Thursday, 11 October 2018

HUMAN RESOURCES : Amazon's AI Human Resources assistant gets unplugged for being sexist!!!



Amazon.com's machine-learning specialists uncovered a big problem: their new recruiting engine did not like women.

The team had been building computer programs since 2014 to review job applicants' resumes with the aim of mechanizing the search for top talent, five people familiar with the effort told Reuters.

The company's experimental hiring tool used artificial intelligence to give job candidates scores ranging from one to five stars — much like shoppers rate products on Amazon, some of the people said.

The group created 500 computer models focused on specific job functions and locations. They taught each to recognize some 50,000 terms that showed up on past candidates' resumes. The algorithms learned to assign little significance to skills that were common across IT applicants, such as the ability to write various computer codes, the people said.


Instead, the technology favored candidates who described themselves using verbs more commonly found on male engineers' resumes, such as "executed" and "captured," one person said.

"Everyone wanted this holy grail," one of the people said. "They literally wanted it to be an engine where I'm going to give you 100 resumes, it will spit out the top five, and we'll hire those."

But by 2015, the company realized its new system was not rating candidates for software developer jobs and other technical posts in a gender-neutral way.

That is because Amazon's computer models were trained to vet applicants by observing patterns in resumes submitted to the company over a 10-year period. Most came from men, a reflection of male dominance across the tech industry.

In effect, Amazon's system taught itself that male candidates were preferable. It penalized resumes that included the word "women's," as in "women's chess club captain." And it downgraded graduates of two all-women's colleges, according to people familiar with the matter. They did not specify the names of the schools.

Amazon edited the programs to make them neutral to these particular terms. But that was no guarantee that the machines would not devise other ways of sorting candidates that could prove discriminatory, the people said.

The Seattle company ultimately disbanded the team by the start of last year because executives lost hope for the project, according to the people, who spoke on condition of anonymity. Amazon's recruiters looked at the recommendations generated by the tool when searching for new hires, but never relied solely on those rankings, they said.

The company's experiment, which Reuters is first to report, offers a case study in the limitations of machine learning. It also serves as a lesson to the growing list of large companies including Hilton Worldwide and Goldman Sachs that are looking to automate portions of the hiring process.

Some 55 percent of U.S. human resources managers said artificial intelligence, or AI, would be a regular part of their work within the next five years, according to a 2017 survey by talent software firm CareerBuilder.

Employers have long dreamed of harnessing technology to widen the hiring net and reduce reliance on subjective opinions of human recruiters. But computer scientists such as Nihar Shah, who teaches machine learning at Carnegie Mellon University, say there is still much work to do.

"How to ensure that the algorithm is fair, how to make sure the algorithm is really interpretable and explainable — that's still quite far off," he said.

Tuesday, 2 October 2018

STRATEGY : Why great companies fail? The case of Nokia, IBM and Kodak

This article is an edited version of "Why Successful Companies Usually Fail" from INSEAD knowledge portal. The original article can be accessed here.

The annals of business history are replete with the names of once great companies that dominated an industry, only to lose pre-eminence and become shadows of their former selves or even disappear. Understanding why powerful companies fail and how to avoid such failure is one of the holy grails of business and management research, not to mention having spawned an enormous and lucrative consulting industry. Yet, the very fact that successful companies continue to fail is testament to an incomplete understanding of the drivers of corporate demise.

Examples of failed giants are abound. Nokia in mobile telephony, Yahoo in internet search, Sanyo and Sharp in consumer electronics are some popular examples.

“Ringtone: Exploring the Rise and Fall of Nokia in Mobile Phones”, a recent book which won the 2018 Academy of Management’s prestigious Terry Book Award, charts and analyses Nokia’s journey. With a perspective with over 20 years of research at Nokia Mobile Phones; a business that shaped an industry it came to dominate with one of the strongest brands in the world, only to all but disappear in a fire sale to Microsoft.

The researchers found that found that what leads a company down a competitive dead-end is a combination of management decisions, organisation adaptation and industry evolution, with each playing a more or less prominent role over time, and the inter-dependencies between them becoming lethal.

1. Management Choices

Management choices obviously contribute to a company’s decline, but it isn’t just the decisions of the incumbent management team that play a role. The seeds of strategic stagnation are usually sown by management choices made a decade or so earlier. It is these decisions that lead to the problem-solving techniques that utilize self-educating techniques (heuristics), commitments which were made earlier and unchangeable and excessive overconfidence due to their previous successes that create a context in which future action is taken.

