Month: January 2019
How The CIO Role Must Change Due To Digital Transformation – Peter Bendor
Digital transformation is sweeping through businesses, giving rise to new to new business models, new and different constraints, and presenting a need for more focused organizational attention and resources in a new way. It is also upending the C-suite, bringing in new corporate titles and functions such as the Chief Security Officer emerge, Chief Digital Officer and Chief Data Officer. These new roles seemingly pose an existential threat to existing roles – for example, the CIO.
As companies invent new business models through digital transformation and bring new organizations into being, they do more than cover new ground. They also carve new roles out of existing organizations (the CIO organization, for instance). Other digital threats potentially affect the CIO role:
- Recognition that digital transformation now makes technology THE business, rather than technology supporting the business; therefore, IT and CIO roles are much more vital to growth in sales.
- Competing through new digital models and digital platforms, focusing on redefining the customer experience and employee experience to create and deliver new value.
At Everest Group, we investigated the question of “Will the role of the CIO go away?” As a result of that investigation, we come back strongly with “no.” In fact, here’s happening to the role of the CIO: the CIO charter is changing and thus changing – but strengthening – the role.
Reasons For Changes In The CIO Charter
The focus of the CIO charter is increasingly changing – matching the new corporate charter for competitive repositioning. The prior focus was on the plumbing (infrastructure, ensuring applications are maintained and in compliance, etc.). Although those functions remain, the new charter focuses on building out and operating the new digital platforms and new digital operating models that are reshaping the competitive landscape.
The reason the CIO role is changing with the new corporate charter is that, in most organizations, the CIO is the only function that has these necessary capabilities for digital transformation:
- Breadth of vision that sees the entire organization and all its workings
- Depth of resources and ability to drive transformation projects and apply technology across silos, functions and divisions.
Digital transformation inevitably forces new operating models that have no respect for traditional organizations that are functional. Digital platforms and digital operating models collapse marketing and operations, for instance, spanning across these functions and groups to achieve a superb end-to-end for customer experience.
The new models force much tighter integration and often a realignment of organizations. The CIO organization and its breadth of vision and depth of resources to drive the transformation and support the new operating model that inevitably emerges from transformation.
How The CIO Role Must Change For The New Charter
Meeting the goals of the new charter for the CIO role will not come without CIOs changing their organizations and, in many cases, changing personally. To seizing the opportunities in the new charter, as well as shaping it, requires substantial change in (a) modernizing the IT, (b) the orientation and mind-set of the IT organization, and (c) changing the organizational structure.
To support digital transformation agendas, CIOs face a set of journeys in which they need to dramatically modernize their traditional functions. They first must think about their relationship with the business. To meet the needs of the business in a much more intimate, proactive, deeper way requires more investment and organizations with deeper industry domain knowledge and relationships. They need to move talent from remote centers back onshore to be close to the business so that they can better understand in a deeper way what the needs are and act on those quickly.
Second, the IT operating model needs to change from its historical structures so that it can deliver a seamless operating environment. The waterfall structures that still permeate IT need to change into a DevOps model with persistent teams that don’t change, teams that sit close to the business. IT also needs to accelerate the company’s journey to automation and cloud.
One thing companies quickly find about operating models is that they can’t get to a well-functioning DevOps team without migrating to a cloud-based infrastructure basis. And they can’t get to a cloud-based infrastructure basis without transforming their network and network operations model.
To meet the new charter, the CIO organization also needs to change in the following aspects:
- Change its mind-set
- Ensure deeper business knowledge
- Increase agility and speed
The modernizations I mentioned above then call into question the historical organizational structure of IT with functions such as network, infrastructure, security, apps development, apps maintenance, etc. In the new digital charter, these functions inevitably start to collapse into pods or functions aligned by business services.
As I’ve described above, substantial organizational technology and organizational change is required within the CIO’s organization to live up the new mandate. I can’t overemphasize the fact that the change is substantial nor overemphasize the need. In upcoming blog posts, I’ll further discuss the CIO’s role in reorienting the charter from plumbing to transformation and supporting the new digital operating models.
