Harvey Nash's Tech Survey

Last night was the London Launch Event for the Harvey Nash Global Tech Survey Report - Race for Your Life.

The Report itself contains some obvious points, e.g. Younger Companies tend to be more innovative than established ones. However there were some surprising findings Construction and Engineering is the leading sector for innovation, with twice the preportion of respondents claiming their organisation is innovative than say Finance (which is investing heavily in FinTech). The FMCG  and Consumer led sector came bottom with less than 5% claiming any innovation.

Encouragingly enough the proportion of respondents who claimed that their organisation is innovative had also grown since the previous survey. Happily enough CTOs came out as more innovative than CIOs (which they should be, as its part of the job description), but CEOs also came a nose ahead of CIOs too.

As the survey is run by a recruitment specialist there is a focus on a number of recruitment centric issues. There are stong sentiments that Ageism dominates recruitment with adverse impact from your 40s onward. People still beleive that a human recruiter is far better than a machine at matching people with the right jobs. There is an increasing emphasis on completely refreshing skills every 5 years with many people investing personally in their skills.

In fact a lot of the panel discussion focussed on how organisations look at people, culture and mixed / diverse teams when building them. It seems that there is a frustration that older people cannot seem to get their CVs past recruitment consultants to the hiring manager. So what is the bottleneck there?

Close to 40% of people felt that automation would affect their jobs. Whilst this is quite high, considering that the last 30 years have been spent trying to automate IT people out of their jobs (without much success), it is probably quite necessary as there is a worldwide shortage of talent.

Two things struck me from the panel discussion however. One was positive, given that the panelists were from Tech start ups and Digital Model based companies; they all considered themselves to be the guardians of their business's appraoch to ethics. 

The negative was how much they failed to convey an understanding of innovation. They were seduced by the acquisition of technologies (by one means or another), but none of them mentioned how they empathised with customers to get at their real needs. There was no discussion of design thinking.

The other issue which came alongside this was how all of them were only just getting to grips with the idea of designing and operating to avoid technical debt. Previously, they had all been in too much of a hurry to just deliver something.

So in terms of how mature is the average operator in the new Digital As Usual (DAU) world. It's looking like 5 out of 10 to me.

The Productivity Problem and Machine Learning

One of the things that few mainstream politicians will admit to is the fact that Economic Policies which promote Productivity, lead to short to Medium Term Unemployment. Likewise the converse is true. If a government promotes policeies for High Employment, they tend to undermine Productivity.

Longer term, productivity has benefits all of its own. Long term productivity growth leads to more investment and hence higher employment. Along with this comes better quality jobs demanding higher skills and hence wage growth.

North America has long enjoyed high growth, largely due to the abundance of land and resources and a relative low density in population, leading to skills shortages and therefore the need for higher productivity (gained from investment in automation technologies). This puts Britain's recent economic performance in perspective. The UK economy largely weathered the most recent economic downturn well. Though one of the consequences was large scale imigration and a drop off in productivity growth.

This means that British Industry needs to invest in significant increases in productivity, if it wishes to maintain its long term competitive position. Also, it poses challenges as Britain has shifted to a services dominated economy, as it is often difficult to achieve high productivity within service industries and traditional approaches such as work flow (or Business Process Management) and rules engines tend to be limited in applicability and affordability. Typical problems are activities which deal with subjective judgements involved in tasks such as categorisation or recognition where people are able to deal with inconsistencies and sometimes incompleteness of data. These steps are usually not value adding in themselves, but important to being able to carry out subsequent value adding tasks.

A simple example would be in pest control. when on a job, the pest controller may find a cockroach during an inspection which indicates a probable infestation problem. Different strains of cockroach however need to be treated with different chemicals to eradicate them. Often samples need to be sent to a lab to be examined and identified, so that the operative can then return and take appropriate action. This adds time, delay and effort to the process with impact on costs and productivity. It also may impact the customer, especially if his or her business is in catering or another business which may have to close down until the infestation is cleared up. Use of picture recognition technology, based on training a machine learning system and providing field access via, say, a mobile app would enable a much quicker and cheaper response. As on the spot diagnosis could take place, leading to instantaneous treatment. The avoidance of going away to come back again, takes a couple of steps out of the process.

Other examples occur in the legal profession, where initial analysis of case files may help decide whether a case is worth pursuing based on existence or not of a number of attributes which relate to previous experience and case law. This allows lawyers and clients to focus on valuable activity rather than value destroying cases.

So, it is strange to see that some politicians want to tax such applications as people, in order to protect jobs. As inevitably this will erode productivity growth and damage long term employment opportunities. Are they trying to keep everyone poor?

Digital Portfolios

Soon, almost all enterprises will be digital. The smart, quick running start-ups of today will start to feel the pains of maturity as they expand the range of activities that they are involved in and the markets in which they operate. The old world survivors which have adapted will also feel the pain as their IT or should we now say Digital Estates become increasingly complex.

