Does Your Business Need That Tempting Technology?
Unless it proves useful to your business, it was a distraction.
Recent posts have focussed on advice when using Data Science or Data Visualisation. Now it’s time we returned to focussing on commercial realities. One lesson, I learned as a senior customer insight leader, was not to get distracted by what one CEO called “hobbies”.
By that, he meant ideas, passions or technical innovations that, whilst interesting, are not relevant to what the business needs now.
In this post, I’ll share a fascinating review of how AI is being used in today’s businesses. Plus, a summary of how insurers are using wider data sets in their digital transformation. Switching sectors, we’ll see how industrial companies are benefitting from IoT. Finally, as a salutary warning, I’ve included a damning critique. It’s a critique of IBM overhyping Watson (risking both their brand and wider perception of AI).
Is AI proving useful to your business?
As promised, let’s start with the topic of Artificial Intelligence (AI). The Harvard Business Review (HBR) recently published an excellent article. It summarises the findings of their survey. Asking 3,073 senior executives about the reality of how they were using AI.
The findings are a useful counter to over-hyped media coverage. Whilst also being an encouragement that real progress is being made. HBR found that 41% of businesses were still at the pilot stage. So, there’s still time to catch-up if you haven’t started.
A third of early adopters surveyed are able to cite revenue increases as a result, so this matters. HBR include some helpful recommendations for how to progress. I particularly liked the portfolio approach that they advocate. When advancing use of insight in businesses, I’ve also found it helpful to diversify. By that, I mean a mix of:
(a) short-term profitable incremental improvements;
(b) longer-term riskier innovations.
HBR recommend another regular piece of advice from this blog. Don’t allow IT or Digital to lead your AI implementations in isolation. Business-led collaborations are a much surer path to achieving embedding & sustainable change.
Is Big Data useful to your business?
Next, let’s risk moving on to the world of Insurance. As this next post acknoledges, its a sector that can be boring, especially in the minds of consumers. Raconteur Magazine published this piece. It summarises how insurers are throwing off their musty image. By embracing the need for digital transformation they are also using wider data.
Examples include advice on your driving behaviour from telematics. Plus, automatic calling of emergency services if you have a crash. More well known will be use of health trackers by Vitality to offer rewards & change behaviour.
A less well known example may be the emergence of Brolly as a digital version of an intelligent broker. Capturing more data & using machine learning, it has considerable promise.
Another reminder that progress is not advanced as vendors suggest, but still positive. The potential for insurance sector is huge. But, digital transformation projects need to consider data & insight aspects.
Is the Internet of Things (IoT) useful to your business?
But use of IoT is not limited to consumer facing businesses. Devices from smart watches to smart homes may get more press coverage, but don’t ignore manufacturing.
In another good read from Raconteur, they share how IoT is impacting product production. It may surprise you that the top 3 industries for IoT investment are manufacturing, utilities & transport. But, there are good reasons why.
From predictive maintenance, to intelligent inventory management there are many benefits. Industrial giants like GE have already demonstrated the potential of industry platforms. Now, IoT enablers manufacturers to learn more about the real use of their products.
Consumers benefit through faster fixes. Product designers can get some of the benefits of ethnographic research. Data flowing from consumers all the way back to the factories that made the device. Machine learning enabling more intelligent design refinement.
It may well be that the industrial value chain proves full value of IoT long before fancy new gadgets in the shops. Several of the points made in this article also read across sectors. So, worth reading for product innovators everywhere.
Is IBM Watson useful to your business?
Now, I need to be careful here. I have no direct experience of using IBM’s flagship product. So, this is not a personal review.
But, I want to include this biting critique, because it speaks to a wider malaise. On Gizmodo blog, Jennings Brown lays into the over-hyping of Watson by IBM. In my experience many technology vendors make the same mistake all the time. Whether it’s Big Data solutions, Data Science toolkits or IoT platforms.
So, in a month when we will focus on business applications, take note. If it sounds too good to be true, it (almost certainly) is. The comparison to President Trump is biting, but a great soundbite.
What is clear is that IBM needs to realise the value of transparency. I am old enough to have worked on Expert Systems and Neural Networks in the 1990s. One of the reasons that AI revolution died out was over-hype and black boxes.
Businesses need pragmatism and honesty from their suppliers. I hope the progress being made by Machine Learning libraries for R & Python help open it up. Greater understanding of techniques being used and limits of those methods would help.
Perhaps it takes such public shaming to encourage vendors like IBM to change. Stop promising to change the world, start by changing how you work with businesses.
Is your use of technology useful to your business?
This post opens our monthly theme focussed on business applications. I hope it has given you pause for thought.
I’ll share more in coming weeks, about how your role needs to balance both commercial & customer benefits. How you use technology is a key part of that judgement.
An Emerging Theme In Thematic Investing
Exchange traded funds (ETFs) are popular vehicles for market participants looking to engage in thematic investing. Thematic investing looks to take advantage of future growth trends, including disruptive technologies. Given that forward-looking approach, stock-picking in the thematic universe is equally as hard, if not harder, than in traditional market segments.
Go back to the late 1990s, before the bursting of the Internet/technology bubble. Back then, investors stood an equal chance of selecting E-Toys over Amazon or some no longer in existence networking equipment maker over Cisco.
