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Multiple times over the past few quarters, we have come across questions around customer success and the importance of proactive customer engagement models and the market opportunities they represent. We have more than one company focusing in this space – Totango, a leader in customer success management solutions and OneMob, a video engagement platform for customers, partners and employees. Very often, we are asked how big is this market today and how fast is it growing. These are legitimate questions for which the answers are not found in any credible independent third party report. This article describes our views of the customer success maturity model and why we believe this market is still in its early stages, but fast maturing.

Enterprises of all sizes are undergoing a profound digital transformation and are adopting cloud-based subscription business models. In a recent survey from Gartner, 42% of CEOs said that “digital first” is now their company’s digital business posture. Every business, from selling razor blades (Dollar Shave Club) to selling music (Pandora, Spotify, etc.), is transitioning to a subscription-based business model. Shared ownership and pay-for-use are becoming alternatives that buyers are evaluating before making any capital investments. As a result, large well-established firms are facing the threat from a gaggle of disrupters who are innovating with new business models. Gartner predicts that by 2020, five of the top seven digital giants will willfully “self-disrupt” to create their next leadership opportunity.

Making this transition is not easy. Top management consulting firms such as Deloitte, have established practice areas around Flexible Consumption to help large companies in their digital transformation. In our observation, this process unfolds in 5 phases – what I call the “Digital Transformation Maturity Model”.

Getting commitment
: It all must start with executive level commitment – a buy-in top down to change the ethos of the company and embrace change. This can take several months to gain sufficient impact, and the larger the company, the longer the process.

Organize and Prepare
: Once the decision is made, the leaders of the company have to align the entire organization around this new model, which involves a lot of preparatory work. For a lot of product companies, the software needs to change to accommodate a shift from a licensing model to a subscription model. Marketing collaterals need to change, CPQ (configure, price and quote) software needs be updated, and sales projections need to be qualified –  just to name a few. Supply chains need to be modified to fit the subscription consumption models. This is a massive transformation effort and can take several quarters.

: In this stage, sales teams need to be trained. They need to start selling the new model. Some existing customers need to be given advance notice and training related to this transformation. While the sales process is ongoing, the new selling model must be slip-streamed in a smooth fashion. Again, this can easily span 2-4 quarters.

: In this stage, the organization is learning and collecting metrics. The effects of the new models are just becoming apparent. For example, at an account where the sales executive would have closed a $1M licensing deal, the sales executive is closing a $100K initial 1-year subscription deal. Some customers who found a cheaper alternative may choose to cancel the next year and churn out of the relationship. Some business models built on User Seats are reaching a new plateau in volume etc. The impact of the transformation will ripple into many other observations and side-effects which must all be collected and measured.

Optimize and Improve
: In this stage, agile organizations are learning and adapting. They are feeling the effects of the subscription model, but the best ones have been able to reap the benefits of the transformation. The less agile ones are struggling with churn, trying multiple things to retain customers, and are probably seeing their revenues erode. The last two phases are overlapping, but collectively this can range from 3-4 quarters for the agile ones, to 6-8 quarters for the less agile ones. I call this phase the “customer success enlightenment” phase, since it is only then that organizations realize the true need and potential of customer success management. A lot of time, organizations want Utopian state of “zero churn”, but the key here is to understand that it takes a lot of concerted effort to adopt best practices to realize that.

Collectively, the 5 stages of a digital transformation process can easily take 3-5 years. However, the pace of digital transformation is accelerating. Companies are increasingly looking to management consulting firms to learn best practices and to technology startups to accelerate this transition. We often see such companies move at a faster pace compared to those who want to complete the journey by themselves. With the right control mechanisms in place, the nimble companies are able to launch their new SaaS offerings even while their internal CPQ and billing systems are still playing catch up. Their product teams are trying to be faster to market, often using manual work-arounds or adopting new platforms that improve their agility. These strategies can often lead to a non-linear digital transformation curve.

Not all CS platforms are equal.
In large deployments, you need to have sufficient granularity of information on how your product or service is being consumed (by BU, group, individual, by module, etc.) and to have a real-time view of this dashboard as opposed to a rear-view mirror. This enables a proactive approach to issues, low adoption and understanding the customer’s business. You need to have systems that are independent of your primary system of record so that they can be dynamic and scale and not get bogged down as you add more data sources. Implementation needs to be in weeks – not months or years. Top performing companies will need to redesign their entire operations with the customer at the center – what Totango refers to as the E2C (Enterprise to Customer) model. Sharing relevant customer information with the appropriate people facilitates not only resolution of customer issues but also feature innovation. (These unique abilities of Totango is what prompted our investment in them.)

To learn more about Customer Success visit

Join top industry practitioners and visionaries at the Customer Success Summit – the Premier Customer Success Event being held March 5-6th in San Francisco. Don’t miss this opportunity to learn and network with the industry best…

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BGV recently moderated a panel hosted by Marcus Evans on the challenges faced by LPs in constructing an alternative asset portfolio around the Venture Capital asset class.  The panel members included Matt Stepan with CFM, a financial advisory firm with $11Bn AUM, and Freeman Wood with Mercer Sentinel, a leading investment advisory consulting firm.  The full webinar can be accessed at:

This entry is the second and final part of the blog focusing on the topic of sustaining returns in the Venture Capital asset class over time.


Context & Key Trends

One of the myths about Private Equity is that private equity does well in good markets and does worse in bad markets. The data below shows that private equity performance has outperformed public markets in both good and bad markets.



