. That means low-code technology, which we’ve been hearing about for years, is ready for widespread adoption. Today, low-code enables you to streamline (and scale) everything from integration to artificial intelligence.
It’s a secret only some organizations are clued in on, but it’s a great way to scale fast, save on resources and give your team more time. Here’s how.
When to use low-code and when to write code
The best time to use low-code is when you need to add something to your organization that isn’t unique or doesn’t drive significant business value.
For instance, a customer portal is not unique; don’t waste time hand-coding it.
While it’s certainly an extremely helpful feature for our customers, it’s unlikely to drive significant shareholder or investor value. However, it’s key for scaling. Using low-code for a must-have but undifferentiated feature will allow your team to work on more important projects while scaling.
When we started working on the timeline for a customer portal project at HealthBridge, we estimated it would take several sprints per portal to develop, but more pressing development work kept pushing it down the list in our backlog. Waiting a year for a basic feature didn’t seem reasonable to me, so we looked for a workaround.
Powered by WPeMatico
Data scientists: Bring the narrative to the forefront
By 2025, 463 exabytes of data will be created each day, according to some estimates. (For perspective, one exabyte of storage could hold 50,000 years of DVD-quality video.) It’s now easier than ever to translate physical and digital actions into data, and businesses of all types have raced to amass as much data as possible in order to gain a competitive edge.
However, in our collective infatuation with data (and obtaining more of it), what’s often overlooked is the role that storytelling plays in extracting real value from data.
The reality is that data by itself is insufficient to really influence human behavior. Whether the goal is to improve a business’ bottom line or convince people to stay home amid a pandemic, it’s the narrative that compels action, rather than the numbers alone. As more data is collected and analyzed, communication and storytelling will become even more integral in the data science discipline because of their role in separating the signal from the noise.
Data alone doesn’t spur innovation — rather, it’s data-driven storytelling that helps uncover hidden trends, powers personalization, and streamlines processes.
Yet this can be an area where data scientists struggle. In Anaconda’s 2020 State of Data Science survey of more than 2,300 data scientists, nearly a quarter of respondents said that their data science or machine learning (ML) teams lacked communication skills. This may be one reason why roughly 40% of respondents said they were able to effectively demonstrate business impact “only sometimes” or “almost never.”
The best data practitioners must be as skilled in storytelling as they are in coding and deploying models — and yes, this extends beyond creating visualizations to accompany reports. Here are some recommendations for how data scientists can situate their results within larger contextual narratives.
Make the abstract more tangible
Ever-growing datasets help machine learning models better understand the scope of a problem space, but more data does not necessarily help with human comprehension. Even for the most left-brain of thinkers, it’s not in our nature to understand large abstract numbers or things like marginal improvements in accuracy. This is why it’s important to include points of reference in your storytelling that make data tangible.
For example, throughout the pandemic, we’ve been bombarded with countless statistics around case counts, death rates, positivity rates, and more. While all of this data is important, tools like interactive maps and conversations around reproduction numbers are more effective than massive data dumps in terms of providing context, conveying risk, and, consequently, helping change behaviors as needed. In working with numbers, data practitioners have a responsibility to provide the necessary structure so that the data can be understood by the intended audience.
Powered by WPeMatico
Enterprise security attackers are one password away from your worst day
If the definition of insanity is doing the same thing over and over and expecting a different outcome, then one might say the cybersecurity industry is insane.
Criminals continue to innovate with highly sophisticated attack methods, but many security organizations still use the same technological approaches they did 10 years ago. The world has changed, but cybersecurity hasn’t kept pace.
Distributed systems, with people and data everywhere, mean the perimeter has disappeared. And the hackers couldn’t be more excited. The same technology approaches, like correlation rules, manual processes and reviewing alerts in isolation, do little more than remedy symptoms while hardly addressing the underlying problem.
The current risks aren’t just technology problems; they’re also problems of people and processes.
Credentials are supposed to be the front gates of the castle, but as the SOC is failing to change, it is failing to detect. The cybersecurity industry must rethink its strategy to analyze how credentials are used and stop breaches before they become bigger problems.
It’s all about the credentials
Compromised credentials have long been a primary attack vector, but the problem has only grown worse in the midpandemic world. The acceleration of remote work has increased the attack footprint as organizations struggle to secure their network while employees work from unsecured connections. In April 2020, the FBI said that cybersecurity attacks reported to the organization grew by 400% compared to before the pandemic. Just imagine where that number is now in early 2021.
