As digital twins come of age, they’re becoming less terrible
From megaprojects to enterprise-level data analytics investments, are digital twins getting easier?
Digital twins are essentially IoT projects that establish bi-directional real-time data flow between physical assets and their virtual representations. The collection and transmission of data from the physical to the virtual twin is enabled by IoT sensors. Digital twins are already widely used in manufacturing, where the most impressive use cases include predictive maintenance and the servicing of remote assets such as offshore wind turbines or telco towers.
Digital twins of prototypes can also make product development much faster and cut down on time-to-market considerably. By ingesting prototype data into the digital model, developers can tell how the physical asset will react to changes in the environment – information that can be used to make changes to the prototype to enhance the future product’s performance. Digital twins of factories were also of great service during Covid, when physical contact in those factories was limited. In 2021 Industry 4.0 flagbearer GE was estimated to have more than 500,000 digital twins in place, while Tesla creates one for each individual car that comes off its production line.
Advancements in sensor, reality capture and network technology mean that digital twins are becoming ever more faithful replicas of physical assets on an increasingly granular level. The first step to creating a digital twin is capturing how the real asset looks. Currently, there is a wide variety of ways in which a digital image of an object can be generated such as LiDAR, a combination of laser and radar technology that renders objects as a cloud of data points in 3D space; photogrammetry, which relies on photographs to reconstruct a 3D image; and 3D scanning.
Thanks to the accessibility of these survey technologies, capturing reality is not where the stumbling block of digital twinning lies. The real difficulty, rather, comes at the stage of overlaying the disparate sources of object data onto the 3D rendering of the object. Data sources can range from time-series sensor data, video feeds, testing or maintenance records. To enable the mapping of various sources of data onto the 3D image, a knowledge graph is created, which will provide common access to all connected data, as well as the relationships various data has with the physical environment. Today, software available through Azure Digital Twins or the AWS IoT TwinMaker renders digital twins more accessible for businesses by automating this rather complex process.
Digital twin megaprojects make great headlines. However, medium-size or large businesses shouldn’t feel daunted by either Nvidia’s Omniverse project, which is aiming to build a digital twin of our entire planet, or the National Digital Twin programme of the Centre for Digital Built Britain. First of all, any physical asset that is changing and where those changes are possible to capture, can serve as a real-life model of digital twins. Secondly, digital twins can be generated not only of physical objects but also systems, processes or even human beings. By creating digital replicas of complex supply chains, for example, and running various scenarios of disruption through them, supply chains can become transparent and more resilient.
Businesses with more limited resources than governments or cities can also consider what level of data fidelity they need for their use cases. Sometimes fewer data points and daily or weekly data updates between the physical asset and its virtual representation will suffice for their purposes. Moreover, imposing projects also start with the digital twinning of multiple layers of objects or subsystems. Consequently, a vast number of digital representations and hundreds of thousands of ecosystems need to be connected before national or global twins are generated.
There is no denying that the more digital twin ecosystems are connected, the bigger the efficiencies and other benefits are. But tomorrow’s grand or enterprise-level projects need to start today with strategically-aligned small-scale digital twins that can be eventually connected and form fully-fledged ecosystems.
Zita Goldman
Meet the company behind UK's Gigabit broadband rollout
Millions of homes are being powered with fast broadband connections across the United Kingdom
Home to more than 60 million internet users, the UK is going through a connectivity revolution with millions of homes set to enjoy improved broadband speeds. The service providers in the UK are continuously upgrading their fibre optic backbone networks and communications infrastructure in this direction. Sterlite Technologies Limited (STL) is supporting the top telecom and digital service providers across Europe in its large-scale network build-outs. Ankit Agarwal, Managing Director at STL, tells us about how the company has grown to become the UK’s most reliable digital network partner.
How long has STL been active in the UK and who are you working with?
We entered the UK market in 2007 and at around the same time, Openreach was spun out of BT to become the country’s main network infrastructure provider. We have been working with Openreach for the last 14 years.
In recent years, as Openreach has focused on rolling out the UK’s first full fibre network, we have strengthened our relationship, and today we are a preferred partner – playing a key role in helping Openreach connect millions of homes.
New fibre providers are emerging and STL is working with most of them – right from Tier 1 telcos to reputed alternate service providers.
How is STL enabling digital transformation in the UK?
We started small in the UK, but we always saw it as our second home market and looked at the digital landscape holistically. In the optical fibre industry, delivery lead times have always been a crucial challenge. We set out to solve this problem for the European market around 2015. We acquired a local Italy-based operator and set up the most advanced manufacturing of optical cables to cater to the demand in the UK and Europe.