Source : https://www.forbes.com/sites/peterbendorsamuel/2019/01/30/how-the-cio-role-must-change-due-to-digital-transformation/#24f9952f68be
API Metrics and Status – A Regulatory Requirement or a Strategic Concern? – John Heaton-Armstrong
TL;DR – those discussing what should be appropriate regulatory benchmarks for API performance and availability under PSD2 are missing a strategic opportunity. Any bank that simply focusses on minimum, mandatory product will rule itself out of commercial agreements with those relying parties who have the wherewithal to consume commercial APIs at scale.
Introduction
As March approaches, those financial institutions in the UK and Ireland impacted by PSD2 are focussed on readiness for full implementation. The Open Banking Implementation Entity (OBIE) has been consulting on Operational Guidelineswhich give colour to the regulatory requirements found in the Directive and Regulatory Technical Standards which support it. The areas covered are not unique to the UK, and whilst they are part of an OBIE-specific attestation process, the guidelines could prove useful to any ASPSP impacted by PSD2.
Regulatory Requirements
The EBA at guidelines 2.2-4 are clear on the obligations for ASPSPs. These are supplemented by the RTS – ” [ASPSPs must] ensure that the dedicated interface offers at all times the same level of availability and performance, including support, as the interfaces made available to the payment service user for directly accessing its payment account online…” and “…define transparent key performance indicators and service level targets, at least as stringent as those set for the interface used by their payment service users both in terms of availability and of data provided in accordance with Article 36″ (RTS Arts. 32(1) and (2)).
This places the market in a quandary – it is extremely difficult to compare, even at a theoretical level, the performance of two interfaces where one (PSU) is designed for human interaction and the other (API) for machine. Some suggested during the EBA’s consultation period that a more appropriate comparison might be between the APIs which support the PSU interface and those delivered in response to PSD2. Those in the game of reverse engineering confirm that there is broad comparability between the functions these support – unfortunately this proved too much technical detail for the EBA.
To fill the gap, OB surveyed the developers, reviewed those existing APIs already delivered by financial institutions, and settled on an average of 99% availability (c.22hrs downtime per quarter) and 1000 m/s per 1MB of payload response time (this is a short summary and more detail can be read on the same). A quick review of the API Performance page OB publish will show that, with average availability of 96.34% across the brands in November, and only Bank of Scotland, Lloyds and the HSBC brands achieving >99% availability, there is a long way to go before this target is met, made no easier by a significant amount of change to platforms as their functional scope expands over the next 6-8 months. This will also been in the face of increasing demand volumes, as those organisations which currently rely on screen scraping for access to data begin to transfer their integrations onto APIs. In short, ASPSPs are facing a perfect storm to achieve these goals.
Knowledge and Reporting
At para 2.3.1 of their guidelines, the OBIE expands on the EBA’s reporting guidelines, and provides a useful template for this purpose, but this introduces a conundrum. All of the data published to date has been the banks reporting on themselves – i.e. the technical solutions to generate this data sit inside their domains, so quite apart from the obvious issue of self-reporting, there have already been clear instances where services haven’t been functioning correctly, and the bank in question simply hasn’t known this to be the case until so informed by a TPP. One of the larger banks in the UK recently misconfigured a load balancer to the effect that 50% of the traffic it received was misdirected and received no response, but without its knowledge. A clear case of downtime that almost certainly went unreported – if an API call goes unacknowledged in the woods, does anyone care?
Banks have a challenge, in that risk and compliance departments typically baulk at any services they own being placed in the cloud, or indeed anywhere outside their physical infrastructure. This is absolutely what is required for their support teams to have a true understanding of how their platforms are functioning, and to generate reliable data for their regulatory reporting requirements.
[During week commencing 21st Jan, the Market Data Initiative will announce a free/open service to solve some of these issues. This platform monitors the performance and availability of API platforms using donated consents, with the aim of establishing a clear, independent view of how the market is performing, without prejudicial comment or reference to benchmarks. Watch this space for more on that.]
Regulatory or strategic concern?