It only takes one compromised account for an attacker to enter the active directory and create their own credentials. In such an environment, all user accounts should be considered as potentially compromised.
Nearly all of the hundreds of breach reports I’ve read have involved compromised credentials. More than 80% of hacking breaches are now enabled by brute force or the use of lost or stolen credentials, according to the 2020 Data Breach Investigations Report. The most effective and commonly-used strategy is credential stuffing attacks, where digital adversaries break in, exploit the environment, then move laterally to gain higher-level access.
Powered by WPeMatico
How startups can ensure CCPA and GDPR compliance in 2021
Data is the most valuable asset for any business in 2021. If your business is online and collecting customer personal information, your business is dealing in data, which means data privacy compliance regulations will apply to everyone — no matter the company’s size.
Small startups might not think the world’s strictest data privacy laws — the California Consumer Privacy Act (CCPA) and Europe’s General Data Protection Regulation (GDPR) — apply to them, but it’s important to enact best data management practices before a legal situation arises.
Data compliance is not only critical to a company’s daily functions; if done wrong or not done at all, it can be quite costly for companies of all sizes.
For example, failing to comply with the GDPR can result in legal fines of €20 million or 4% of annual revenue. Under the CCPA, fines can also escalate quickly, to the tune of $2,500 to $7,500 per person whose data is exposed during a data breach.
If the data of 1,000 customers is compromised in a cybersecurity incident, that would add up to $7.5 million. The company can also be sued in class action claims or suffer reputational damage, resulting in lost business costs.
It is also important to recognize some benefits of good data management. If a company takes a proactive approach to data privacy, it may mitigate the impact of a data breach, which the government can take into consideration when assessing legal fines. In addition, companies can benefit from business insights, reduced storage costs and increased employee productivity, which can all make a big impact on the company’s bottom line.
Challenges of data compliance for startups
Data compliance is not only critical to a company’s daily functions; if done wrong or not done at all, it can be quite costly for companies of all sizes. For example, Vodafone Spain was recently fined $9.72 million under GDPR data protection failures, and enforcement trackers show schools, associations, municipalities, homeowners associations and more are also receiving fines.
GDPR regulators have issued $332.4 million in fines since the law was enacted almost two years ago and are being more aggressive with enforcement. While California’s attorney general started CCPA enforcement on July 1, 2020, the newly passed California Privacy Rights Act (CPRA) only recently created a state agency to more effectively enforce compliance for any company storing information of residents in California, a major hub of U.S. startups.
That is why in this age, data privacy compliance is key to a successful business. Unfortunately, many startups are at a disadvantage for many reasons, including:
- Fewer resources and smaller teams — This means there are no designated data privacy officers, privacy attorneys or legal counsel dedicated to data privacy issues.
- Lack of planning — This might be characterized by being unable to handle data privacy information requests (DSARs, or “data subject access requests”) to help fulfill the customer’s data rights or not having an overall program in place to deal with major data breaches, forcing a reactive instead of a proactive response, which can be time-consuming, slow and expensive.
Powered by WPeMatico
Billion-dollar B2B: cloud-first enterprise tech behemoths have massive potential
More than half a decade ago, my Battery Ventures partner Neeraj Agrawal penned a widely read post offering advice for enterprise-software companies hoping to reach $100 million in annual recurring revenue.
His playbook, dubbed “T2D3” — for “triple, triple, double, double, double,” referring to the stages at which a software company’s revenue should multiply — helped many high-growth startups index their growth. It also highlighted the broader explosion in industry value creation stemming from the transition of on-premise software to the cloud.
Fast forward to today, and many of T2D3’s insights are still relevant. But now it’s time to update T2D3 to account for some of the tectonic changes shaping a broader universe of B2B tech — and pushing companies to grow at rates we’ve never seen before.
One of the biggest factors driving billion-dollar B2Bs is a simple but important shift in how organizations buy enterprise technology today.
I call this new paradigm “billion-dollar B2B.” It refers to the forces shaping a new class of cloud-first, enterprise-tech behemoths with the potential to reach $1 billion in ARR — and achieve market capitalizations in excess of $50 billion or even $100 billion.
In the past several years, we’ve seen a pioneering group of B2B standouts — Twilio, Shopify, Atlassian, Okta, Coupa*, MongoDB and Zscaler, for example — approach or exceed the $1 billion revenue mark and see their market capitalizations surge 10 times or more from their IPOs to the present day (as of March 31), according to CapIQ data.