We later also acquired Optotec, an optical interconnect company in Italy. This category of products is the single biggest driver of rolling out FTTx really fast. On the data centre front, we strengthened our interconnect capabilities and have been connecting data centres across Europe. Quite recently, we set out to enable operators in the UK to deploy FTTx very fast by setting up our services business in the UK and acquiring Clearcomm – a UK-based network integration company. As of now, we have close to 200 employees across the UK.
We are in the process of building a new manufacturing presence in the UK that will focus on the design and manufacture of fibre solutions such as Celesta, STL’s high-density optical fibre cable. This facility will also serve as our UK hub for 5G research and innovation.
How do fibre networks relate to 5G? What can the UK do to its digital networks to expand its 5G coverage?
In simple words, a strong optical fibre architecture provides high capacity and bandwidth to a 5G network. With the 5G network, emerging technologies like Video on Demand (VoD), IoT and artificial intelligence will burst out inordinate amounts of data. To handle this data, service providers are upgrading their backhaul networks with fibre technology that will enable them to deliver unlimited bandwidth.
For the UK to expand its 5G vision, along with a strong optical fibre footprint, it also needs open, disaggregated, programmable networks that can support the 5G use cases. The UK government recently launched a £30 million competition to fund R&D projects that accelerate adoption of OpenRAN and position the country as a leading player in a new era of disaggregated networks. The sovereign also requires robust and quick network deployment that delivers stage-wise excellence. STL, with its unique capabilities across all layers of the network, is well-positioned for this space.
What will be the wider social impact of these digital networks?
The need for ubiquitous internet connectivity is greater than ever. These digital networks will shape everything from GDP and industry momentum to inclusion and equal opportunity. As a society, we need to invest in developing fibre-powered broadband highways that reach every corner of the UK – and the world. The digital sector contributes £149 billion to the UK economy and currently employs 2.9 million people. According to McKinsey, improving infrastructure could add $13 trillion to global GDP by 2030, transforming billions of lives in the process.
What is the impact of digital technology on sustainability?
Over the past year-and-a-half, the world has witnessed the power of digital networks and technologies in unexpected ways. Increased digitalisation brings with it a great opportunity for more sustainable activities. Future businesses and societies will have sustainability at their core. Having said that, as industry captains in the technology space, it’s our responsibility to bring sustainability to the centre of all business agendas. STL has always relied on technology-led innovation and the same applies to our sustainability efforts. We have integrated our operations and CSR programmes with the UN Sustainable Development Goals (SDGs). For example, we became the first optical fibre and cable producer globally to be Zero Waste to Landfill certified, and by 2030 we aim to become a Net-zero emission and water positive company.
by Ankit Agarwal, Managing Director, STL
To find out more, visit www.stl.tech
INDUSTRY VIEW FROM STL
The future of work is freelance: addressing the talent gaps during The Great Resignation
Whether it’s called The Great Resignation, The Great Realisation, The Big Quit or any of the many other terms lent to this trend in the labour market, one thing is certain – people are burned out and quitting their jobs at a pace that hasn’t been seen in decades.
The world is upon its two-year pandemic anniversary – we’re living through a period where people don’t know what their lives will look like in a month, a week or sometimes even a day. This uncertainty is forcing them to re-evaluate their relationship with their work. Does what they do interest them? Does it give them purpose? Does it allow them to spend time with their families? Does it give them the flexibility they’re looking for? Are they being compensated fairly? All these factors are being taken into consideration. People around the world have spoken, and the answer to these questions in many cases has been a resounding “no”.
In December 2021, there were roughly 1.3 million job vacancies in the UK. From July to September, around 400,000 people quit their jobs. This is up from 270,000 in the same period in 2019. Last year was the first time since the 1990s that the workforce got smaller. And people aren’t necessarily jumping for joy at the prospect of finding a new job. This is making it massively difficult for companies to find talent – once always there and ready to work, much of the workforce is simply not interested anymore. According to a recent survey from Fiverr of more than 2,000 workers based in the UK, more than a third (35 per cent) of respondents said their company is struggling to recruit/find staff.
Part of the problem is that the way companies think about their workforce has traditionally been in the form of an employer/employee relationship. And yet 2020 brought on not just a global pandemic, but a global reckoning about what work in the future should look like. Businesses need to address this notion that people don’t want to work in the same way they have been for decades. They need to think differently about their hiring practices and the best ways to move their business forward.