For any TPP seeking investment, where their business model necessitates consuming open APIs at scale, one of the key questions they’re likely to face is how reliable these services are, and what remedies are available in the event of non-performance. In the regulatory space, some of this information is available (see above) but is hardly transparent or independently produced, and even with those caveats does not currently make for happy reading. For remedy, TPPs are reliant on regulators and a quarterly reporting cycle for the discovery of issues. Even in the event that the FCA decided to take action, the most significant step they could take would be to instruct and ASPSP to implement a fall-back interface, and given that they would have a period of weeks to build this, it is likely that any relying party’s business would have suffered significant detriment before it could even start testing such a facility. The consequence of this framework is that, for the open APIs, performance, availability and the transparency of information will have to improve dramatically before any commercial services rely on them.
Source : https://www.linkedin.com/pulse/api-metrics-status-regulatory-requirement-strategic-john?trk=portfolio_article-card_title
7 Big Lessons We Learned on How to Sell a Patent – Sammy Abdullah
In 2017, we had a death in the portfolio. Once all the employees left, the only remaining assets were some patents, servers, domains, and a lot of code. Recently, we managed to learn how to sell a patent and code. Here is what we learned on how to sell a patent:
How to sell a patent in 7 steps
1. Set expectations when selling patents
The value of IP is a small fraction of what the company was once valued at; it’s maybe 1 to 5 cents on the dollar. Any acquirer of the IP is unlikely to do an all-cash deal, so don’t be surprised if the final consideration is a blend of cash, stock, royalty, earn out, or some other creative structure that reduces the acquirer’s upfront risk.
Selling a patent is going to take a year or more with legal taking 6 to 9 months alone (we recommend specialized counsel that has M&A experience and experience in bankruptcy/winding down entities).
It’s also going to take some cash along the way as you foot the bill for legal, preparing the code, and other unforeseen expenses that have to be paid well ahead of the close. With those expectations in mind, you need to seriously consider whether it is worth the work to sell the IP, what you will really recover, and what the probability of success really is.
2. Reach out to everyone
If you’ve decided it’s worth it to try and recover something for the IP, reach out to absolutely everyone you know. That includes old customers, prospects, former customers, anyone who has ever solicited you for acquisition, your cousin, your aunt, etc.
The point is don’t eliminate anyone as a potential acquirer as you don’t know what’s on someone’s product roadmap and be shameless about reaching out to your entire network. The acquirer of the IP in our dead company was a prospect who never actually became a customer. We also had interest from very random firms that weren’t remotely adjacent to our space.
3. You need the CTO
In order to transfer code to an acquirer, you’re going to need the CTO or whoever built a majority of the code to assist. No acquirer is going to take the code as-is unless you want them to massively discount the price to hedge their risk.
They’re going to want it cleaned up and packaged specifically to their needs. In our case, it took a founding developer 3 months of hard work to get the code packaged just right for our acquirer, and of course, we paid him handsomely for successful delivery.
4. You need great counsel
The code was once part of a company, and that company has liabilities, creditors, equity owners, former employees, and various other obligations. All of those parties are probably pretty upset with you that things didn’t work out. Before you embark on a path to sell the IP, consult with an attorney that can tell you who has a right to any proceeds collected, what the waterfall of recipients looks like, who can potentially block a deal, who you need to get approval from, whether patents are in good standing, etc.
You’ll need to pay the attorney up front for his work and as you progress through the deal, so it takes take money to make money from selling IP.
5. Utilize Github
Put the code on Github. Have potential acquirers sign a very tight and punitive NDA before allowing them to see the code. It also may be advisable to only give acquirers access to portions of the code. Github is the best $7 a month you’ll ever spend when it comes to selling IP.
6. Get all the assets
Make sure you have access to all the assets. This includes all code, training modules, patents, domains, actual servers and hardware, trademarks, logos, etc. An acquirer is going to want absolutely everything even if there are some things he can’t necessarily use.
7. Make sure the acquirer is fair
The acquirer has to be someone that is negotiating fairly and in good faith with you. We got very lucky that our acquirer had an upstanding and reputable CEO. If you don’t trust the acquirer or if they’re being shifty, move on. In our case, had the acquirer been a bad guy, there were many times when he could have screwed us such as changing the terms of the deal before the close, among other things.