As we look into the venture capital asset class, we find a similar story.  Since the recovery from early 1999-2000s the venture capital asset class has outperformed the S&P 500, with a constant increase in IRR and multiples across recent vintages (see charts below).


The chart below from Cambridge compares gains in their cohort of top 100 investments. They concluded that “success comes in all sizes”, meaning the group of top performers includes both large and small funds – ranging from small funds- less than 250M, to mid-size funds, and to larger funds – funds more than 750M. In recent years, funds of less than $250M have accounted for a good portion of value creation.


Cambridge has also looked into the performance of top quartile US venture capital funds by vintage years across new funds, developing funds (funds that are in their 3rd or 4th fund), and well-established funds. The cohort of top quartile venture funds contains a good mix of new, developing, and well-established funds.

This data runs contrary to the common notion that only well-established billion dollar funds provide good returns to investors. As investors look to deploy into this asset class, there is an argument to be made in having a basket of investments across big and large, new and established funds.  



The topic we are going to discuss is the best practices our panelists and their clients have used to sustain returns in the venture asset class after they have made the manager selection decision.  

  1. Matt, at CFM what has been your experience with key variables that led to sustaining performance over time with your VC fund investments?
  2. We have seen a few patterns that contribute to persistence of returns over time. These include: a) Relatively modest fund size – Smaller funds focused on a fewer number of portfolio companies with a thoughtful approach to how they deploy their capital.  Larger funds tend to become less nimble.  It is important to be nimble in the VC world because the startups are often going at a sprint and firms need to be able to react to that while being thoughtful; b) We have also seen consistent success from funds where the teams are focused within markets or sectors where they have a deep understanding of the trends transforming them.  Our prototypical funds are ones with 3 GP’s, a team size of 10-15 people, a fund size greater than $100M but sub $300M with a focus on 3-4 sectors that the team knows well; c) From a portfolio construction basis, funds that have a mix of companies that are both solutions oriented and disruptive do well.  Solution oriented portfolio companies with a good operational track record can often get to good M&A exits on an all cash basis.  We have found that a balanced portfolio between disruptive IPO track startups and solutions oriented startups leads to a persistence of returns over time; d) Finally we believe that the personal character of the VC’s is also a determinant.  Often times when companies begin not to perform to expectations, sometimes VCs step away too early instead of taking corrective action.  While it makes sense to spend time with winners, we also believe that fund managers should be thoughtful in sticking with what they have invested in by taking corrective action instead of settling for a suboptimal outcome.


  1. Freeman, what are some of the best practices around risk control to protect the sustainability of returns over time that you suggest to your clients when they invest in Venture Capital?
  2. We have a strong belief that establishing transparency is important – in what is being invested in by the managers as well as how those investments are performing over time. Sometimes our clients fall into the trap of a “set it and forget it” mind set because they are dealing with committed capital but we believe that being proactively involved is critical after making the investment allocation.  We advise our clients to perform on-site diligence as frequently as they are comfortable (at least once every 12 or 18 months) to see how the manager is controlling their risks and how the portfolio is performing.


  1. Matt, we have seen cases where investors have used various techniques to get to know the manager team using direct or co-investments. Can you comment on how CFM has scaled its venture fund relationship? Have you done direct and co-investments?
  2. We have had the opportunity to do both and have found that co-investments that are follow on investments (Series B and C) work better for us. These opportunities give us the time to get to know the company, the management team and track progress over time before making a co-investment decision.  We have led a few direct investments but we feel that this does not align as well with our expertise and that VC firms are better suited to make such investments.  Finally, we want to be viewed as a partner by VC firms and not as competitors.  For all these reasons we have found co-investments to work better for us than direct investments.


  1. Freeman, what is the best way for your clients to get to know a GP at a fund?
  2. It is a combination of upfront diligence before making the investment decision and post investment relationship building. Often a combination of meeting the manager, understanding their expertise/edge, ensuring that there is an alignment of incentives and getting to know the supporting teams, the key processes (beyond the GPs).


  1. What has been you experience with trying time investments in the venture capital asset class.
  2. CFM – While industry data over time reveals that vintage year does play a role in investment performance, we have found that a sustained effort over the long term (ten years or more) results in consistent performance. If this is done well then distributions from earlier years end up funding current and future capital commitments.  We have found the optimal strategy is to be patient, invest in the asset class for the long term and apply the best practices that have been discussed today to deliver good returns.  VC investment is a marathon even though at times the VC markets may feel like a sprint but applying a consistent framework can lead to a persistence of returns.  It is important not to get caught in the day-to-day sprint and stay focused on the long term.
  3. Mercer – I agree, timing is a double-edged sword – do it well and it can be lucrative, do it poorly and it can be very painful. Having a commitment and a process for an asset class for the long term enables LPs to smooth out timing differences and get to know the fund managers well.  This is important.  We have found that LPs who invest in different asset classes some times uncover best practices that can be leveraged to help their fund managers improve their performance.  These types of long-term relationships are a win-win for both LPs and fund managers.  

BGV recently moderated a panel hosted by Marcus Evans on the challenges faced by LPs in constructing an alternative asset portfolio around the Venture Capital asset class.  The panel members included Matt Stepan with CFM, a financial advisory firm with $11Bn AUM, and Freeman Wood with Mercer Sentinel, a leading investment advisory consulting firm.  The full webinar can be accessed at:  This is the first in a two-part blog summarizing the webinar content focusing on the best practices around manager selection in the Venture Capital asset class.


