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HOW TO KEEP DIGITAL TRANSFORMATION ON TRACK AFTER THE PANDEMIC

DIGITAL TRANSFORMATION

Ashley Coker, CEO and founder, Slate

 

Introduction

The global coronavirus health emergency has made it abundantly clear how dependent we are on digital services for business continuity and social cohesion. When physical contact must be minimised, digital businesses are in a better position to rapidly adapt and continue their services and respond to customers’ needs.

This is perhaps why Chancellor, Rishi Sunak, was prompted to delay the introduction of IR35 Off-Payroll working rules to the UK private sector until April 2021, as part of his package of measures to support British businesses through the COVID-19 crisis.

While some businesses expressed relief at the delayed introduction of IR35 rules in the private sector, many financial enterprises had already terminated contracts with IT contractors in preparation for the original deadline, with the risk of digital transformation programmes stalling.

 

What is IR35?

Inland Revenue legislation 35 (IR35) is a tax law designed to prevent individuals from using intermediaries, such as their own limited company, in order to avoid paying their fair share of tax and national insurance contributions (NICs). By setting up a limited company, some people were able to leave their employment in a bank on a Friday and return to the same job on a Monday as an IT contractor, with no change in their role, duties, or place of employment. HMRC wants to put a stop to this.

However, with an estimated 170,000 contractors working through their own personal service companies, HMRC has not had the resource to address cases individually and decided to put the onus on the organisations that hire contractors.

From April 2021, the responsibility for assessing whether a contractor is genuinely self-employed (outside of IR35) will fall on every medium and large private sector organisation with a turnover of over £10.2 million, a balance sheet of £5.1 million, and more than 50 employees. This means that every contract will have to be reassessed to decide whether an individual’s work falls inside or outside IR35. Contractors must be provided with a Status Determination Statement (SDS) for each contract that they undertake, confirming the organisation’s assessment of their status for IR35 purposes.”

 

How has the financial sector prepared for IR35?

To avoid the time and resource required to scrutinise thousands of contractor contracts, many financial services organisations took a blanket decision which deems that all contractors are working inside IR35. Several prominent organisations have taken this route and terminated all contracts with contractors who bill for their services via limited companies.

Being deemed to be working inside IR35 has the effect of making hiring organisations liable for paying contractors’ income tax and National Insurance contributions at source, as though they were employees, without contractors benefiting from the sick pay and holiday pay benefits of the organisations’ employees. Tax experts have calculated that working inside IR35 will reduce contractors’ incomes by approximately 25 per cent. This makes projects less attractive to IT contractors who might be working on delivering digital change.

 

How does IR35 affect Digital Transformation?

Prior to the IR35 deadline extension, HSBC, Lloyds bank and Barclays bank were reported to have taken a uniform decision to classify all contractors as working within IR35. It was also reported that Deutsche Bank risked losing 50 out of 53 contractors working in its London-based change management team after taking the decision to cease working with contractors via personal service companies and asking them to join the payroll of a recruitment outsourcing agency used by the bank.

If IT contractors stop working with their financial service industry clients, to avoid falling foul of IR35 after April 2021, this could have a devastating impact on digital transformation projects that depend on the specialist skills of external contractors.

A number of contractors have reported that they plan to seek employment overseas after IR35 comes into force in the private sector, so that they can carry on enjoying the flexibility, job satisfaction and remuneration of working off-payroll. This could result in a brain drain for many sectors, such as banking, which relies heavily on the skills of external IT contractors to deliver digital transformation.

 

Fast track to digital delivery:

While IR35 could pose serious challenges for digital change programmes in the UK financial services sector after April 2021, some CIOs we have spoken to see the contract renewal phase as an opportunity to clear the decks, refocus and keep their best people on the pitch.

Our experience of providing corporates with highly-skilled software engineers who are born problem-solvers, who work in small, capped teams on a 5 in 50 model, has shown that they are often fundamental to getting stalled digital change programmes back on track. These developers work alongside enterprise IT teams, on a Seed, Scale, Succeed process, bringing fresh coding skills and transforming project thinking into product thinking, with continuous delivery of digital service iterations. They are technology specialists who relish the challenge of working on high profile digital journeys, but who do not wish to work as corporate employees and are therefore hard for financial services organisations to hire.

We now have another twelve months to prepare for IR35. In the meantime, as financial services organisations adapt to the demands of the pandemic, this is the time for small, agile teams of problem-solvers to shine.