Strong heuristics, particularly from the unconscious or unintended learning a company experiences as it grows and overcomes crisis situations, become implicit ‘principles’ in decision-making. So, for example, in its early days, having invested huge sums in technology development, Polaroid found there was a very limited market for its expensive instant cameras and certainly not one large enough to sustain the company. 

In the face of this crisis, Polaroid adopted a film-first, ‘razor blade’ model whereby it sold cameras at cost but made a huge margin (around 70 percent) on the film for its cameras. This simple heuristic, that only film makes money, became entrenched and shaped future management decisions for the next 30 years. Even though Polaroid recognized the need to invest in digital technologies as early as 1985, successive management teams framed the challenge too narrowly in terms of ‘printing’ digital images rather than producing affordable cameras to capture images (as Japanese competitors Sony and Canon were doing). After numerous CEOs, restructurings and ‘new strategic directions’, Polaroid filed for bankruptcy.

Poor and inadequate cognitive framing can also result from ‘creeping commitments’ – past decisions to which a company becomes hostage and which sets them on a direction from which it is difficult to deviate. 

Here, Nokia’s Symbian operating system provides a good example. Initially adopted by a consortium of mobile phone producers in 1998 in a bid to stave off the threat of Microsoft entering the industry, over time Nokia’s commitment to and continued investment in this device-centric operating system had a profoundly negative impact on its ability to adapt to a platform and ecosystem approach.

Success tends to breed hubris and this, in combination with the voracious appetites of certain classes of shareholder, can lead to managers focusing on the operational issues which will drive greater efficiency for the benefit of short-term results and not long-term sustainability and growth. 

This is what happened at IBM under the leadership of Sam Palmisano, who was so focused on doubling shareholder returns every five years he failed to see, or acknowledge, that the competitive environment was changing. With no response to this shift, IBM was in serious trouble – although this wouldn’t become apparent to the outside world until a few years later.

2. Organisation Adaptation (Business models, structures & processes)

Management choices lead to the implementation of structures, processes and business models which if left unchallenged can result in dysfunctional rigidity and become a formidable constraint to much needed adaptation further down the line.

Business Models

At IBM, it wasn’t long after Ginni Rometty succeeded Palmisano as CEO that the depth of problems began to show. 

The IBM business model of selling expensive hardware AND software AND expertise to use those systems were getting outdated with new business models. For years, this business model had stifled growth initiatives at IBM and made change extremely difficult. Fewer corporate customers were buying hardware in favour of cloud solutions and ‘software as a service’ (SaaS) and this had a significant impact on the firm’s performance. 

IBM had to abandon hardware and software sales and reinvent itself as a IT consulting and technology company. IBM sold off printer manufacturer Lexmark in 1991 and selling off its personal computer (ThinkPad/ThinkCentre) and x86-based server businesses to Lenovo (2005 and 2014, respectively) and shifted its business mix by focusing on higher-value, more profitable markets. 

It acquired companies such as PwC Consulting (2002), SPSS (2009), and The Weather Company (2016). Also in 2014, IBM announced that it would go "fabless", continuing to design semiconductors, but offloading manufacturing to GlobalFoundries.

Organisation structures

Organisation structures can prove just as big an impediment to much needed change as out-of-date business models. Nokia found itself mired in infighting and intense internal competition due to matrix structures which proved difficult (and ultimately impossible) to manage as different groups with vested interests sought to protect their corners. 

In this scenario, under performance pressure, misinformation from business groups tends to filter upwards giving senior management a false impression of how a company is faring. Combined with a lack of internal collaboration that prevents people from ‘connecting the dots’ which point to changes in the external environment, it becomes clear how structure can play a large part in pushing a company towards failure.

3. Industry Evolution / Changing Environment

When the very nature of an industry changes, this is bound to result in casualties and successful incumbent companies are perhaps the most vulnerable as they are more likely to be locked into a co-evolution with existing partners, suppliers and major customers when it comes to a vision for the future. 

In addition, both management choices and the level of organisational adaptation will make it more or less difficult for a firm to step out of its current business model and recognise the environment around them is radically changing.

Neither the board nor the management of Kodak understood how fast the environment was changing from film to digital photography, and so management choices fatally reinforced the importance of the core film business. 

With the support of IBM’s board, Palmisano was so focused on increasing shareholder returns that he failed to see the locus of competition was shifting to the cloud and on-demand. They stayed focused on selling expensive bundles of hardware and software until it was almost too late.