Context & Key Trends

Since the 2008 financial downtown, there has been a steady increase in LPs committing higher allocations to alternative assets. In fact, this practice has accelerated since 2016 and is expected to continue to do so over the next 12 months.  In a recent survey by Preqin, almost 65% of the respondents said they expect to deploy more capital in the next 12 months, compared to the past 12 months (see chart below).


Global family offices with an estimated $4T are allocating 50% to the alternative asset class.  Within the alternative asset category, private equity (including venture, buyout and growth capital) and private debt have been the biggest benefactors of the shift in allocations.


Despite the recent run up in public markets, this sector is becoming structurally less attractive to LPs.  These LPs are responding by raising their allocation to private markets.  Some rotate out of hedge funds into multi-asset funds.  Even Sovereign wealth funds, and pension funds as well, which comprise 5-6% of the allocation to private equity, are expected to go to 10-11% allocation. Within the alternative asset classes, investor appetite for venture capital has significantly increased over the past 12 months, ranging from Family Offices, to Sovereign wealth funds, to Endowments and Foundations. This data is fairly consistent across all geographies.



Challenges – Manager Selection

While growth in the number of funds has increased- assets under managements and even distributions have increased- this development presents a unique set of challenges. In order to increase their allocation to alternatives, investors must find the right managers and investment strategies to put that capital to work.


There is a wide dispersion in the returns from the private equity asset class, heavily dependent on the fund managers.  We believe that manager selection significantly influences the net returns.

Furthermore, a stark difference exists between top quartile vs. bottom quartile managers in terms of fund performance – measured in net IRR. The chart below shows that the net IRR range over a 10-year horizon is between 16-17%. The median is about 6-8%. However, when you look at the bottom quartile performance, difference is more distinct.

Thus, the challenge for institutional investors is to find top quartile fund managers. There is no guarantee that one can generally invest in this asset class and get the type of the returns they target.



In our discussion, the first topic we are going to discuss is the best practices our panelists and their clients have used to go about manager selection successfully.


  1. Matt, from a CFM perspective, what are the top two to three criteria that you have used successfully to select high performing managers?
  2. We tend to look at three criteria to evaluate and identify top quartile fund managers. These include: a) Top quality leadership – GP’s at the firm; b) A differentiated approach to investing in the markets they focus on; c) Early stage focus – to enable us to take advantage of the equity valuation increase that comes from investing in innovative companies at this stage.


  1. Freeman, what do you recommend to your clients around due diligence best practices to evaluate fund managers?
  2. We tend to advise our clients to diligence the fund’s governance and infrastructure to identify and make investments and also on how they manage the investments over time. Our emphasis is on ensuring there are sound, robust and repeatable processes to manage investments over time and not just identify investments.  We also tend to look for transparency in the processes.


  1. Matt, you see a high number of pitches from fund managers, how do you diligence the quality of the team?
  2. We tend to look for specific characteristics in the individual GP’s including: a) Strong operating and investment backgrounds; b) Their ability to relate well to an entrepreneur – the journey that an entrepreneur takes from startup to exit is a unique and difficult one to navigate.; b) A track record of consistent success and their ability add value beyond the capital be it as a coach, a trusted advisor and/or a productive board member. At the team level, we look for teams that have worked together successfully before – this ensures that they have worked out how they make decisions and work as a team.  


  1. Freeman, could you give us a few examples of robust repeatable processes that you look for when evaluating fund managers?
  2. We look for teams with demonstrated expertise in the areas of investment and operational focus. For example, we like to see a clear segregation of responsibilities and processes in areas such as making investments (i.e. investment committee etc.), finance/back office operations, management of portfolio companies and portfolio exit/dissolution.  We like to see that processes are well documented and have been implemented consistently over time.


In our next blog, we will summarize the best practices around sustaining returns over time once LPs have made the manager selection for investment in the VC asset class. 


