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Product Value Leakage: The IT Services Mindset Problem

Introduction

Over the past two decades, we have been extremely fortunate to work with some of the best product minds in the world, who make material impact on the world by building game changing products. We have also been asked to turnaround companies having products which lost their edge and plagued with execution issues. While there are a myriad of issues on why products fail, one of the serious issues we have seen is the “IT Services Mindset”, often times the damage inflicted by this mindset is irreversible with companies leaking their product value and becoming custom IT services organizations. …


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The unintended consequences of optimizing for valuation versus optimizing for cashflow

Introduction

Pivots are more than just a fashionable word, many start-ups use the terminology just for the sake of it and rarely understand its anatomy, mechanics, and their own ability to execute a good pivot. While there are many different reasons to pivot, and ways to holistically achieve it — this article will examine the pivot zones created by two choices i.e., optimizing for cashflow vs optimizing for valuation. Many start-ups fall into these traps very early on in their evolution. These decisions have intended and unintended consequences, landing the business in a place which will need a pivot. Some of these pivots are practical, others difficult and a few paths lead to nowhere. …


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Understanding business models in autonomous driving

Introduction

Autonomous driving is one of the most disruptive developments witnessed. It will change the way we think of cities, roads, parking, commuting, leisure and ownership, and it will spawn new kinds of jobs as the business models unfold. Many open questions have answers when it comes to business models, infrastructure, technology direction and development.


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Understanding the disruptive technologies propelling autonomous driving

Augmented Reality

In my previous article, we discussed various drivers of business models and the way it will change cities, roads, parking, commuting, leisure and ownership while creating new jobs. …


Modern-Day Sales: A Value-Based Approach

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In the last 10 years, business has changed a lot. Even many companies and industries have come as we have fundamentally changed the way we sell products or services, interact with customers, and deliver value. Having said that we still use legacy cells approaches which do not work or produce suboptimal results. In this article we are going to examine the modern day, value based selling approach.

Introduction

In today’s world, buyer have a multitude of choices and plethora of information about products, services and brands starting the sales cycle even before you have engaged with them. At times, the information overload is confusing and noisy while other times it provides the confidence and head start to see data points and make decisions. They need people to share ideas, help them think and see through problems or solutions; yet, many companies and sales functions have struggled to adapt to the new age of selling through value and insights — select few are getting this right and winning business. …


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Understand the disruption vectors of the “Stack Attack”

Major technologies shift every 2–3 years, with new platforms building on prior generation capabilities. These shifts are propelled by new technologies or new software stacks. Software stacks are also called “technology stacks” and provide a complete platform to run applications to process complex computing environments.

Introduction

In the era prior to cloud, mobility, IoT, AI, Big Data etc., technology stacks used to be vendor specific e.g., Microsoft etc. Today, there is an explosion of technologies in these stacks and we have new tools being spawned into mainstream every year e.g., Kubernetes, Docker Toolbox, Polly, Prometheus etc. did not exist a few years ago. Many capabilities and technologies like Data Lakes, NoPSD etc. …


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Understanding Data Challenges in the Autonomous Driving Domain

There are numerous data challenges in the autonomous vehicle value chain, a lot of it impacts specific use cases and outcomes. This article highlights the nature of challenges and their impact across the data value chain.

Introduction

Automotive data is of high interest due to the diverse and complex nature of data, its multiple sources as well as high volume of the data continually generated. Within an autonomous driving context, real-time requirements around navigation, safety and revenue models create new challenges.

General AV Data Challenges

As vehicles advance to higher levels of autonomy, the deep learning models utilize high volumes of data for decisions e.g., from sensors, cameras, lidars, pedestrian behaviors, road conditions etc. There are a multitude of different challenges when it comes to the data value chain within autonomous driving and we will examine a few key themes here. …


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Understanding the Value of Big Data in the Autonomous Driving Ecosystem

Introduction

Today, there is a ton of data generated from people, devices and about many things e.g., weather, location, demographics, purchase patterns etc. Moreover, we are shifting from an era of user generated data/content to an era of machine generated data/content increasing the volumes exponentially.

Unlocking value from autonomous driving value chains is not about having more data — but the right data, at the right time, for the right ecosystem participant

Most of these large sets of data are considered valuable because they can be packaged and sold to someone else. However, the common myth is that collecting lots of data about lots of things creates value. It is important to understand the right criteria and attributes of data to generate value effectively. For example, Google collects a lot of data, but value is accrued only when it is meaningfully processed thorough applications, APIs, or service to create value for customers. …


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How Autonomous Driving Tech stack choices impact business models

AV Technology Stack: Layers and Components

At a high level, there are five primary layers of the autonomous driving technology stack i.e., sensors, infrastructure, compute and network, hardware/software interface and applications. Companies play within different layers of the stack to create value, and the resulting technologies come together as an ecosystem to enable autonomous driving. For example, Mobileye delivers vision-based sensor fusion, HERE creates maps and NVDIA enables compute etc. Apart from the core layers and components, there are critical technologies and policies enabling the autonomous driving value chain e.g., security, artificial intelligence, simulation technologies, various big data technologies as well as safety and regulations. …


Understanding key drivers and adoption patterns for edge computing

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Edge computing sounds very mystical, but it has been around for a while in some form. Edge computing architectures are designed to spend most of their useful life near to its consumption rather than the cloud. The shift in the era from user generated to machine generated data and the advent of technologies like IoT, Artificial Intelligence, Virtual Reality, High Definition Gaming and Streaming etc. have created volumes of data at galactic scales needing a decentralized internet; much more data created, processed and stored at the edge.

Cloud Principles at the Edge

Cloud is not here to displace the cloud like initially believed; it is an extension of the cloud. On-demand resources, abstraction of physical infrastructure to locations close to consumers. The approaches to manage edge locations are like cloud, it is only a matter of understanding which workloads are suitable to process on the cloud versus at the edge. Traditional cloud players like AWS with their AWS Outpost and Microsoft with Azure Stack Edge are extending their cloud computing initiatives to the edge, technically these are fully assembled stacks of compute and storage resembling their own date centers- just installed at the customer premises but monitored, maintained and serviced by these vendors. Cloud providers have made it clear that they are extending the cloud through edge offerings. …

About

Nitin Kumar

Silicon Valley CEO, Venture Investor, Board Member and Former Management Consulting Partner. A gadget freak & global nomad with a unique perspective !

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