As this happens, many of them will start to appreciate the need for Portfolio Management of their Digital Assets. The constant churn of Digital as Usual (DAU) means that almost everything will be obsolete or approaching obsolescence and business requirements will keep changing. Enterprises will need to continuously assess their portfolio and prioritise improvements, changes and rationalisation, as well as the response to threats and changing legislation as governments react to Digital Disruption in a number of ways.

Anyone responsible for providing Digital Services to their enterprise needs to be able to deal with this and the complexity which lies underneath, so that they can spend wisely and assign resources for the most optimum effect. To do this requires a high degree of collaboration with other business functions to ensure that a balanced and appropriate approach is taken. This is where Digital Asset Portfolio Management (DAPM) comes in.

At its very simplest, DAPM is about Business Quality, Technical Quality and Affordability. These 3 things need to be monitored and continuously managed through the layers of a Digital Product. The key layers being Customer & Business Environment, End-to-End Product Process, Applications, Data, Infrastructure (cloud, virtual &/or physical).

Changes in Customer expectations, business trends, legislation etc. can impact the overall Digital Product's relevance, market fit and legality. This is a major aspect of business quality and will imply the need for change to End-to-End Product Processes. Although Product Processes may also be impacted by other issues such as changes in volume, ability to deal with increasing product complexity, scarcity of resources or competition (in performance terms) with other products in the market place (i.e. the bench mark suddenly shifts and your process has been left behind). Likewise, applications may fail to keep pace with changing needs. Data may become corrupted or inadequate due to poor information management or a bad fit between the data and the real needs of the business. Infrastructure gradually becomes obsolete, difficult to support or integrate, and weaknesses in security become apparent.

All this gets even more complicated if mergers happen and applications become duplicated, or technical strategy changes introduce new technical platforms into the enterprise.

One of the key things that DAPM has to do, is identify all the major components required to deliver a digital product (including containers and serverless functions) and keep track of their condition and costs. This allows the calculation of unit costs to support a product transaction and enables investments to be assessed in terms of not just impact on quality and effect, but also the on cost of supporting a product.

A mature digital organisation needs to build DAPM into its budgeting and planning activities, and use this to inform its technical strategy. Alternatively, businesses with a huge legacy problem who want to transition to digital, may need to use DAPM to identify and prioritise which applications need to be retired, replaced or upgraded to enable their move.

However you look at it DAPM is an essential digital practice.

Where Next for Wearables

I recently found this article https://www.wareable.com/wareable50/best-wearable-tech-2017 on wearable technology trends, which is worth a read.

The thing I really liked was the Thynk Relax device, which basically uses electrical neck stimulation to help you relax and improve sleep. It's a bit pricey but slots alongside Dreem's headset as something which is really focused on individual well-being and in the the nature of Zeitgheist addresses one of the major issues of the age, Stress.

However overall this article gives a snapshot of where investment is going. Out of 50 (or so items mentioned) Mainstream trends are:

• Watches and Wriststraps account for 14 of the main items, all with slightly different slants.
• Smart Clothing and shoes get 7 mentions.
• VR, AR and Mixed Reality get 6 with evolved approaches to smart glasses and weareable cameras counting for another 4.
• Hearables and earbuds count for another 3 with more mentions of possibilities as well.
• Home automation platforms and static digital assistants (which are not currently weareable, but this is an obvious evolutionary path)  garner 6 mentions.

Looking across the products, one gets a sense of evolution and convergence. Some things are being simplified to address user centric design concerns (make things simple). Single use items such as payment rings probably will not survive long as products in their own rights. Products are starting to address response to human emotions, e.g. straps which detect them and home management systems which adjust the home environment to fit your mood and music/media based output to clothing. There is also a slight shift away from just sensing to doing things to you as well.

The overall wearable eco system is evolving to sense everything to do with the wearer and his or her environment, to provide him or her with information input (visual, audio, heating and cooling of clothing, and bodily stimulation), to screen out unwanted stuff, e.g. background noise, as well as issue commands to your car, devices in a smart house etc. and to provide AI based advice and updates of information from the internet.

The foundations are really being laid to get rid of the smart phone, home computer and pad, and replace them with smart clothing, jewelry and even smart temporary tattoos. Interestingly as this wave hits, Google and Apple appear to be trying to keep up, but with slightly underwelming products, and Microsoft is barely visible in the race. It's time to try and work out who will be the next consumer and design driven giant in the tech field.

The Perils of Bad AI

Everyone by now will have read that they are about to be replaced by robots and AI bots at work. Many people have also heard how employment agencies and some large firms use AI based software to screen applications and most who do complain about it.

So, recently, I tried an experiment with CV parsing software. I used a "top 10" CV parser and took some copies of a friend's CV which had been tweeked to apply for slightly different roles and submitted it to the free demonstration site.

Within hours I had received back the analysis of the 3 different CVs. I almost fell off my chair in astonishment of the analysis produced. In all cases, it cited the wrong position as his most recent one. It ignored half of his work experience, reducing over 20 years experience to just over 10. It got his level of seniority wrong and in one case it totally missed what was his major skill. In fact it bore such little relationship to what the CVs said that it could be said to be "made up" or "fabricated". It certainly was not accurate and was misleading.