Nokia was so locked into its product-centric view of the industry, and focused too much of the perceived threat of Microsoft, its management couldn’t conceive of the ecosystem-based future Apple and Google were creating. 






Monday, 24 September 2018

CORPORATE STRATEGY : Timeless lessons from Bill Gates, Andy Grove and Steve Jobs

The Five Strategy Rules of Gates, Grove and Jobs
  1. Look forward, reason back
  2. Make big bets, without betting the company
  3. Build platforms & ecosystems, not just products
  4. Exploit leverage & power
  5. Shape the company around your ‘personal anchor’

1. Look Forward, Reason Back

Strategy must be forward looking. Look towards the end game. and then reason back to the actions which produce the desired outcome.

Bill Gates - Microsoft

This aspect of strategy is best illustrated by the stated vision of Bill Gates which he articulated around 1975. 

"A computer on every desk and in every home and Microsoft software running inside them..." 

Gates purposefully stayed away from making hardware due to the fact that hardware was getting ever more powerful and cheaper by the day. Gates reasoned that computing hardware is becoming commoditized and low margin and hence and there is not point in selling hardware. What makes this hardware realize it full potential and do what it is designed to do? Software.

Bill Gates did everything possible to make sure that every micro computer (a.k.a PC) that was ever made ran Microsoft software. A brilliant masterstroke by young Gates was that he managed to convince the negotiators of IBM that the operating he was contracted to write for IBM Personal Computers (called PC DOS) where Microsoft should get the rights to license his PC DOS to other PC clone makers. 

This was truly a masterstroke. Gates knew that IBM created the PC as an open standard hardware system. This not only meant that any hardware maker could easily make peripherals and devices that worked with the system but also that anyone could legally copy the design and make IBM PC clones. Bill Gates knew that if IBM created a standard, the world would follow it. IBM was the world's largest and the most powerful computer company at the time.

Gates was right and hundreds of manufacturers in the US, Europe, Taiwan, Hong Kong and Korea started creating cheaper IBM PC clones and licensed the operating system from Microsoft. By the mid 80's and early 90's the world was full of millions of PC clones running Microsoft software. 

2. Make big bets, without betting the company

Andy Grove - Intel

Andy Grove was instrumental in building Intel into the world’s largest microprocessor company during his 37-year career there. He was a mercurial but visionary leader who helped position Intel’s microprocessors as the central technology inside personal computers.

Intel created the world’s first commercial microprocessor in 1971, but the company’s primary focus was memory chips for mainframe computers. That was until the personal computer was invented and a new use for Intel’s microprocessors emerged. Grove’s leadership of that transition affirmed his status as a key figure in the digital revolution and an icon of business leadership. Grove was named Intel’s president in 1979, took the CEO job in 1987 which he held until 1998.

Grove’s gamble – moving Intel from memory chips to microprocessors in the early 1980s to serve what was still a fledgling PC industry – helped rescue Intel from a financial crisis and set it on course to becoming one of the most profitable and important technology companies of all time.

When IBM was creating the IBM PC open standard for personal computers during 1978-1980 period, it chose Intel's 8088 processor. The 8088 was targeted at economical systems. IBM chose the 8088 because under the guidance of Grove, Intel offered a better price and could supply more units. Since IBM created the PC system around Intel's processors, every PC clone maker had no choice but to buy Intel's chips propelling Intel to the global leadership in microprocessors.

3. Build platforms & ecosystems, not just products

Steve Jobs - Apple ecosystem

If anyone understood the importance of building platforms and ecosystems centered around their product, its Steve Jobs. Unlike IBM which created the open standard PC system, Apple's computer systems and other products were intentionally closed and tightly controlled to make sure they work well with each other.  This is one of the main draws of using Apple products - they work so well they work with each other. It feels seamless because everything you need is already built in; there's no need to download or install anything. Apple set out to build a complete ecosystem based on its devices and operating systems with the iMac and iBook in the late 1990s.

That ecosystem is part of the reason why many iPhone users will also use a Mac computer and vice versa, as some features wouldn't work if you mixed it up with a Windows computer or an Android phone.  iTunes, iPods, iPhone, Apple watch are all designed to work well with each other and transfer data seamlessly. Apple’s steady evolution of services like iCloud and Apple Music, and cross-platform software features like AirDrop, Handoff, Find Friends, Universal Clipboard, and Auto Unlock mean iPhones are at their best when used with other Apple gear like MacBooks.