Technology

HOW TO ACHIEVE THE BEST POSSIBLE CUSTOMER EXPERIENCE THROUGH ARTIFICIAL INTELLIGENCE

By Craig Charlton, CEO of SugarCRM

 

Before high definition televisions were introduced, home entertainment was limited to a grainy picture on a small CRT box in the corner of your living room. It could in no way compete with the picture quality seen in cinemas, for instance, with details hard to pick out. The difference was like chalk and cheese. In the early two thousands this all changed with the introduction of high definition LCD tv’s, which took home entertainment to a new level and made it feel like a truly immersive experience. More recently we’ve seen the introduction of 4K and even 8K devices, which have taken the experience even further.

In the world of CRM and CX, we’re now at a similar watershed moment. Currently, most businesses have a fragmented, dated and distorted picture of their customers, which is affecting the level of service that they can achieve and their ability to grow. Poor data quality is hitting organizations where it hurts, costing them time and money. It’s important that organisations act now to replace their current hazy view of their customer, with a sharply focused picture that’s rich in breadth and depth.

We call this a high definition customer experience, or ‘HD-CX’, and by delivering on it, businesses can reach new levels of performance and predictability, and increase customer lifetime value. There’s a long way to go however, as research indicates that 91% of data in CRM systems is incomplete, and 70% of CRM system data goes bad each year[2].

 

Craig Charlton

 Where can CX take us?

Forrester states that over the next 5-10 years CX will become “crucial for brands to survive, for them to avoid disintermediation, irrelevancy, blandness, and/or cluelessness about customer sentiment.”[3] Those brands that choose to wait 5-10 years before delivering a HD-CX experience however, will have found themselves disrupted and behind the curve.

To leapfrog competitors and fuel growth, companies need to  obtain a high definition view of their market, business and customers as soon as possible. Right the way from formulating ideal customer profiles (ICP) and identifying sectors with a propensity or intent to purchase, through to customer lifetime loyalty. HD-CX is all about drawing on accurate, up-to-date information from multiple sources and from across the organisation to reach new levels of business performance and predictability. The value of performance and predictability applies to businesses of all sizes and in all industries.

 

Why is being ‘time aware’ so crucial?

It’s about time we redefined the 360-degree customer concept and added the key missing component: Time. It was Benjamin Franklin that said, “Lost time is never found again.” Although nobody can stop the flow of time, what we can do is ensure a complete historical record of every change event in the customer journey, and augment this information via a rich repository of relevant information to ensure full situational and directional awareness of a customer.

It’s no good just having a 360-degree view of one moment in time—right now. Recording every change event in the customer journey is essential for predicting future outcomes. Accurate predictions enable companies to make better business decisions, manage risk, respond to problems and take advantage of opportunities. Organisations need to gain insight into the past, present, and future of their customer-facing business processes.

 

Stay ahead of your competitors with artificial intelligence

Making sense of all this data can be a perennial issue for companies, with the average company holding on average 162.9TB of data[4]. To make sense of this data, create a competitive advantage and deliver an unparalleled level of predictability across a whole array of different business use cases, Artificial Intelligence is the key.

Understanding your current state and how you got there is essential, but what if you had the ability to look into the future toward what your business could be? I’ve already stressed the importance of having a complete historical record of every change event in the customer journey to ensure full situational and directional awareness of your customers and your business, but AI considers the other direction of time: the future.

AI has the ability to deliver exceptional predictions, even with limited or incomplete CRM data by leveraging vast external data to consider factors your data doesn’t cover and surface insights that you may not have known existed. These unparalleled predictions allow businesses to make confident decisions and focus on the highest priority activities across marketing, sales, customer service, and more. However, not all AI-powered prediction is created equal and predication accuracy is essential for success. A proven platform with deep learning models combined with both the best quality external data and CRM data, is a combination that most companies can’t provide their customers.

If companies successfully create a time-aware and high-definition picture of their customers, they will benefit from greater customer relationships and unparalleled oversight of their businesses. However, they must utilise AI to provide exceptional customer experiences and business predictions. If businesses don’t adapt to change and instead continue to operate with an old, outdated, standard-definition view of their customers, they will lose out to competitors as they won’t be able to deliver an experience that their customers expect.

 

[2] https://www.dnb.co.uk/content/dam/english/business-trends/b2bm-db-improve-the-quality-of-your-marketing-now-1-0.pdf

[3] https://go.forrester.com/future-of-cx/#:~:text=The%20wheel%20of%20change%20is,relationships%20stable%20amid%20unprecedented%20upheaval.