Phillippe Bouissou, Managing Partner at Blue Dots Partnersshares his perspective on why external alignment is mission critical for technology startups. This requires a deeper diagnosis of the root causes behind stalled growth instead of simply firing the CEO. This blog was previously published here. Before being in the management consulting business, I was a Partner at Allegis Capital, a Palo Alto-based early-stage VC firm with $500M under management. The firm was capitalized by 33 large corporations as Limited Partners, who provided the capital we invested. It was an impressive list of multi-national, mega billion-dollar companies including AT&T, Comcast, Boeing, GE, Fujitsu, Siemens, Motorola, P&G and JP Morgan to name a few. I remember one day, walking into a Board meeting for one of our portfolio companies and the CEO was clearly exhibiting some discomfort as he had to explain why he missed sales for the quarter that just ended by 18%. An instinctive reaction to that problem is what I call the “self defeating blaming circle” and to quickly put the burden on sales. So, our CEO asked his VP of Worldwide Sales to present and his VP defended his upsetting results by citing the lack of quality of the leads, which led to much lower than expected conversion rates. The VP of Marketing then came in and complained that the product did not have all the features and functionality that were required for the market segments the company was targeting. When the head of product finally came, he explained that no one gave him the right product roadmap and the exact specifications of what customers really wanted, so he and his team built what they thought had the best feature set. You get the picture: the board meeting was a circus of finger pointing: Unfortunately, this scenario happens quite frequently in Boardrooms. To us, at Blue Dots, this is the perfect symptom of external misalignment. It is very hard to shoot at your companion-in-arms if all the weapons are pointing in the same direction (the hill the company is trying to take) as opposed to shooting each other. When I meet with early-stage VC firms, I often hear the following opening statement from the Partner I am meeting with: “All our portfolio companies are doing really well, growing fast and we don’t need your help.” I remind them that I was a VC for close to a decade and that I know that somewhere between 30% to 60% of their portfolio companies are not growing as fast as the investors would like. This is part of taking risks and a fund will suffer a large number of casualties, as seed and early-stage investing is a risky business with inherently uncertain outcomes. It is the one big winner (the home run) that makes a fund. Two home runs and you are a top VC fund like Accel, Andreessen Horowitz, Benchmark, Greylock, Kleiner Perkins, Lowercase Capital, Sequoia, Union Square Ventures, and others. Then comes the second salvo from the VC Partner: “If one of our portfolio companies is not growing as fast as we expect, we fire the CEO.” While firing the CEO is at times the right, reasonable and legitimate thing to do, we do not believe that it is the right approach to solving the growth problem and here is why:
  1. It creates all kinds of unintended consequences, including massive disruption to the rest of the organization.
  1. It does not answer the question: “Why aren’t we growing as fast as we’d like?” Growth could have stalled because: the messaging is not aligned with the perception. In that case, the person responsible might be the VP of Marketing. Of course, ultimately, the buck stops at the CEO’s desk, but the problem in this case can be addressed by other means than firing the CEO.
  1. It takes 4 to 6 months at best to find a new CEO, then another 3 months or so for the new CEO to get his or her bearings and start to deeply understand why growth has stalled.
In the end, it may take one year to get to the bottom of it and start fixing the real misalignment issues. Don’t get me wrong, I am not suggesting that firing the CEO is always a bad thing to do. However, I would argue that if the core issue is slow revenue growth, then approaching the problem along the four independent axes that Blue Dots devised is a much more effective, pragmatic and disciplined approach.

Anik Bose, General Partner at BGV, shares his perspective on the digital transformation of the HR function. Digital transformation is a well-known disruptor in many sectors, but its impact on Human Resources is less broadly understood. The flow of venture capital into HR tech is one good indicator of disruption potential – in 2016 over $1.96Bn of venture capital flowed to HR tech startups according to CB insights. Another indicator is the strategic investment activity of established HR companies looking to revamp their own offerings. Concur, Infor, and Workday had the most combined acquisitions and investments in HR tech start up companies between 2012 and 2016 according to CB Insights. Concur Technologies was the most active investor with 16 investments. Infor, a SaaS HR management company, was the most active acquirer on the same list with 13 acquisitions since 2012. Workday invested in 8 companies and acquired 5 over the same time frame. BGV Perspective Digital transformation of HR can be described along three technology dimensions: mobile, analytics, and social, with cloud being an underlying foundation. Mobile has been by far the most visible change driving the “consumerization of HR systems.” Swipeclock offers a workforce management mobile app that is well designed, delivers a great user experience, and is fine-tuned for user adoption. It is used by over 900,000 users for time, attendance, and scheduling. Benefits to enterprises are increased productivity, fewer errors, and obviated non-compliance. Advanced analytics – AI and ML technologies – are another technology that will play a key role in transforming the HR function. Today, Workday’s system can identify employee job changes that are likely to result in high-performance outcomes (as well as what job moves to avoid). Success Factors can recommend specific training employees should have based on their roles and tasks. In the social arena, ZipRecruiter is a job search engine that connects the right people to the right job. Its powerful technology posts jobs to 100+ job sites across the web, identifies the best candidates, and notifies them to apply to the best fit positions. Digital transformation of HR can also be described along high impact functional areas – recruitment and talent acquisition, performance management, employee engagement, contingent workforce management, and employee training. Recruitment and talent acquisition – Today’s recruitment and talent acquisition market is enormous—an estimated $240Bn in the United States alone based on research by Bersin by Deloitte. This massive market focuses on tools to help companies find strong job candidates, market themselves, distribute job postings, interact with job boards, conduct pre-hire skill assessments, perform background screening and psychological testing, and interview candidates. Applicant tracking systems need to oversee this entire complex process from end to end. Such tools are highly strategic for many businesses. Fast-growing technology companies, for example, can make or break their business plans based on how quickly they can find the right engineers, marketing professionals, and salespeople. Retailers and seasonal manufacturers need to hire hundreds to thousands of people at critical times during the year, so it is key that they find workers as quickly and effectively as possible at scale. Personity (, a BGV portfolio company, is one whose vision is to remove the “bias” from high value business decisions. The company focuses on leveraging AI technology to improve the HR recruiting process by providing personality attributes to improve the screening process, thus reducing cost per hire and the time to fill while reducing turnover. A new breed of platforms, including those from vendors such as SmartRecruiters, Lever, Greenhouse, Gild, and others, have started from scratch, building end-to-end recruitment management systems that handle everything, including sourcing, ad management, analytics, online interviewing, interview management, candidate scoring, ongoing candidate relationship management, and onboarding. Performance management – Brian Kropp, head of HR at CEB, a corporate research and advisory firm that advises on HR practices, revealed that only 4% of HR managers think their system of assessing employees is effective at measuring performance, and 83% say their systems need an overhaul. Reflektive ( is a startup that aims to replace the yearly performance review with a more flexible performance management processes grounded in real-time feedback and a genuine dialogue between supervisor and employee. This tool helps companies embrace the newest trends in performance management by encouraging and enabling continuous feedback especially relevant for Millennials. Employee Engagement – Technology has the potential to address the employee disengagement problem. Disengaged employees are estimated to cost the US economy $500 billion per year in lost productivity. Customer and marketing teams have been developing innovative ways to measure customer input for decades. Today, companies are starting to do the same with their employees by making use of always-on, pulse-based feedback systems. According to Bersin by Deloitte, the consumerization trend is converting HR into a system of engagement that can reach beyond the territory of HR and really engage employees’ inner work lives, rather than being just one of record (certifications, training, etc.). Highground ( offers a cloud-based employee engagement platform to help companies build deeply engaged and high-performing cultures through continuous feedback, ongoing employee development, and real-time recognition. Contingent workforce management – Roughly 40 % of workers in the US are contingent in some fashion, according to government sources, and many of them look for jobs on special networks. Employers use those same channels to post jobs and find people with specialized skills. There are two emerging markets that support this new way of working. The first is contingent workforce management systems, such as Fieldglass from SAP, Kronos, Beeline, PeopleFluent, Workday, and many others. The second market is the gig-work networks that match workers to projects. There are dozens of such solutions, some of which include Upwork, Freelancer, Fiverr, and Workpop. These platforms have morphed from job networks to recruiting and skills-management sites. Employee training – There is a new category of learning products that focus on delivering a “learning platform.” In other words, they are places to browse and learn, and not merely to register for courses. These new platforms bring YouTube-like video experiences to employees and include features for curation, recommended learning, and data-driven recommendations. We believe that this new category of software will become significant as every major company begins to realize that it needs these systems as a complement (or, someday, replacement) for its core learning system. Vendors include Degreed, Pathgather, EdCast, Everwise, LinkedIn Learning, and others. Adoption Challenges Technology and HR are not always comfortable bedfellows. Traditional HR functions tend to play it safe and are usually slow to adopt new technologies. But as the HR function is thrust into the limelight given its potential role in transforming employee productivity, HR leaders will need to be forward thinking in their adoption of new technologies and applying data driven analytical approaches to inform personnel decisions. Furthermore, the generational divide in the workforce will increasingly push HR functions to embed new technologies at a faster pace. This is analogous to how end-user driven smart phone adoption drove IT organizations to embrace mobile technologies. Best-of-breed startups that can deliver value along the key HR functions described above while delivering exceptional user experience and providing simple integration with existing systems will be winners in the digital transformation of HR.