More recently, iconic companies like data giant Snowflake and video-conferencing mainstay Zoom came out of the IPO gate at even higher valuations. Zoom, with 2020 revenue of just under $883 million, is now worth close to $100 billion, per CapIQ data.
Image Credits: Battery Ventures via FactSet. Note that market data is current as of April 3, 2021.
In the wings are other B2B super-unicorns like Databricks* and UiPath, which have each raised private financing rounds at valuations of more than $20 billion, per public reports, which is unprecedented in the software industry.
Powered by WPeMatico
For startups choosing a platform, a decision looms: Build or buy?
Everyone warns you not to build on top of someone else’s platform.
When I first started in VC more than 10 years ago, I was told never to invest in a company building on top of another company’s platform. Dependence on a platform makes you susceptible to failure and caps the return on your investment because you have no control over API access, pricing changes and end-customer data, among other legitimate concerns.
I am sure many of you recall Facebook shutting down its API access back in 2015, or the uproar Apple caused when it decided to change the commission it was charging app developers in 2020.
Put simply, founders can no longer avoid the decision around platform dependency.
Salesforce in many ways paved the way for large enterprise platform companies, being the first dedicated SaaS company to surpass $10 billion in annual revenue supported by its open application development marketplace. Salesforce’s success has given rise to dominant platforms in other verticals, and for founders starting companies, there is no avoiding that platform decision these days.
Some points to consider:
- Over 4,000 fintech companies, including several unicorns, have built their platforms on top of Plaid.
- Recruiters may complain about the cost, but 95% still utilize LinkedIn.
- More than 20,000 companies trust Segment to be their system of record for customer data.
- Shopify powers over 1 million businesses across the globe.
- Epic has the medical records of nearly 50% of the U.S. population.
What does this mean for founders who decide to build on top of another platform?
Increase speed to market
PostScript, an SMS/MMS marketing platform for commerce brands, built its platform on Shopify, giving it immediate access to over 1 million brands and a direct customer acquisition funnel. That has allowed PostScript to capture 3,500 of its own customers and successfully close a $35 million Series B in March 2021.
Ability to focus on core functionality
Varo, one of the fastest-growing neobanks, started in 2015 with the principle that a bank could put customers’ interests first and be profitable. But in order to deliver on its mission, it needed to understand where its customers were spending their money. By partnering with Plaid, Varo enabled more than 176,000 of its users to connect their Varo account to outside apps and services, allowing Varo to focus on its core mission to provide more relevant financial products and services.
Gain credibility by association
Powered by WPeMatico
Tech in Mexico: A confluence of Latin America, the US and Asia
Mexico has been known as an up-and-coming tech hub and a gateway to the Latin American market. As an investor focused on developer-centered products, open-source startups and infrastructure technology companies with a particular interest in emerging market innovation, I have been wanting to do some firsthand learning there.
So, despite the ongoing pandemic, I took all the necessary precautions and spent roughly seven weeks in Mexico from January to March. I spent most of my time meeting founders to get a handle on what they are building, why they are pursuing those ideas, and how the entire ecosystem is evolving to support their ambitions.
Knowledge transfer is not the only trend flowing in the U.S.-Asia-LatAm nexus. Competition is afoot as well.
The U.S.-Asia-LatAm nexus
One fascinating, though not surprising, observation was how much LatAm entrepreneurs look to Asian tech giants for product inspiration and growth strategies. Companies like Tencent, DiDi and Grab are household names among founders. This makes sense because the market conditions in Mexico and other parts of LatAm resemble China, India and Southeast Asia more than the U.S.
What often happens is entrepreneurs first look to successful startups in the U.S. to emulate and localize. As they find product-market fit, they start to look to Asian tech companies for inspiration while morphing them to suit local needs.
One good example is Rappi, an app that started out as a grocery delivery service. Its future ambition is squarely to become the superapp of LatAm: It is expanding aggressively both geographically and productwise into delivery for restaurant orders, pharmacy and even COVID tests. It’s also introducing new payment, banking and financial-service products. Rappi Pay launched in Mexico just a few weeks ago, while I was still in the country.