Bill Gates / Andy Grove - Wintel Alliance

It wasn't just Steve Jobs who understood the power of building a platform and an ecosystems. Both Gates and Grove understood it too. That's why they created the infamous Wintel alliance (Windows + Intel) between Microsoft and Intel where Intel kept on creating ever powerful processors and Microsoft kept on creating, newer and more powerful versions of Windows operating system that could harness the power of the newest Intel processors. 

While Intel did everything it could to lock hardware makers to use Intel chips and intel certified motherboards and chipsets inside the machines, Microsoft drove a hard bargain making sure that every Intel Inside PC had a licensed Microsoft Windows installed. 

Microsoft's ecosystem didn't stop there. They created immensely popular office productivity software MS Office which bundled a word processor, a spreadsheet programme and a presentation software and some other useful utilities as well. When MS Office was launched in 1990 as a software bundle, it instantly became another Windows based ecosystem where one application could share data with another application with ease. Since one couldn't by MS Word as an independent programme after it became bundled into the MS Office suite, it forced people to start using the other programmes in the bundle as well. This ended the hugely successful runs independent software companies like Lotus, which created Lotus 123 spreadsheet programme, WordPerfect word processor created by SSI and dBASE database software created by Ashton Tate.

People did not buy Wintel based PCs for their ease of use, that honour went to Apple Macintosh, people bought Wintel PCs due to the huge software base and peripheral base (which included printers, scanners, CD Drives, video accelerator cards etc.) that was created for the Wintel ecosystem. 

4. Exploit leverage & power

Bill Gates 

In the early days Bill Gates leveraged the small size of his company to convince IBM to let him license the PC DOS operating system to other PC makers. IBM probably did not take this young lad in bottle rimmed glasses too seriously to ponder the thinking behind the request. It was too late when they realized what they had agreed to.

As Microsoft got bigger, it shamelessly used its dominant position as the only OS maker to strong-arm PC makers as well as software developers and software users to impose its licensing policies that not only protected its virtual monopoly but also extracted the best fee.  

Microsoft has over the years destroyed many competitors. They destroyed the hugely popular Netscape internet browser in the early days of the world wide web (1994-) by buying the web browser technology from a small company called spyglass. They used the spyglass browser engine to create Internet Explorer which MS started giving free. There was a time when Internet Explorer was included in every computer magazine's free software CD. They were giving free what Netscape charged $49! 

Is there any better example for leveraging and using power?

Gates also leveraged the power Microsoft had in operating systems into creating an office productivity software bundle which included expensive software, which users previously had to buy separately from different companies and did not work well together. MS Office bundle let to the demise of popular programmes like Lotus 123, WordPerfect, WordStar, dBASE, Harvard Graphics (presentation software) and companies that created those products.

Andy Grove

When IBM chose Intel's 8088 processor over the competitors, it open the door for the company become the world's number one microprocessor maker. Andy Grove saw this door opening and made sure that it stayed open for ever. 

There were other companies who were making PC compatible microprocessors. Advanced Micro Devices (AMD) is one such company.  Intel gave a licence for AMD to manufacture its 8088 processors so that it could win the IBM PC contract. Later Intel revoked this agreement and did everything possible to make sure that AMD would not become a credible alternative to Intel supplied processors.

Intel strong-armed PC manufactures to exclusively use their processors in exchange for various technological benefits the company could give to the PC makers.

According to documents submitted in a 2005 court case filed by AMD, Intel is accused of leveraging its dominant position an power in following manners.  Intel has forced major customers into exclusive or near-exclusive deals through;
  • Conditional rebates, allowances and market development funding on customers agreement to severely limit or forego entirely purchases from AMD
  • Intel has threatened retaliation against customers introducing AMD computer platforms,particularly in strategic market segments; 
  • Intel has established and enforced quotas among key retailers effectively requiring them to stock overwhelmingly, if not exclusively, Intel-powered computers, thereby artificially
  • limiting consumer choice.
  • Intel has forced PC makers and technology partners to boycott AMD product launches and promotions;
  • Intel has abused its market power by forcing on the industry technical standards and products which have as their central purpose the handicapping of AMD in the marketplace. 

5. Shape the company around your ‘personal anchor’

Grove

Grove was a disciplined engineer and he created a company culture that was based on his ethos. Grove had a legendary temper and he could berate people for showing up late to work. But people who worked with him always held him in high regard. He gave off an undeniable charisma. He was funny. One former Intel exec described him as the person you would “follow up a hill in battle.”

Andy Grove was known to use his confidence in a way that made everyone around him feel more confident as well. There was never an air of inequality or superiority. Grove was one of the first executives to sit in an office cube with his employees. He created this arrangement to eliminate barriers between the executive team and the staff, and to make himself available for all feedback.