The following blog article was written by Profitect CEO Guy Yehiav, June 16, 2017, in direct response to the announcement of Amazon’s purchase of Whole Foods.  Thought Leadership I recently wrote a blog about a month ago that spoke to the rumors swirling around Amazon possibly purchasing BJ’s. Amazon was quick to distance themselves from the noise, and today’s announcement is a the perfect indicator as to why. Amazon today announced it is acquiring supermarket giant Whole Foods for $13.7 billion. This is a move that will send shock-waves across the food and grocery industry and will be examined and discussed thoroughly in the weeks to come. I stand by my original statements when the possibility of the BJ’s acquisition was brought. I think this is a brilliant move for Amazon into a brick and mortar strategy. A recognizable and valuable brand like Whole Foods enables Amazon continues to position itself as a true innovator and leader in this space. Read below to see why I had positioned this as a strategic move for Amazon to acquire a brick and mortar network: Amazon is looking to optimize its supply chain. It’s been made clear through these speculations that Amazon is looking to extend its supply chain and ultimately create a comfortable way for consumers to shop in warehouses close to them. In the past two years, Amazon has prioritized fast and convenient delivery. Investing in planes, shipping services, drones and trucks – Amazon has spent $3 billion in transportation shipping alone. The endgame is clear: ‘uberize’ last mile service. There really is no better way to streamline this process than by occupying more warehouses and improving the supply chain. It’s also a smart move because warehouses appeal to customers that live in close proximity. They get the same level of quality they expect from Amazon, while simultaneously reducing the cost of delivery and working with a “local” company. Amazon is moving further into a customer-centric model. Let’s face it – each customer is unique and has different wants and needs when it comes to what they buy and how they buy it. Consider two different groups of products that are most commonly purchased on Amazon – they can both be found in seconds and significantly contribute to the online retailer’s success. The first set of products can be defined as ‘mainstream.’ This means items that are being bought every day and are not difficult to find – TVs, laptops, desk supplies, seltzer water or even holiday decorations. Consumers shop for these products on Amazon because they can be delivered quickly, efficiently and at competitive prices. These are Amazon’s reliably movable products, with consistent sales on a daily or weekly basis. The second group is the ‘long-tail products.’ These could be anything from a rare book, a particular part for a car that isn’t sold at your average automotive store or a certain size shoe that isn’t commonly carried. Amazon recognizes that, by having such a wide assortment of products available in one place (in this case, online), consumers will continuously look to them for their needs because of this “one-stop-shopping” model. In fact, this model has been successful to the point of beating out Google as the first point of search for most products. Opening up warehouses that consumers could physically shop in would add another dynamic of tailoring shopping experiences for consumer benefit. For example, if a newly re-branded Amazon warehouse is located just a mile away, a consumer would be able to pick up the exact product they need and Amazon would ensure that it’s waiting for them upon arrival. This comes with the added benefit of being able to conduct regular shopping of mainstream items while in-store, killing two birds with one stone. This is the next logical step in the quest to optimize convenience for consumers, reducing the 24-48 lead time from purchase to delivery to 10 minutes. Thinking long term, this is how Amazon will create the ideal customer-focused retail experience of the future, where shoppers will have their goods waiting for them, and they can be instantly directed to anything else without having to ask an associate or wander the aisles. Despite having backed away from rumors of purchasing BJs, the fact the rumor mill was churning is telling in itself. Amazon is hoping to combine the Brick & Mortar and online models into one convenient location that sells just about everything, while optimizing its supply chain cost down to the last five miles. It is a pretty powerful concept, and one that showcases how Amazon is thinking ahead and disrupting traditional commerce every day. With bringing back the desire to shop in-store, Amazon also generates an opportunity to analyze consumer behaviors in a more granular fashion. When a product is returned for example, Amazon will not only understand why, they also now have the chance to provide the customer the opportunity to replace that purchase with something they may like better – potentially increasing sales converting real traffic in-store rather than only relying on online conversion. Considering that online conversion rates are at 0.08 percent and increase to eight percent in-store, there is significant opportunity for Amazon here.