Rappi now looks more like Meituan and Grab than any of its U.S. counterparts, and that’s not an accident. SoftBank, whose portfolio contains many of these Asian tech giants, invested heavily in Rappi’s previous two rounds and now has a $5 billion fund dedicated to the LatAm region. The knowledge and experience accumulated from Asian tech in the last 10 years is transferring to like-minded firms like Rappi, right under Silicon Valley’s proverbial nose.
U.S.-Asia-LatAm competition
Knowledge transfer is not the only trend flowing in the U.S.-Asia-LatAm nexus. Competition is afoot as well.
Because of similar market conditions, Asian tech giants are directly expanding into Mexico and other LatAm countries. The one I witnessed up close during my visit was DiDi.
DiDi’s foray into LatAm started in January 2018 with its acquisition of 99, a Brazilian ride-sharing company. In April 2018, DiDi entered Mexico with its bread-and-butter ride-sharing service. It wasn’t until April 2019 that DiDi launched its food delivery service, DiDi Food, in Monterrey and Guadalajara — two of the largest cities in Mexico. Its expansion hasn’t slowed down since, with a 10% extra earnings incentive to lure delivery drivers.
Image Credits: Kevin Xu
My Airbnb in Mexico City happened to be two blocks away from the large WeWork building where DiDi’s local office was located. Every day, I saw a long line of people responding to the earning incentives — waiting outside to get hired as DiDi delivery workers.
Meanwhile, the Uber office that’s literally one block away had hardly any foot traffic. As Uber and Rappi fight for more wealthy consumers, DiDi is working to attract lower-income users to grab market share, hoping that one day some of these people will reach the middle class and become profitable customers.
Powered by WPeMatico
Startups must curb bureaucracy to ensure agile data governance
By now, all companies are fundamentally data driven. This is true regardless of whether they operate in the tech space. Therefore, it makes sense to examine the role data management plays in bolstering — and, for that matter, hampering — productivity and collaboration within organizations.
While the term “data management” inevitably conjures up mental images of vast server farms, the basic tenets predate the computer age. From censuses and elections to the dawn of banking, individuals and organizations have long grappled with the acquisition and analysis of data.
By understanding the needs of all stakeholders, organizations can start to figure out how to remove blockages.
One oft-quoted example is Florence Nightingale, a British nurse who, during the Crimean war, recorded and visualized patient records to highlight the dismal conditions in frontline hospitals. Over a century later, Nightingale is regarded not just as a humanitarian, but also as one of the world’s first data scientists.
As technology began to play a greater role, and the size of data sets began to swell, data management ultimately became codified in a number of formal roles, with names like “database analyst” and “chief data officer.” New challenges followed that formalization, particularly from the regulatory side of things, as legislators introduced tough new data protection rules — most notably the EU’s GDPR legislation.
This inevitably led many organizations to perceive data management as being akin to data governance, where responsibilities are centered around establishing controls and audit procedures, and things are viewed from a defensive lens.
That defensiveness is admittedly justified, particularly given the potential financial and reputational damages caused by data mismanagement and leakage. Nonetheless, there’s an element of myopia here, and being excessively cautious can prevent organizations from realizing the benefits of data-driven collaboration, particularly when it comes to software and product development.
Taking the offense
Data defensiveness manifests itself in bureaucracy. You start creating roles like “data steward” and “data custodian” to handle internal requests. A “governance council” sits above them, whose members issue diktats and establish operating procedures — while not actually working in the trenches. Before long, blockages emerge.
Blockages are never good for business. The first sign of trouble comes in the form of “data breadlines.” Employees seeking crucial data find themselves having to make their case to whoever is responsible. Time gets wasted.
By itself, this is catastrophic. But the cultural impact is much worse. People are natural problem-solvers. That’s doubly true for software engineers. So, they start figuring out how to circumvent established procedures, hoarding data in their own “silos.” Collaboration falters. Inconsistencies creep in as teams inevitably find themselves working from different versions of the same data set.
Powered by WPeMatico
Kaltura puts debut on hold. Is the tech IPO window closing?
The Exchange just yesterday discussed a downward revision in the impending Compass IPO and the disappointing Deliveroo flotation as signals that market demand for high-growth, unprofitable tech shares could be slipping. Recent news underscores the possibly chilling conditions. This morning, Kaltura, a technology company that provides video streaming software and services, delayed its IPO. JioForMe reports that the postponement comes after Kaltura’s “valuation demand was lower than expected.”
The Exchange explores startups, markets and money. Read it every morning on Extra Crunch, or get The Exchange newsletter every Saturday.