“Intel is a data driven company and the phrase is, ‘Don’t argue with the emotions, argue with the data.’

Measurement against a standard makes you think through WHY the results were what they were. Former Intel executive Pat Gelsinger said once: “If you went into a meeting with Grove, you’d better have your data; you’d better have your opinion; and if you can’t defend your opinion, you have no right to be there.” 

Jobs

Jobs was a creator at heart. He loved creating beautiful, well crafted devices that are a joy to use. For Jobs, design was not just art, but also engineering perfection. He created the company in this way. He questioned everything, drove everyone towards his vision and made sure that the products which came out of Apple were world class.


Sunday, 23 September 2018

BRANDING : How could BMW be a better loved brand than Maggi Noodles or Lion Beer in Sri Lanka?


Disclaimer : Author(s) have no interest or affiliation with any of the brands mentioned here other than academic curiosity.

Last April (2018), brand valuation company, Brand Finance in partnership with the business magazine LMD unveiled the highly anticipated brand report. Among the report, there are "Most Valuable Brands" and "Most Loved Brands" rankings.

Page 9 of the LMB Brands Annual 2018 issue helpfully describes the methodology and the processes they undertook to create the rankings. They describe a 7 step process which starts with "brand strength calculation". Brand strength is calculated using a number of variables. While the full list of variables used is not shared, "brand equity", "financial performance" and "sustainability" are listed as variables used.

According to the methodology, brand equity is measured using market research. The page 9 of the 2018 Brands Annual states that the brand equity is an important indicator of Brand Strength Index (BSI) and this is established using market research data collected by an independent research company. According the data supplied, they surveyed 1750 persons from Colombo and Gampaha for this purpose. 

SAMPLE SIZE

Sri Lanka has 21 million people and 5 million households. According to Department of Census and Statistics , In 2017 Sri Lanka had a total of 8,583,082 economically active (a.k.a gainfully employed) persons and out of which 6,732,711 persons or a whopping 78% lives in rural areas.

How statistically significant would be a sample size of 1750 from Colombo and Gampaha to measure the brand choices of 8,583,082 economically active people, out of which 6,732,711 lives in rural areas of the country? Of course there is conventional wisdom among the FMCG and Market Research fraternity that Gampaha is the most representative district. It is not clear how this conclusion was arrived but this has been the consensus since the author was a student of CIM decades ago. Whether anyone in the market research fraternity done any research to validate this assumption is not clear at all.

How could BMW be a better loved brand than Maggi Noodles or Lion Beer (in Sri Lanka, not Dubai..) ?

The above shows the best loved brands in the country. While the writer would not contest the top 5 in the list, it seems almost beyond belief that a brand like BMW, the luxury German car managed to get into number 44, while Maggi, one of the staple snacks of the Millenials and Gen Z is at a distant 85. Could this be right? How many of the surveyed 1750 respondents drive a BMW or had any meaningful interaction with the brand for them to rank it way higher than Maggi which I am sure almost everyone tucks in at least once in a while.

How could all time favorite Lion Beer go down to 113 as in terms of "brand love" in a country of record alcohol consumption?

Sony at number 6 is another surprise. In a country where most people buy Samsung (which is at number 35), LG or some other Chinese brand, Sony, the 80's favorite occupies number 6! Baby Cheramy, Pears Baby are 33 and 36 positions respectively when the much more expensive Johnson's Baby which is beyond reach for most young families get the number 8 position? Does it mean that mothers use Baby Cheramy on their precious babies but love Johnson's Baby? Is that brand equity?

Does it mean that people who drive Suzuki Alto's actually love BMWs and Honda's? Does it mean that people buy Samsung, LG or Singer but they love Sony? 

We really don't know. 

Hopefully the brand managers of these companies would start questioning the results because they don't make a lot of sense. 

ENTREPRENEURSHIP / STARTUPS : Chamath Palihapitiya's new bet - Capital as a Service (CaaS)

Capital as a Service funds early stage companies based on their fundamental metrics and merit: no expensive coffees, “warm introductions” or designer pitch decks. Founders fill out a form, upload their transaction or engagement data, and then get a response: helpful data-driven feedback on their submission and their business, and hopefully a financing offer as well. 

In 2017, Social Capital partner Ashley Carroll has led a minimum viable product (MVP)  of CaaS that evaluated over 3,000 companies and led to the successful funding of several dozen of them. 