Anik Bose (BGV General Partner) and Niranjan Venkatesan (BGV intern and Kellogg MBA student) share their perspective on innovation and value creation in computer vision. Computer vision is defined as tasks that include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions. In layman’s terms, computer vision is an arm of artificial intelligence (A.I.) that focuses on enabling machines to “understand” images by processing and analyzing them on a pixel-by-pixel basis, rather than relying on human-controlled categorization data, such as keywords and descriptions. Getting computers to recognize objects just like human beings do remains elusive; 100% accuracy and reliability is almost impossible. As a reference point, the human eye delivers 91% recognition. New technologies such as deep learning are evolving that promise to increase accuracy and reliability dramatically, but these technologies need more research before they can become mainstream. These technologies are modeled on a neural network and will allow the conversion of an image to text or speech. Deep learning will also enable the conversion of text or speech to image or video and the two together can enable tagging, searching, and indexing of a video or image just like text. Some of these new software technologies can deliver a recognition accuracy of 95%. Intellivision, a BGV portfolio company, is able to deliver 98% accuracy for specific vertical applications. Early M&A activity in the computer vision space by larger companies is a lead indicator of the large market potential. The most prominent acquisition being Intel’s recent $15bn acquisition of Mobile eye. Adoption Challenges While the computer vision market forecasts are significant, we believe there are several adoption challenges that must be addressed for the market opportunity to be realized. Key adoption factors include image data privacy concerns, lack of data accuracy, quality and ubiquity, automotive regulations, evolving industry standards and dependence on analytic platforms and applications. These factors, along with operational challenges such as costs, increases in video/image data driven by higher security needs, inability to maintain and fit legacy systems to the new requirements and the difficulties associated with scaling pilots in addition to high bandwidth requirements for hardware, are all rate limiting factors influencing the timing and size of the actual market opportunity. The Venture Investment Opportunity We believe that the computer vision technology stack can be broken down into three layers: a) hardware – This includes cameras, sensors, chipsets and video cards; b) solution frameworks – This includes image-processing algorithms, analytics/deep learning algorithms; c) application – This includes facial recognition, AR/VR and 3D imaging applications. This stack must be applied to proprietary data needed to train the algorithms required to solve specific customer problems. Access to such data will be the long-term differentiator for the winning companies, sometimes more important than the technology stack itself. We believe that there are six specific areas where innovative startups can play a strong role in value creation. These are:
  • Robotics Vision – Driven by demands for the following: safety, quality, reliability, and ease of use, cost efficiencies, benefits of 3D over 2D technology, rapid deployment, and penetration of smart camera in retrofit robotic systems. Key early adopter industries will be automotive and food processing. 6dbytes is an innovative robotics software orchestration company that is targeting the food-processing industry.
  • Visual inspection/Machine Vision – Manufacturers prefer machine vision for visual inspections for their high speed and repeatability of measurements. This accuracy, along with the ability to safely and reliably identify flows and defects in products without disrupting or delaying processes, will create strong demand for computer vision. Key early adopter segments are likely to be the electronics and automotive industries. Drishti is another innovative startup that aims to revolutionize the manufacturing assembly line by digitizing human actions based on technology that can enable non-intrusive and real time observation.
  • Augmented Reality – Applications such as improved logistics in a warehouse, remote monitoring, trouble-shooting and hands free access to contextual information are expected to drive the adoption of AR. Retail and transportation are expected to be early adopter segments. Augment is a startup seeking to transform the retail shopping experience with AR. They are one of the first companies targeting the enterprise B2B space with an end- to-end AR platform.
  • Video Analytics – Intelligent video surveillance to respond to rising threats along with increased demand for business intelligence and adoption of cloud and analytics are also creating the need for computer vision technology. Early adopter markets are likely to be public safety and defense. Intellivision is an innovative BGV portfolio company that provides intelligent video analytics and smart camera solutions for retail, smart home and IOT markets.
  • 3D Imaging – The automotive and construction sectors are progressively adopting 3D imaging solutions for designing, previewing and rectifying the final version of the end products. Fast-paced adoption is expected in healthcare as well for surgical applications and diagnosis.
  • Image/Facial Recognition – Applications will increasingly value code recognition, digital image processing, object recognition, pattern recognition and optical character recognition.   Media and entertainment is expected to be a lead early adopter segment. Finally, facial recognition will be driven by applications such as law enforcement, surveillance, mobile device authentication as well as targeted advertising in retail.
In conclusion, we believe that the analysis of content via computer vision and artificial intelligence is no longer a concept being discussed only in academia. It is an area where we expect to see significant startup innovations that will empower and disrupt existing industries over the next ten years.