TechCrunch noted yesterday that Kaltura had not released a second, higher IPO price range. The fact stood out given how hot the public markets had proven in recent months for new tech offerings. Kaltura’s S-1 filing detailed accelerating revenue growth, which at the time we thought would be more than enough to fetch the company an attractive initial public valuation.
It appears that Kaltura was also surprised that it was not trending toward a higher IPO price.
In another sign of how quickly the temperature for new tech flotations may have chilled, digital comms firm Intermedia Cloud Communications also delayed its IPO today. In a release, CEO Michael Gold said the decision is due “to challenging current conditions in the market for initial public offerings, especially for technology companies.”
Challenging current conditions? For IPOs? For tech IPOs? That’s new.
Uh-oh
Axios reporter Dan Primack noted this morning that SPAC formation appears to be slowing. Mix that into the delays and yesterday’s anemic-to-awful IPO news, and the market could be seeing a somewhat rapid retrenchment toward more historical valuations and demand levels for unprofitable equities.
Thinking out loud: We should expect SPAC formation and deal volume to fall the fastest of all the signals we’re tracking, including IPO pricing, the pace of S-1 filings and first-day trading performance. Why? Because it’s the most exotic of the various data points we’ve observed on the way up during the tech boom. Therefore, it should also be the thing most vulnerable to rising financial gravity.
Powered by WPeMatico
Will the pandemic spur a smart rebirth for cities?
Cities traditionally have been bustling hubs where people live, work and play. When the pandemic hit, some people fled major metropolitan markets for smaller towns — raising questions about the future validity of cities. It’s true that we’re still months away from broader reopenings and herd immunity via current vaccination efforts.
However, those who predicted that COVID-19 would destroy major urban communities might want to stop shorting the resilience of these municipalities and start going long on what the post-pandemic future looks like.
Those who predicted that COVID-19 would destroy major urban communities might want to stop shorting the resilience of these municipalities and start going long on what the post-pandemic future looks like.
U.N. forecasts show that by 2030, two-thirds of the world’s population will reside in cities, communities that are the epicenters of culture, innovation, wealth, education and tourism, to mention just a few benefits. They are not only worth saving — they’re also ripe for rebirth, precisely why many municipal leaders in the U.S. anticipate the Biden administration will allocate substantial monetary resources to rebuilding legacy infrastructure (and doing so in a way that prioritizes equitable access).
With this emphasis on inclusivity and social innovation, the tech community has the ability to address a range of lifestyle and well-being issues: infrastructure, transportation and mobility, law enforcement, environmental monitoring and energy allocation.
In this time of reset for cities, what smart city technologies will transform how we live our lives? What kinds of technology will make the biggest impact on cities in the next 12 months? Which smart cities are ahead of the curve?
To unpack these questions and more, we conducted the SmartCityX Survey of industry experts — including smart city investors, corporate and municipal thought leaders, members of academia and startups on the front lines of urban innovation — to help provide valuable insights into where we’re heading. Below you’ll find some key takeaways:
Infrastructure is the most crucial issue for cities
Critical infrastructure topped the list of most prominent issues facing today’s cities, followed closely by traffic and transportation. Cisco may have left the party too soon, but others, including countless startups, are lining up and capitalizing on future growth opportunities in the space. A couple of recent data points that support this trend — particularly as it relates to infrastructure rebuilding, IoT and open toolkits to connect fragmented technologies — include the following:
- Bentley Systems, fresh off a September IPO, announced a $100 million corporate venture capital fund.
- Qualcomm announced its IoT Services Suite, comprising leading solutions ranging from wireless connectivity, hardware, software and data analytics to platform integration.
Smart Infrastructure is paramount to Smart City success. It’s crucial that this infrastructure be “architected” as opposed to just connected. This is the only way to truly achieve seamless interoperability while ensuring scalability, reliability, security and privacy. Technology companies that offer robust architectural components and/or platforms stand to deliver tremendous stakeholder value and outsized returns to investors. — Sue Stash, general partner, Pandemic Impact Fund
What’s driving change in cities?
When asked what will accelerate innovation and change in cities, an overwhelming majority cited COVID-19 as the primary factor, followed by remote work, which has accelerated the adoption of online collaboration tools and forced legacy companies to complete multiyear digital transformation projects in a matter of months. The biggest opportunity is to build cities back better and smarter, focusing on new infrastructures that do more with less, and for most of us, that begins and ends at home.
Powered by WPeMatico