Social Capital evaluated nearly 3,000 companies during its MVP and committed to funding several dozen across 12 countries. An interesting byproduct of the data-oriented approach was that CEO demographics skewed 42% female and majority non-white. (For context, female founders received 2.19% of venture capital funding in 2016.) In an email to press, Social Capital CEO Chamath Palihapitiya called the 42% data point “simply fucking awesome.”

It’s no surprise that the firm is taking this route. For years, Palihapitiya’s vision has been pretty clear — operational experience coupled with a focus on data. But as Social Capital begins to expand and veer toward being stage-agnostic, some people aren’t on board with the direction the firm is taking. 

Palihapitiya seems to be hyper-focused on this data-driven approach, and he reiterated his plan to make Social Capital a full-service capital partner to the businesses it invests in throughout their life cycles. He added:

“CaaS is designed for entrepreneurs who are either over-served or under-served by today’s venture status quo. In that first bucket: founders who prefer a low-touch, highly efficient funding process, or don’t want to give up a large chunk of ownership in their company. In the latter: founders outside Silicon Valley and the US more generally who often don’t have access to Silicon Valley-based firms, nor the networks necessary to get the right warm intro.”

First of all, (for the curious) what is MVP?

Minimum viable product is a version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort. A key premise behind the idea of MVP is that you produce an actual product (which may be no more than a landing page, or a service with an appearance of automation, but which is fully manual behind the scenes) that you can offer to customers and observe their actual behavior with the product or service. Seeing what people actually do with respect to a product is much more reliable than asking people what they would do. The primary benefit of an MVP is you can gain understanding about your customers’ interest in your product without fully developing the product. The sooner you can find out whether your product will appeal to customers, the less effort and expense you spend on a product that will not succeed in the market.

What exactly is CaaS?

Capital as a Service is a big step into the future, and like most big steps, it goes against the grain of a lot of conventional wisdom. The Venture Capital industry, which makes a living by betting on change that disrupts and reorganizes other industries, still holds this steadfast belief about itself: that’s just the way things are done here. It won’t change. CaaS intends to change this and disrupt the VC process. 

The alpha version of Capital-as-a-Service (“CaaS”) works in the following manner. Founders engage with Social Capital online for diligence and funding. Without so much as a plane ticket or a coffee chat, entrepreneurs submit their transaction data to the automated diligence engine and CaaS can make funding decisions in a matter of hours. Overnight, through software, open for business on six continents 24 hours a day, 365 days per year.

With CaaS, the goal was to launch a new operating system for early stage investing, built on the principles of data-based decisions and architected for global reach and scale. A platform that would enable any founder, anywhere in the world, to short-circuit the arcane frictions of the traditional fundraising process and get straight to the heart of what matters: the product-market fit and the compounding value created for customers. CaaS concept sought to make decisions that were transparent, consistent, and unbiased, and to offer a feedback loop to entrepreneurs based on the predictions of the models.
(C) Social Capital LLP
According to a post by Social Capital partner Ashley Carroll, the point-person of the company's CaaS effort;

"At Social Capital, we’re most excited about entrepreneurs that challenge assumptions, that take a non-consensus view of the world, and then validate that view with experiments and data. 

It’s only natural that we’d apply that same lens to our own discipline. In that process it’s become clear that some of the assumptions upon which early-stage venture investing was founded don’t hold to be true. 

With this insight, we’ve been working on something with the potential to disrupt the status-quo and accelerate our mission: capital-as-a-service, a new operating system for early-stage investing..."

The anatomy of traditional venture capital hasn’t changed in the past 30 years. Face-to-face interactions and human judgement, followed by (at best) a few thin Excel models and relationship-driven diligence creates a high propensity for bias and a low propensity for scale. 

This is a classic example of a sector ripe for disruption. Today, every industry is being revolutionized by the application of data: from healthcare to logistics to media and beyond. If the operative question is whether early-stage investment decisions can be better made with data than intuition, using virtually every other discipline as a guide the answer is almost certainly yes...

No hoops, no $7 artisanal coffee chats, no designer pitch decks, no bias, no politics, no bullshit. Just the best teams with the best ideas, the best execution, and the best metrics funded on the merits of their achievements, not the status characteristics of their founders or the exclusivity of their professional networks...."

Social Capital CaaS process





Sunday, 16 September 2018

DIGITAL ECONOMY : UK's Digital Economy Strategy - A Primer


In January 2018, there were news reports that work has begun on the Digital Economy Strategy with the help of McKinsey. According to the reports at the time, the strategy document was to be made public in April 2018. However, it is mid September already and there is no sign of the strategy document.