Enter freelance talent. The pandemic led to an explosion in the freelance workforce, as millions of highly educated, skilled professionals decided not to return to full-time employment, even when the opportunity presented itself. Instead, they chose the freedom and flexibility that comes with freelancing. And with millions of skilled freelancers around the world vying for contract- or project-based work, they are the perfect solution to fill in talent gaps during this time.
Freelancers don’t resign
They were never full-time employees to begin with. When bringing on freelance talent, there's no need to waste time on interviews, vetting or guessing games. And even easier than a request for proposal (RFP) process, where department heads need to listen to and evaluate pitches from people often gathered through word-of-mouth recommendations, platforms such as Fiverr Business are designed to demonstrate everything about specific freelancers or agency teams up front. They allow for complete and total integration into existing team and department structures. The platform takes care of everything. And the best part is, if the freelancer helping with the project is not available anymore, or does not want to continue with the work, there are thousands more at the click of a button.
Agile workforces are the workforces of the future
In Managing the Future of Work, researchers at Harvard Business School and Boston Consulting Group’s Henderson Institute, found that 90 per cent of companies surveyed see a future competitive advantage in shifting their talent model to a blend of full-time and freelance employees. This shift in perspective is likely due, in part, to the pandemic mindset that many white-collar workers were forced to adapt to – the idea that remote work is the new norm and companies have to remain flexible. Managers have built up their confidence in managing remote teams; this, in turn, has led to an increase in understanding how freelance talent can help. By embracing a flexible work model, both internally and externally, they can speed up operations and deliver faster on strategy, while at the same time adapt quickly to changing environments.
By embracing a flexible work model, companies will not only be able to fill the skills and talent gaps they currently have in their workforce, they will find that it will help them improve efficiency and scale quickly, all while maximising their costs and output. Digital talent platforms such as Fiverr Business are making it possible for companies to be adaptive, flexible and able to respond in real time to changing market and environmental factors.
Shany Malbin
INDUSTRY VIEW FROM FIVERR
Artificial intelligence carries a huge upside. But potential harms need to be managed
Artificial intelligence and machine learning have the potential to contribute to the resolution of some of the most intractable problems of our time. Examples include climate change and pandemics. But they have the capacity to cause harm too. And they can, if not used properly, perpetuate historical injustices and structural inequalities.
To mitigate against their potential harms, the world needs frameworks for the governance of data that are economically enabling and that preserve rights.
Artificial intelligence and machine learning operate on the basis of massive datasets from which algorithms are programmed to discern patterns. These patterns can be used to infer new insights and also predict behaviour and outcomes. Increasingly, artificial intelligence and machine learning are being used to substitute human decisions with automated decision making on behalf of humans. This is often in areas which can have a significant impact on peoples’ lives. Take access to loans or even access into a country.
Yet it all happens in a black box that even the designer the algorithm may not have access to, so deciding what goes into the box is important.
The biggest datasets and algorithmic activity are generated by the global social networks that surveil our every action online. These datasets can be used to anticipate and mould our needs and desires.
Big technology firms, multilateral agencies and development banks have made much of the potential of artificial intelligence to advance economic growth and national development. And they’re increasingly being used in social and economic applications as well as public decision-making, planning and resource allocation. These include guiding court judgments, selecting job applicants and assigning scholars to schooling systems.
The COVID-19 pandemic has also highlighted the enormous value of public data and the potential value of combining public and private data to deal with public health and disaster crises.
Yet, there is growing concern about the uneven distribution of both the opportunities and harms associated with artificial intelligence.
The threats
The increasing use of artificial intelligence and machine learning in public decision making is raising critical issues around fairness and human rights.
In particular, how digital data are produced is being red flagged. Datasets have some huge gaps. Certain people are rendered visible, underrepresented, and discriminated against as a result, in the way data are collected. The fact that most of world’s population isn’t connected to the internet and the global social networks that drive the new, data-driven economy means they simply don’t exist.
Globally, artificial intelligence also poses a risk to the progress made toward gender equality. Stories abound of artificial intelligence systems being biased against women and gender minorities.
What’s more, artificial intelligence systems may rely on assumptions and data that exclude or misrepresent groups that already face multiple and intersecting forms of discrimination. This often results in outcomes that reflect and reinforce gendered, racial, and ableist inequalities and biases.
These systems are not adequately subject to the kind of rigorous accountability and regulation needed to mitigate the risks they pose to society.
So significant is this threat that several international forums have emerged that are committed to the development of “good”, “ethical” and “responsible” artificial intelligence.
But most of the initiatives present technical solutions to social and political problems. This means they are being developed outside a human rights frame. They are also largely initiatives of the global North, with limited multistakeholder participation from the global South.