Given the limited recourse you often have in situations like this, ‘bad boy’ acquirers do it all the time. We got lucky finding an acquirer who was honest, forthright and kept his word. You’ll need to do the same.
Takeaways on how to sell a patent
Selling patents is incredibly challenging. In our case the recovery was very small relative to capital invested, the process took nearly 1 year, and there were a lot of people involved to make it happen. We also spent about tens of thousands of dollars in legal fees, data scientist consulting, patent reinstatement and recovery, shipping of servers, etc.
A lot of that expenditure was done along the way so we had to put more money at risk for the possibility of maybe recovering cash in the sale of IP. Learning how to sell a patent wasn’t easy, but it got done. Hopefully, we never have to do it again and neither do you.
Source: https://about.crunchbase.com/blog/how-sell-patent/
Digital Transformation of Business and Society: Challenges and Opportunities by 2020 – Frank Diana
At a recent KPMG Robotic Innovations event, Futurist and friend Gerd Leonhard delivered a keynote titled “The Digital Transformation of Business and Society: Challenges and Opportunities by 2020”. I highly recommend viewing the Video of his presentation. As Gerd describes, he is a Futurist focused on foresight and observations — not predicting the future. We are at a point in history where every company needs a Gerd Leonhard. For many of the reasons presented in the video, future thinking is rapidly growing in importance. As Gerd so rightly points out, we are still vastly under-estimating the sheer velocity of change.
With regard to future thinking, Gerd used my future scenario slide to describe both the exponential and combinatorial nature of future scenarios — not only do we need to think exponentially, but we also need to think in a combinatorial manner. Gerd mentioned Tesla as a company that really knows how to do this.
He then described our current pivot point of exponential change: a point in history where humanity will change more in the next twenty years than in the previous 300. With that as a backdrop, he encouraged the audience to look five years into the future and spend 3 to 5% of their time focused on foresight. He quoted Peter Drucker (“In times of change the greatest danger is to act with yesterday’s logic”) and stated that leaders must shift from a focus on what is, to a focus on what could be. Gerd added that “wait and see” means “wait and die” (love that by the way). He urged leaders to focus on 2020 and build a plan to participate in that future, emphasizing the question is no longer what-if, but what-when. We are entering an era where the impossible is doable, and the headline for that era is: exponential, convergent, combinatorial, and inter-dependent — words that should be a key part of the leadership lexicon going forward. Here are some snapshots from his presentation:
- Because of exponential progression, it is difficult to imagine the world in 5 years, and although the industrial era was impactful, it will not compare to what lies ahead. The danger of vastly under-estimating the sheer velocity of change is real. For example, in just three months, the projection for the number of autonomous vehicles sold in 2035 went from 100 million to 1.5 billion
- Six years ago Gerd advised a German auto company about the driverless car and the implications of a sharing economy — and they laughed. Think of what’s happened in just six years — can’t imagine anyone is laughing now. He witnessed something similar as a veteran of the music business where he tried to guide the industry through digital disruption; an industry that shifted from selling $20 CDs to making a fraction of a penny per play. Gerd’s experience in the music business is a lesson we should learn from: you can’t stop people who see value from extracting that value. Protectionist behavior did not work, as the industry lost 71% of their revenue in 12 years. Streaming music will be huge, but the winners are not traditional players. The winners are Spotify, Apple, Facebook, Google, etc. This scenario likely plays out across every industry, as new businesses are emerging, but traditional companies are not running them. Gerd stressed that we can’t let this happen across these other industries
- Anything that can be automated will be automated: truck drivers and pilots go away, as robots don’t need unions. There is just too much to be gained not to automate. For example, 60% of the cost in the system could be eliminated by interconnecting logistics, possibly realized via a Logistics Internet as described by economist Jeremy Rifkin. But the drive towards automation will have unintended consequences and some science fiction scenarios could play out. Humanity and technology are indeed intertwining, but technology does not have ethics. A self-driving car would need ethics, as we make difficult decisions while driving all the time. How does a car decide to hit a frog versus swerving and hitting a mother and her child? Speaking of science fiction scenarios, Gerd predicts that when these things come together, humans and machines will have converged:
- Gerd has been using the term “Hellven” to represent the two paths technology can take. Is it 90% heaven and 10% hell (unintended consequences), or can this equation flip? He asks the question: Where are we trying to go with this? He used the real example of Drones used to benefit society (heaven), but people buying guns to shoot them down (hell). As we pursue exponential technologies, we must do it in a way that avoids negative consequences. Will we allow humanity to move down a path where by 2030, we will all be human-machine hybrids? Will hacking drive chaos, as hackers gain control of a vehicle? A recent Jeep recall of 1.4 million jeeps underscores the possibility. A world of super intelligence requires super humanity — technology does not have ethics, but society depends on it. Is this Ray Kurzweil vision what we want?