In the last part of a three-part blog, Sonal Puri, CEO of Webscale (a BGV portfolio company) shares the company’s vision, how its cloud application delivery platform is differentiated in the market and their move to the broader mid-market. WEB ONLY, CLOUD FIRST We have a saying at Webscale – “Deliver, no matter what.” It speaks to the laser focus we’ve had since the company was founded, to deliver an amazing web application user experience to every one of our customers, regardless of the situation. For our core target of mid-market e-commerce, those situations can vary greatly. Maybe they’re experiencing a major surge in traffic caused by a successful marketing promotion, or maybe their sudden perceived popularity is not so positive and happens in the form of a DDoS attack designed to take their site down. Whatever the circumstances, our promise to our customers is that we have their back, and their site will showcase the highest performance, availability and security that we can deliver, every day, no matter what. In addition to this, is our commitment to delivering the robust feature set of our cloud-based application delivery platform with a level of simplicity that has previously alluded this segment. What do we mean by simplicity? Well, it’s ease of use, first and foremost, and that starts with getting your critical web applications migrated into the cloud, with as little effort as possible, as a software-defined infrastructure. This auto-provisioning methodology means there is no need to re-write, saving massive amounts of time and resources, nor is there any need to lift-and-shift and use only a subset of the cloud’s capabilities. Once you’re deployed in the cloud, Webscale’s automated technology stack manages the rest – from predictive auto-scaling in the event of a traffic surge, content optimization and caching to ensure fast page load times, to a powerful web application firewall that will automatically block malicious attacks and apply rules to prevent any loss of business or corporate reputation. That simplicity continues with easy monthly billing and proactive support that identifies and resolves issues often before they’re even known, and certainly before they cause disruption. End of the day, its peace of mind, and it’s one of the most important things we bring our customers. Make no mistake – the mid-market e-commerce segment is no slouch when it comes to its demands on a web application infrastructure. Flash sales, viral events and seasonal fluctuations make sudden changes in traffic commonplace, and when your customer is likely to go to a competitor if your site takes more than three seconds to load, there is zero tolerance for performance or availability issues. For these reasons, e-commerce has been an excellent foundational segment for Webscale to target, and tackling these challenges has contributed to the development of a number of features that we uniquely enable in the application delivery segment. It’s one of the reasons that Webscale was recently named a Top Innovator in cloud application delivery by research firm IDC, citing simplicity as one of our key differentiators in the space. We predict that more than 90% of enterprise applications will be HTTP/S-based by 2020 based on our own experience with working on large scale enterprise network and application deployments. With its core expertise built around the delivery of web-based applications, Webscale is in the right place at the right time, with a mature platform designed to address the performance, availability and security issues that web-based applications will face when leveraging the public cloud. From migration, to deployment and simple ongoing management, Webscale has become a true partner to businesses wanting to deliver world-class web applications that not only delight their users, but truly use the cloud the way it was meant to be used – as a powerful and utility style computing platform with infinite resources, not just a static and oversized datacenter.

Garrett Gafke, President and CEO of IdentityMind Global, an on-demand online risk management and compliance automation platform. The regulatory focus of the new administration can best be divided into two categories: regulations that address the economy and regulations that address security. In the first bucket are regulations and policies that affect what businesses pay from a tax perspective, and the operational regulations that affect their business practices (e.g. safety, quality, environmental). In the second group are regulations that affect things like cybercrime, human trafficking and financial crimes (e.g. the funding of terrorism, money laundering). In this post, we’ll focus on the security side, specifically on the technology that is being developed to address this problem directly: RegTech. RegTech is the vehicle to simplify and automate regulatory compliance around anti-money laundering and sanctions screening, among others. For instance, the new startups in online lending, online banking, virtual currency and the rest of the companies creating the broader fintech universe have been, up to this point, largely unregulated. RegTech provides the ability for these companies to now have the capability to comply with applicable regulations and to manage risk without having to over-hire, dramatically lower their margins, or worry about what happens as they reach internet scale transaction volumes. The traditional financial services industry can also benefit. While it already has regulatory processes in place, it also carries a ton of cost. Its processes are powered by people connected to legacy systems, which makes them more expensive, less scalable and uneven in quality. RegTech can help them make a difference in terms of effectiveness, thus improving their bottom line with a goal to create real effectiveness and efficiency. However, RegTech companies have generally not had a seat at the table when it comes to figuring out what makes sense in terms of compliance policy, and what is possible in terms of compliance. A seat at the table is important because:
  • Government technology tends to be antiquated. It is in the administration’s best interest to ensure that its platforms are brought up to date and can handle the complexity and scale required by today’s regulatory environment and online businesses. And it’s important that the U.S. government understands not only the state of current technology but also what is coming next so that it can update regulations to take RegTech into account for maximum effect. From a regulatory perspective, RegTech has the potential of shifting the mindset from reactive supervision to real-time preventive and proactive monitoring.
  • Fintech companies have escaped most regulation for the past six years or so. While regulation is coming, imposing regulation for which compliance is too difficult could damage this sector of the economy and hinder innovation. Understanding what is possible through technology is essential because company officers could potentially face prison time if they are not able to meet their compliance responsibilities.
A more appropriate regulatory framework is needed to bolster financial innovation. The framework must ensure the health of the new fintech industry and take advantage of technology innovations to reduce the financial system compliance cost. An inclusive approach with a broader set of voices and stakeholders makes the most sense. And with a large number of banks in the U.S., many of them headquartered overseas, the global ramifications of a U.S.-driven policy cannot be ignored.
Forbes Finance Council is an invitation-only organization for executives in successful accounting, financial planning and wealth management firms.