I then decided to change the presentation of the information slightly in the CV. I moved his most recent role to the second page and where he listed earlier previous experience, I changed the orger in which role, organisation and date was presented. The content itself remained the same. Guess what? his most recent role was identified as an even earlier one. But it now identified the missing 10 years or so of experience. It still however did not correct the level of seniority that it assigned.

The thing which strikes me is that the agencies are using the software to deal with a problem of volume. Each advert typically attracts 300 to 1,000 applications. But they are not advising people how to structure their applications so that the software reads the CVs (or resumes) accurately. 

In my opinion, any agency or recruiter using this type of software is not going to pick the right candidates and is opening itself to breaches of data protection legislation (at least in europe) as use of any incorrect, out of date or deficient data which causes loss, harm or embarrassment is a criminal offence. Arguably, failing to shortlist someone because you rely on erroneous information would be in that category.

This shows how fragile and potentially dangerous some of the existing AI and machine learning applications are. They are powerful when properly trained and tested, but treating them as a facile magic bullet which will automate all interpretative assessment out of processes is dangerous.

The Way of DAU - The New Digital Philosophy

For those of you who have come to accept that Digital has become the new normal, it it is not surprising to know that there is a new acronym DAU or Digital as Usual. This replaces the old one BAU or Business as Usual.

There is even a philosophy known as The Way of DAU (pronounced Dow). This is built around 10 guiding principles which encapsulate current best practice in the Digital world.

For those getting started, the principles are useful for driving adoption and practice of Digital. They are:

1.       Understand the Market;

2.       Identify what Changes Rewrite the Rules;

3.    Select High Priority Opportunities;

4.       Build Product Focused Culture and Teams ;

5.       Walk in your Customers’ Shoes;

6.       Embrace Opex;

7.       Go Lean;

8.       Cherish Information;

9.       Nurture Partnerships;

                    10.     Harness Fear of Obsolescence.

Although there is an assumption of a continuous iterative loop to be followed when applying them.

That's all for the weekend.

Is Your Enterprise Digital Ready? - Summer Time Reading Recommendations

Sometimes it is better to make sure that other people think that they had the idea first. As Information Professionals are not always believed when they try to persuade their business colleagues that they need to change their ways, if they are going to get the best out of their Digital Strategies and Investments.

The truth is that there are some fundamental issues to address which separate Good or Average performing companies from Excellent ones when it comes to exploiting IT or Digital investments and transformations. Proponents of Digital Strategy, Agile and DevOps often raise them, but due to the fact that these issues are being raised in a technological context, non IT colleagues tend to either listen and not hear or just dismiss them as the mad ravings of techno boffins.

Key among these are:

1. Having a "Real Business Strategy" based on deep market insight and how to disrupt or exploit it in your favour;
2. Working as a Team within a healthy Business Culture;
3. Adopting Design Thinking to help empathise with customer needs, really understand what you are trying to address and then to creatively address options and iterate design to create elegant and well targetted solutions rapidly, whilst embracing leraning from failure as a critical part of the approach;
4. Systems Thinking to understand the end-to-end process, identify and manage critical business bottlenecks and organise around product or work delivery, instead of hierarchical functional silos.

A large part of this is really concerned with taking an ego-less multi-functional team approach to addressing what is really needed and then pursuing continuous delivery, automation and improvement in small steps. 

Fortunatley there are some great business books on some of these subjects which evryone should be encouraged to read as they address the issues from a more general business perspective and introduce the key concepts that all the Digital Geeks are so keen on.

My recommendations are:

Good Strategy Bad Strategy is a great expose on how to do Strategy properly. Most readers will recognise many of the bad examples which are lacerated by Richard Rumelt (one of the leading fathers of Business Strategy) in what is a fairly easy and entertaining read.

Winning Teams Winning Cultures  - addresses a lot of the key issues in building a positive enterprise culture. This comes from Larry Senn (of Senn Delaney a culutural change consultancy) and Jim Hart who are long time practitioners in the field of cultural change. It's an interesting book, because just like democracy it is difficult to bomb culutural change from 40,000 feet into an organisation. It requires authenticity, long term commitment and sytematic sweating by the management team to achieve.

The Human Constraint - the author (Angella Montgomerry) takes the principles advocated by Demming and Goldratt and updates them to apply to all businesses (not just manufacturing) in the practical adoption of system thinking and the Theory of Constraints to business in general.

Finally there are plenty of sources on Design Thinking available on the internet. The UK Design Council publishes the Double Diamon model which provides a simple model for explaining the process. I recently saw a great webcast by Ileana Stigliani, fom Imperial College Business School, on the subject Unleash Innovation Through Design Thinking

(see: https://www.ivyexec.com/professionals/classes/details/unleash-innovation-through-design-thinking ).