- Is society truly ready for human-machine hybrids, or even advancements like the driverless car that may be closer to realization? Gerd used a very effective Video to make the point
- Followers of my Blog know I’m a big believer in the coming shift to value ecosystems. Gerd described this as a move away from Egosystems, where large companies are running large things, to interdependent Ecosystems. I’ve talked about the blurring of industry boundaries and the movement towards ecosystems. We may ultimately move away from the industry construct and end up with a handful of ecosystems like: mobility, shelter, resources, wellness, growth, money, maker, and comfort
- Our kids will live to 90 or 100 as the default. We are gaining 8 hours of longevity per day — one third of a year per year. Genetic engineering is likely to eradicate disease, impacting longevity and global population. DNA editing is becoming a real possibility in the next 10 years, and at least 50 Silicon Valley companies are focused on ending aging and eliminating death. One such company is Human Longevity Inc., which was co-founded by Peter Diamandis of Singularity University. Gerd used a quote from Peter to help the audience understand the motivation: “Today there are six to seven trillion dollars a year spent on healthcare, half of which goes to people over the age of 65. In addition, people over the age of 65 hold something on the order of $60 trillion in wealth. And the question is what would people pay for an extra 10, 20, 30, 40 years of healthy life. It’s a huge opportunity”
- Gerd described the growing need to focus on the right side of our brain. He believes that algorithms can only go so far. Our right brain characteristics cannot be replicated by an algorithm, making a human-algorithm combination — or humarithm as Gerd calls it — a better path. The right brain characteristics that grow in importance and drive future hiring profiles are:
- Google is on the way to becoming the global operating system — an Artificial Intelligence enterprise. In the future, you won’t search, because as a digital assistant, Google will already know what you want. Gerd quotes Ray Kurzweil in saying that by 2027, the capacity of one computer will equal that of the human brain — at which point we shift from an artificial narrow intelligence, to an artificial general intelligence. In thinking about AI, Gerd flips the paradigm to IA or intelligent Assistant. For example, Schwab already has an intelligent portfolio. He indicated that every bank is investing in intelligent portfolios that deal with simple investments that robots can handle. This leads to a 50% replacement of financial advisors by robots and AI
- This intelligent assistant race has just begun, as Siri, Google Now, Facebook MoneyPenny, and Amazon Echo vie for intelligent assistant positioning. Intelligent assistants could eliminate the need for actual assistants in five years, and creep into countless scenarios over time. Police departments are already capable of determining who is likely to commit a crime in the next month, and there are examples of police taking preventative measures. Augmentation adds another dimension, as an officer wearing glasses can identify you upon seeing you and have your records displayed in front of them. There are over 100 companies focused on augmentation, and a number of intelligent assistant examples surrounding IBM Watson; the most discussed being the effectiveness of doctor assistance. An intelligent assistant is the likely first role in the autonomous vehicle transition, as cars step in to provide a number of valuable services without completely taking over. There are countless Examples emerging
- Gerd took two polls during his keynote. Here is the first: how do you feel about the rise of intelligent digital assistants? Answers 1 and 2 below received the lion share of the votes
- Collectively, automation, robotics, intelligent assistants, and artificial intelligence will reframe business, commerce, culture, and society. This is perhaps the key take away from a discussion like this. We are at an inflection point where reframing begins to drive real structural change. How many leaders are ready for true structural change?