Anik Bose, BGV General Partner shares his perspective on the digital transformation of manufacturing and the challenges associated with mingling the worlds of information technology and operational technology. The explosive growth in sensors, data and analysis is bringing asset intensive industries into a new era of unprecedented connection and information. This transformation offers these industries the ability to significantly improve their operations and achieve higher levels of productivity. It is estimated that every 1% increase in production efficiency in manufacturing represents $200,000 saving per day per plant in a large manufacturing operation.  This specific example was illustrated by FANUC, a top two industrial robot vendor in the world (e.g., if the utilization rate of a large factory goes up from 85% to 88%, the factory will save $600 K per plant per day. The greater the complexity of the supply chain, the higher the value creation potential. To unlock this value manufacturers are increasingly looking to adopt big data and analytics to improve operational efficiency and increase product quality, across multiple verticals such as pharmaceuticals, chemicals, energy and automotive systems. However, this comes with some inherent challenges due to the complexities of mixing the Information Technology (IT) and the Operational Technology (OT) worlds. To deliver on the promise of the inherent value creation potential we need to build stronger connections between IT and OT at both the technology and organizational levels. The challenge lies in the fact that each system was purpose-built, but neither was designed to work with the other. Technology Challenge In today’s enterprise there is a substantial communication gap between IT and OT technologies. Each uses its own method of connectivity, from the physical connectors and buses that data rides on, to the language each uses to convert bits and bytes into human readable and actionable information. Industrial devices have been designed for long life cycles and as a result use varied physical communication layers, mostly proprietary to their industry. The first step to connect such legacy industrial systems to the IIoT is to provide some type of conversion from these application specific physical buses to open, ubiquitous physical interfaces such as Ethernet and wireless. There is also a need to aggregate smaller, simpler devices like non-networkable sensors or electric circuits into a networked gateway device, in order to transmit the sensor level signals onto standard network interfaces and then into the primary Internet communications protocol – TCP/IP. The biggest challenges to this proposition come from the:
  1. Large number of devices and sensors
  2. Need for low power and low bandwidth connectivity and
  3. Fragmented nature of the vendor market
While a custom protocol can be useful in a single given application, it creates a hurdle in accessing the data required to realize the benefits that digital manufacturing offers. In contrast, IT networks use the same open standards and protocols found on the Internet. The Internet was founded on open standards like TCP/IP. Application specific protocols are layered on top: HTTP/S, SMTP, SNMP, MQIT etc. The Internet uses programming languages like JavaScript, Java and Python and presents information using technologies like HTML5 and CSS, all of which are open. To achieve the promise of Digital Manufacturing, OT and IT technologies must converge, allowing connection and communication. Today, the existing systems and protocols have created “islands of connectivity” caused by the lack of interoperability between open and proprietary protocols. This convergence between them is likely to be enabled through an evolutionary transition beginning with solutions such as protocol gateways, OPC servers and middleware. In the long run, OT/IT convergence will demand a flattened architecture and seamless communication between assets, utilizing open, standards-based protocols and programming. Another area, which is critical for this IT/OT convergence, is the security aspect. The OT systems had inherent built-in security due to the physical separation of the networks – these systems were “air-gapped” from the IT systems. Connecting OT systems creates points of failure that can cause real disruption to the business. Imagine a ransomware attack holding up a factory floor for ransom. Enabling the convergence of IT and OT systems in a secure way is essential for this transformation. People Challenge The above challenges are further compounded by the different skill sets and resistance to change that exists between IT and OT teams. Traditionally there have been separate departments for IT and OT – with different people, goals, skills and projects. Continuing to operate separately not only creates a significant barrier to the adoption of technologies that fall outside the operations- teams’ comfort zone but also exposes companies to fault or security risks that could significantly impact production. To rectify this situation, the strategies of the IT and OT departments need to be aligned and IT and operations managers need to have some common and goals and targets. Joint projects will harmonize duplicate or overlapping systems and processes, and promote the development of the interdisciplinary skills now missing in most companies. This is a significant cultural shift that requires time, trust and a progressive plan. Simple pilot projects are a great way to offer tangible value, train resources and progressively develop the skills of IT/OT skills in the team members. Getting started BGV portfolio company Bayshore Networks ( ) enables industrial enterprises to connect to the internet securely while protecting the manufacturing assets from cyber-based threats.   The company’s product enables asset intensive industries that are seeking operational efficiencies to bridge their IT and OT environments, collect the big data and apply the analytics required to unlock the value of digital manufacturing and mobilize its workforce into the connected world. One key use case is granular secure remote access to industrial devices.  While traditional VPN allows a remote maintenance technician to dial into the OT zone, but the problem is that once that maintenance technician is inside the OT zone, they have access to all industrial devices (Siemens, ABB, Yokogawa, etc), which is a major security problem.  This is why traditional VPN is not a viable tool to enable secure remote access for the OT networks.  Bayshore’s granular Layer 7, secure remote access solution allows remote workers to dial into specific PLC’s, without giving access to all industrial devices. Other use cases range from providing CIP compliance for Utility customers (i.e., ability to enforce/block NERC-005-5), protecting data and systems from attacks initiated through IOT apertures for Data Center customers and safely/securely connecting IT/OT to enable OT data transformation for Manufacturing customers.