We at Colombo Business Blog thought that it would be a good exercise to analyse some first world digital strategies - starting with the UK - so that we could benchmark our own digital economy strategy document when it eventually see the light of the day.


UK DIGITAL ECONOMY STRATEGY

The original source documents could be accessed here and here


The UK's place in the world digital landscape



The UK tech sector can be said as a shining light in Europe, but Brexit is a serious challenge. It is therefore critical that the UK looks beyond its borders and the EU and set its sights on a truly international scale.

The tech sector has experienced rapid growth over recent years, both across the UK and beyond. At each stage of growth, ecosystems experience shared challenges and find shared strengths.

Software, IT and telecoms services together generated 4.2% of UK gross value added (£59bn) and provided 885,000 jobs in 2011. By 2014 digital economy employed 1.3 million people in 2014, 5% of all employees in Great Britain. Between 2014 and 2017 employment in the UK's digital tech sector increased by 13.2%. Uk workers in digital tech are also more productive than those in non-digital sectors, by an average of £10,000 per person per annum.

UK has 107,000 software businesses, and are the world’s number two exporter of telecoms services (£5.4bn) and number three in computer services (£7.1bn) and information services (£2bn). By 2014 there were 204,000 digital economy businesses, 9% of the UK total in 2015.  The UK has world-class strengths in communications, especially wireless technologies; software development, computing and data analysis; cyber security; and user experience and service design.


In UK, 33% of tech company customers are based outside the UK, compared to 30% in Silicon Valley and 7% in Beijing.  25% of the world’s entrepreneurs report a significant relationship with two or more others based in London, a figure beaten only by Silicon Valley.


The UK is a global leader in digital tech investment


The UK was in the top three countries for total capital invested in digital tech companies from September 2016 to August 2017, behind only the US and China. Only the US has a higher number of deals.

Total investment and number of deals in digital tech companies have risen significantly since 2012. From £984 million in 2012, spread over 870 deals to £3.3 billion in 2016 over 2645 deals – both deal count and investment have more than tripled over the four year period. In this period average deal size has increased incrementally – from £1.13 million in 2012, dropping to £0.94 million in 2013, and then steadily rising year-on-year to £1.25 million in 2016.















Challenges for UK digital businesses (especially start-ups and digital SMEs)


Low working capital

New companies have low working capital and less opportunities to inject new working capital, affecting their resilience and ability to build the relationships they need in order to break into a complex and competitive market.

Skills shortages

The forces that create a dynamic and fast-moving innovation culture also create skills shortages, particularly as innovation gains pace.

Getting Heard / Getting Noticed

With more than 200 smart-home demonstrators in the UK and more than 3,000 e-health applications on the European market, how can the new ideas of a small, unknown company be heard?

Intellectual property

The cost and delays encountered in protecting intellectual property contrast with the speed of technology change, leading small companies to look for competitive advantage through agility and know-how instead of through long-term strategies such as patent registrations or diversification.

Tribal boundaries

Successful digital businesses fuse technical expertise with creative flair and an understanding of their customers. However, this fusion means erasing the tribal boundaries between ‘geeks’ and ‘luvvies’ or tech people and marketing / creatives / public relations people working in the industry. These cultural divisions within the digital community can be as hard to overcome as the gaps in understanding between technologists and their clients.

Funding support

Support from government, investors and clients can be less agile than the companies themselves, and is often designed around traditional innovation models and linear product development processes. The drag of this support on companies’ time and resources can even outweigh the value on offer.

Rapid scaling

Digital platforms often succeed based on the size of their user base. This pressure to ‘go big or go home’ tempts businesses to scale up customer numbers rapidly, often before business structures are properly in place.

Investor confidence

With a short product cycle, rapidly evolving technology and markets, and high churn of companies, the digital industry lacks a coherent strategic roadmap, challenging confidence in long-term investment in digital capability

Growth Areas for UK digital economy

Mobility
Internet of Things 
Data Mining
Enterprise Services 

Objectives of the UK Digital Strategy
  1. Encouraging digital innovators
  2. Equipping the digital innovator 
  3. Focus on the user
  4. Growing infrastructure, platforms and ecosystems 
  5. Ensuring sustainability

Encouraging digital innovators


We see two main constituencies of digital innovators: the technical expert providing technology and digital solutions, and the digital champion driving change through an established business.