[4] https://cdn2.hubspot.net/hubfs/1624046/IDGE_Data_Analysis_2016_final.pdf?t=1496694598964

 

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Technology

USING ARTIFICIAL INTELLIGENCE TO ACHIEVE CIRCULAR ECONOMY

By Professor Terence Tse, ESCP Business School

 

It is really only a matter of time before the two main trends, artificial intelligence (AI) and circular economy, would come together. A milestone of this convergence was the white paper “Artificial intelligence and the circular economy”: AI as a tool to accelerate the transition, jointly published by The Ellen MacArthur Foundation and Google earlier this year. It has kick-started the discussion on how AI can be used as a tool to help accelerate and scale our transition to a circular economy. This can be achieved by unlocking new opportunities through improving product and material design, enhancing circularity-based business models, and optimising circular infrastructure. The paper draws on the food and consumer electronics industries to illustrate the circular benefits driven by AI. The forecasted value that can emerge from these is encouraging: up to $127 billion and $90 billion a year in 2030, respectively.

 

The pace will be slow

No doubt these are very good news. It also shows how innovative technologies can take circular economy to the next level. Yet, I believe the path leading there will be full of challenges, not least because, contrary to what general media would like to get us to believe, the development of AI is, in reality, really slow.

 

There are several reasons attributable to this sluggish pace

First, there is a general shortage of AI-proficient graduates. Training up AI researchers takes time. Universities are not churning out data scientists fast enough to meet the job market demand. For those who are graduating, they will most likely be snapped up by the technology giants. Indeed, it has been estimated that some 60% of AI talent are in the employment of technology and financial services companies, leading to a ‘brain drain’ in academia, which in turn, slows down the production of qualified graduates. Small circular economy-based companies (as well as AI start-ups) will struggle to have the same hiring power, as they often lack the ability to match the levels of salaries and prestige offered by large organisations.

Another reason why circular economy-aimed companies, large or small, will struggle to deploy AI is that the technology remains a very expensive investment. AI is, at the moment, far from a plug-and-play technology. Arguably, there are off-the-shelf AI applications available in the market. But what this one size fits-all technology solutions can really do is often very limited and their effectiveness low. Inevitably, for AI to work at an acceptable, value-creating level, it is necessary to integrate it into the existing wider IT system. Customising AI applications to be embedded in the system architecture is very complex and hence very costly.

To make matters worse, the market is seemingly inundated with self-proclaimed AI companies. A recent report has suggested that 40 percent of start-ups in Europe that are classified as AI companies do not actually use artificial intelligence technologies in a way that is “material” to their businesses. As someone who researches and works in the business of AI, I can readily observe this phenomenon has already eroded the trust of many companies, making them increasingly cautious when proceeding with investment and deployment of AI.

 

Gradual developments, not quantum jump

For these reasons above, the adoption of AI, and by extension, in the area of circular economy, will be slow. This, however, does not mean there will be no advancement. Instead of “big bang” new business model creations, AI will most likely produce circular advantages through baby steps in operational enhancement gradually. For instance, one of the important elements in achieving circular economy is better asset management. In a recent research project for the European Defence Agency, my colleagues and I have discovered that there is a wide spectrum of operations for ministries of defence to save money and practise circular economy, from refurbishing and repurposing small military equipment items to reduce waste and minimise the use of virgin materials to extending the service years of capital assets. Unquestionably, the same may be applied to civilian activities. For example, combining the power of AI and drones can extend the longevity of major infrastructure such as reactors and bridges.

Advancements in drone technologies have allowed them to be deployed to take pictures at heights that are dangerous for inspectors to reach. The contributions of AI come from its ability to analyse and identify cracks as well as defects on assets that are not always visible to human eyes from captured images. Consequently, problems are detected before the assets become irreparable, thereby lengthening their lifetime.

A seemingly insignificant but potentially huge possibility of waste reduction would be saving on paper use. In the insurance industry, for instance, there is still a huge reliance on actual paper, with the communications between various stakeholders, including the underwriters, brokers and insured, passing on a large number of physical documents. AI techniques, in particular natural language processing, can help speed up the digitalisation of documents as they can go beyond the point of just reading and processing text to recognising and recording signatures and rubber stamp marks. Little by little, it will be possible to lower paper consumption.

 

The future is now

Both AI and circular economy are by themselves breakthrough ideas that are set to change the world dramatically. Combined, it can be a very powerful force of good. But this can only be achieved if we can synthesise them. For AI and circular economy to work together, it is necessary to educate AI developers to be more familiar with the idea of circular economy as well as making circularity practitioners and researchers more AI-savvy. Holding just half of the equation, we risk missing out on most of the intelligence. After all, no matter how smart machines can be, ultimately, it is the human intelligence – or stupidity – that determines the kind of future that we will be having.

 

Extract of “The AI Republic: Building the Nexus Between Humans and Intelligent Automation”

 

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