“History is littered with examples of prospering industries with no indication of which company will come to dominate the industry,” according to Nasdaq. “This suggests that successful thematic investing is more about selecting baskets of investments rather than single securities.”1
The ALPS Disruptive Technologies ETF (DTEC) provides basket exposure to a broad swath of thematic investments. DTEC features exposure to not just one or two emerging technologies, but 10 such themes on an equal-weight basis.
The 10 themes represented in DTEC are as follows: 3D printing, clean energy, cloud computing, cybersecurity, data and analytics, fintech, healthcare innovation, Internet of Things (IoT), mobile payments and robotics and artificial intelligence (AI).
Generally speaking, fund issuers have been quick to respond to disruptive and transformative technologies, bringing products to market to tap these themes. Prior to DTEC coming to market late last year, there were ETFs devoted exclusively to cloud computing, cybersecurity, robotics and other themes featured in DTEC. However, few use the basket approach to themes employed by DTEC.
February, a rough month for U.S. stocks, highlighted the advantages of DTEC's multi-theme methodology. Seven of the 10 themes found in the fund finished the month lower, but DTEC was able to outperform the S&P 500 on a monthly basis.
Focusing on individual themes can be rewarding over the long-term, but not all investors have the risk tolerance for such a strategy. Consider this: the Indxx Global Robotics & Artificial Intelligence Thematic Index jumped more than 48% in 2017. That type of performance is enough to seduce many investors, but that same benchmark slipped 7.60% in February, generating monthly volatility of 34.10%.2 Said another way, that robotics and AI index's February slide was more than triple the loss experienced by DTEC during the month.
While it probably is not accurate to call the indexes devoted to individual disruptive themes “old,” many use old school weighting methodologies. For example, the two largest components in the ISE Cloud Computing Index are Netflix, Inc. (NFLX) and Amazon.com Inc. (AMZN). Only two members of the S&P 500 have larger market values than Amazon while Netflix currently has a larger market cap than Wal-Mart (WMT) and McDonald's (MCD).
Holdings subject ot change as of 12/31/17
For its part, DTEC not only equally weights its 10 disruptive themes, but its 100 components as well, potentially reducing single stock risk in the process. As the chart below confirms, equally weighting stocks is rewarding across sectors and market capitalization segments.
Past performance does not guarantee future results
Annualized returns for the past 10 years show seven of the 11 S&P 500 sectors, when equally weighted, outperform cap-weighted equivalents, according to S&P. Three of those seven sectors – financial services, healthcare and technology – are prominent parts of DTEC's roster.
1 Source: Nasdaq Dec. 28, 2015 https://www.nasdaq.com/article/what-thematic-investing-is-and-its-strengths-and-risks-cm559209
2 Source: ETF Replay data
An investor should consider the investment objectives, risks, charges and expenses carefully before investing. To obtain a prospectus which contain this and other information call 866.675.2639 or visit www.alpsfunds.com. Read the prospectus carefully before investing.
An investment in the ALPS Disruptive Technologies ETF (DTEC) may be subject to substantially greater risk and volatility than investments in larger and more mature technology companies.
There is no assurance that the market developments and sector growth based upon the themes discussed in the article will come to pass.
ALPS Disruptive Technologies ETF shares are not individually redeemable. Investors buy and sell shares of the ALPS Disruptive Technologies ETF on a secondary market. Only market makers or “authorized participants” may trade directly with the Fund, typically in blocks of 50,000 shares.
ALPS Advisors, Inc. (AAI) has engaged IRIS Werks, LLC (IRIS) to produce analysis and commentary on ALPS-advised ETFs. IRIS currently has a compensated business relationship with AAI. AAI is not affiliated with IRIS.
The content and opinions expressed in this article are that of the author and not the views and opinions of AAI. In addition, AAI assumes no responsibility to ensure the accuracy of the content written by the author.
There are risks involved with investing in ETFs including the loss of money. Additional information regarding the risks of this investment is available in the prospectus. Past Performance is not indicative of future results.
The fund is new and has limited operating history.
ALPS Portfolio Solutions Distributor, Inc. is the distributor for the ALPS Disruptive Technologies ETF. AAI is affiliated with ALPS Portfolio Solutions Distributor, Inc.
The author is not an investment professional and this article should not be considered investment advice. While the information and statistical data contained herein are based on sources believed to be reliable, the author takes no responsibility to ensure the accuracy of the content. Additionally, this article should not be relied on or be the basis for an investment decision. Information that is historical is not indicative of future results, and subject to change.
S&P 500®: A capitalization-weighted index of 500 stocks designed to measure performance of the broad domestic economy through changes in the aggregate market value of 500 stocks representing all major industries.
S&P SmallCap 600®: A capitalization-weighted index that measures the small-cap segment of the U.S. equity market.
S&P MidCap 400®: A capitalization-weighted index that measures the mid-cap segment of the U.S. equity market.
Indxx Global Robotics & Artifical Intelligence Thematic Index: The Indxx Global Robotics & Artificial Intelligence Thematic Index is designed to track the performance of companies listed in developed markets that are expected to benefit from the increased adoption and utilization of robotics and Artificial Intelligence ("AI"), including companies involved in Industrial Robotics and Automation, Non-Industrial Robots, Artificial Intelligence and Unmanned Vehicles.
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