The strategy is to;
  1. Ensure that business support, encouragement and investment is available to those developing digital ideas
  1. Help early-stage digital businesses to connect to established businesses and potential lead customers in industry and government
  1. Help established companies find the innovators who can help them develop digital solutions, including bringing digital expertise to bear on Innovate UK’s activity in health and care, transport, energy, built environment and creative industries
  1. Help these digital innovators to drive change, whilst managing risk to existing business flows
  1. Encourage innovators in different sectors to share knowledge, develop common approaches and translate and reuse experience from other industries.


Equipping the digital innovator

Digital innovation requires the deployment of technology into business systems. To create a user experience requires products and services, and to create these requires engineering and business design.

The strategy is to;
  1. Support tools and systems that streamline transaction flows; that allow data, content, metadata, value and permissions to be moved seamlessly without manual intervention; that are trusted by businesses; and that protect the value of digital assets.
  1. Help businesses to develop technology and services that bring the benefits of the digital world into the user context of the physical world.
  1. Work with data and content owners on tools and systems to improve the quality of existing and future data sources and their suitability for secondary use, and with web and mobile service designers on tools for software design that take advantage of these resources.
  1. Help businesses to build confidence in the commercial and user value of their products.


Focus on the user

Good business strategies begin not with the product, or the commercial model, but with the user. Understanding users and their needs is of paramount importance to all business – from digital start-ups to existing businesses that are digitising. 

Once they understand this, they can design elegant solutions that provide an excellent user experience. This is more evident when designing direct customer-facing products, but remains true further upstream for those offering services to other businesses. Somewhere, there is always a human.

The strategy is to;
  1. Encourage digital businesses to think about their users’ needs and the user experience at every step of product development
  1. Ensure that digital products are trusted, by helping businesses to design their systems for resilience, privacy and consent, identity management and data security
  1. Help businesses to develop products that are available when needed, and that relate and adapt to the place and context within which they are used
  1. Invite businesses to consider inclusive or adaptable designs, so that they can create a compelling experience for the broadest possible market.

Growing infrastructure, platforms and ecosystems

The digital economy is connected. Communications networks move data and deliver services; the traffic is handled by software and data management platforms; devices provide the final bridge to the real world and the user. 

This intricate system is joined together by tools and interfaces that connect businesses into digital supply chains, facilitating data transfer, transactions, payments and hand-offs of metadata and security information. 

Each of these elements has the potential to create a marketplace for users and suppliers. Interoperability, open standards and architectures, and interfacing standards such as APIs (application programming interfaces) and metadata standards all contribute to market defragmentation, as do regulations to promote open competition and free trade.

The strategy is to;
  1. Support businesses developing interoperable infrastructure and software platforms and enablers that can be used by multiple client businesses, and encourage industry-wide common practice to broaden the market for their suppliers and their users.
  1. Support new entrants to build up digital ecosystems around these platforms, and help them with tools and connections, until the activity reaches a critical mass that enables them to scale. This encompasses interoperable open systems ranging from open data to ‘internet of things’
  1. Help communications and device businesses, and software and data systems businesses, to work together with service and applications businesses to support one another’s investment cases and to design complete user solutions
  1. Work across Europe and worldwide to help establish common practice and fluid trading systems that will support UK digital innovators as they export.


Ensuring sustainability

Digital innovation draws on information and communication technologies and component hardware. We support the development of this capability through our enabling technologies strategy. But digitisation is not just about technology. It streamlines and reroutes business processes and workflows, it disrupts the way we manage transactions and how we think about value, and it redesigns human experiences and changes the way we interact with one another. 


In our digital strategy, therefore, we must also draw upon social and economic science, understand the role of law and regulation, draw on design expertise and consider the psychology of the marketplace. This requires multidisciplinary effort and often raises questions for policy makers or exposes unanswered questions for research. Innovate UK, in collaboration with Forum for the Future and Aviva Investors, has developed the Horizons framework.

The strategy is to;
  1. Work closely with the UK research councils to encourage cross disciplinary academic collaboration and help connect it to real-world business needs.
  1. Work with government and regulators to ensure that legal, regulatory and policy frameworks are supportive of digital innovation and business growth, and collaborate in delivering those policy initiatives that invite business innovation.
  1. Work with skills agencies and universities so that appropriate skills are available to both product designers and individual and commercial product users, to ensure confident deployment and adoption.
  1. Use, and encourage others to use, the Horizons framework when developing strategies and plans.
  1. Work alongside other support bodies and the third sector, so that our support for commercial progress can be balanced with support for social progress.