- Gerd likes to refer to the 7-ations: Digitization, De-Materialization, Automation, Virtualization, Optimization, Augmentation, and Robotization. Consequences of the exponential and combinatorial growth of these seven include dependency, job displacement, and abundance. Whereas these seven are tools for dramatic cost reduction, they also lead to abundance. Examples are everywhere, from the 16 million songs available through Spotify, to the 3D printed cars that require only 50 parts. As supply exceeds demand in category after category, we reach abundance. As Gerd put it, in five years’ time, genome sequencing will be cheaper than flushing the toilet and abundant energy will be available by 2035 (2015 will be the first year that a major oil company will leave the oil business to enter the abundance of the renewable business). Other things to consider regarding abundance:
- Efficiency and business improvement is a path not a destination. Gerd estimates that total efficiency will be reached in 5 to 10 years, creating value through productivity gains along the way. However, after total efficiency is met, value comes from purpose. Purpose-driven companies have an aspirational purpose that aims to transform the planet; referred to as a massive transformative purpose in a recent book on exponential organizations. When you consider the value that the millennial generation places on purpose, it is clear that successful organizations must excel at both technology and humanity. If we allow technology to trump humanity, business would have no purpose
- In the first phase, the value lies in the automation itself (productivity, cost savings). In the second phase, the value lies in those things that cannot be automated. Anything that is human about your company cannot be automated: purpose, design, and brand become more powerful. Companies must invent new things that are only possible because of automation
- Technological unemployment is real this time — and exponential. Gerd talked to a recent study by the Economist that describes how robotics and artificial intelligence will increasingly be used in place of humans to perform repetitive tasks. On the other side of the spectrum is a demand for better customer service and greater skills in innovation driven by globalization and falling barriers to market entry. Therefore, creativity and social intelligence will become crucial differentiators for many businesses; jobs will increasingly demand skills in creative problem-solving and constructive interaction with others
- Gerd described a basic income guarantee that may be necessary if some of these unemployment scenarios play out. Something like this is already on the ballot in Switzerland, and it is not the first time this has been talked about:
- In the world of automation, experience becomes extremely valuable — and you can’t, nor should attempt to — automate experiences. We clearly see an intense focus on customer experience, and we had a great discussion on the topic on an August 26th Game Changers broadcast. Innovation is critical to both the service economy and experience economy. Gerd used a visual to describe the progression of economic value:
Source: B. Joseph Pine II and James Gilmore: The Experience Economy
- Gerd used a second poll to sense how people would feel about humans becoming artificially intelligent. Here again, the audience leaned towards the first two possible answers:
Gerd then summarized the session as follows:
The future is exponential, combinatorial, and interdependent: the sooner we can adjust our thinking (lateral) the better we will be at designing our future.
My take: Gerd hits on a key point. Leaders must think differently. There is very little in a leader’s collective experience that can guide them through the type of change ahead — it requires us all to think differently
When looking at AI, consider trying IA first (intelligent assistance / augmentation).
My take: These considerations allow us to create the future in a way that avoids unintended consequences. Technology as a supplement, not a replacement
Efficiency and cost reduction based on automation, AI/IA and Robotization are good stories but not the final destination: we need to go beyond the 7-ations and inevitable abundance to create new value that cannot be easily automated.
My take: Future thinking is critical for us to be effective here. We have to have a sense as to where all of this is heading, if we are to effectively create new sources of value
We won’t just need better algorithms — we also need stronger humarithms i.e. values, ethics, standards, principles and social contracts.
My take: Gerd is an evangelist for creating our future in a way that avoids hellish outcomes — and kudos to him for being that voice
“The best way to predict the future is to create it” (Alan Kay).
My Take: our context when we think about the future puts it years away, and that is just not the case anymore. What we think will take ten years is likely to happen in two. We can’t create the future if we don’t focus on it through an exponential lens
Source : https://medium.com/@frankdiana/digital-transformation-of-business-and-society-5d9286e39dbf
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