A right-based approach
There are rights-based data frameworks which inform artificial intelligence development. These include the European Union’s General Data Protection Regulation. But they tend to focus primarily on first generation or fundamental rights, such as privacy. Privacy is broadly conceived of as an individualised right. It may not always be the chief value in more communitarian-centred societies.
The COVID-19 pandemic has highlighted the need for data to be regulated in the collective interest or common good. This does not mean that the right to privacy
needs to be foregone.
Collective interest also pertains to the governance of data in the context of identifiable groups or communities where the potential consequence of individual identification results in the exposure of collective identity.
The literature and practice of data governance has predominantly been viewed and undertaken from this negative regulatory perspective. In other words, with a focus on compliance with data protection and cybersecurity and penalties for breaches.
This is a necessary condition for just artificial intelligence. But it’s not sufficient. There are many areas of data governance that require positive intervention. Examples include enabling access to data, its usability and integrity if it is to deal with issues of inclusion, equality, redress, and social justice.
These are issues that can be understood as second and third generation, social and economic rights.
AI that respects human rights
To address these issues, a new global project is being launched on the side-lines of the Summit for Democracy.
The summit represents an international forum to advance commitments in support of democracy and human rights. Its objective is to assess the progress being made by countries in advancing artificial intelligence that respects human rights and democratic values.
The project is known as the Global Index on Responsible AI. It is being led by the African digital think tank, Research ICT Africa, and an independent Data 4 Development network.
Governments and the international community have started to respond to the global call for responsible artificial intelligence. In 2019, 42 countries signed up to the OECD principles on Trustworthy AI. This commits them to ensuring that AI systems are safe, fair, and trustworthy.
Most recently, UNESCO developed Recommendation on Ethics in AI was adopted by its 41st General Assembly. The recommendation centres on the protection of fundamental rights and freedoms, environmental sustainability, and diversity.
The Global Index addresses the need for an inclusive, measurable standard that complements the rapidly evolving understanding of what responsible artificial intelligence means in practice. It also encourages and tracks the implementation of governance principles by relevant actors.
The Global Index will track the implementation of responsible AI principles in over 120 countries. An international network of independent researchers will be established to assess the extent to which the principles are being applied. It will also collect primary and secondary data on key indicators of responsible artificial intelligence.
This will equip governments, civil society, researchers, and other stakeholders with the key evidence they need to uphold responsible use principles in the development and implementation of artificial intelligence systems. The evidence will also be used to:
- meet development and human rights obligations,
- build capacity for responsible AI around the world, and
- deepen international co-operation.
The public and other interested stakeholders will be given an opportunity to help shape the design and reach of the Index which will be developed consciously through a global South lens.
Its development represents an important opportunity for experts from the African continent, and the Global South, to be at the forefront of shaping the new global agenda on the responsible use and development of artificial intelligence.
Alison Gillwald, Adjunct Professor, Nelson Mandela School of Public Governance, University of Cape Town and Rachel Adams, Doctoral Supervisor, University of Cape Town
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Don’t jump too soon: understanding the lifecycle of data centre equipment
If you had to choose between extending the life of equipment that meets your current business needs or spending tens of thousands on new hardware, what route would you take?
Businesses often choose to replace their server, storage or network equipment every three to five years to reduce risk and improve performance in the data centre. Despite what the OEM might recommend, there is an alternative.
While it may be common practice for IT teams to plan a hardware refresh every three years, this can waste time, resources, and critical IT budget dollars. Simply put, this approach doesn’t make sense if your equipment is performing well and meeting demands. Before taking the plunge, consider your needs and research alternatives such as third-party maintenance (TPM).
Extending the life of useful IT equipment
Replacing your server, storage and network hardware unnecessarily is a poor way of investing limited CapEx and OpEx budgets. The reality is that most server and storage equipment continues to meet demands far longer than the “standard” three years without risking performance or reliability.
Many IT professionals assume that failure rates are high once new hardware is released and rise again as it gets older, but this isn’t the case. Service Express has analysed equipment data from more than half a million devices over the past 15 years. The findings show that data-centre hardware is reliable for longer than you think.
Storage failures
Storage devices generally consist of three critical and non-critical components: CPUs, system boards, disk drives, power supplies and so on. The chart below shows that failure rates barely increase with time.
Over five years, critical storage failure rates are between 0.1 and 0.2 per cent, equivalent to about one failure out of 1,000 components every month. This is why it’s important to consider extending the life of your equipment instead of falling into the cycle of a premature refresh.
Equipment refreshes introduce possible difficulties for IT teams. New hardware means teams need time to focus on getting familiar with new interfaces, processes and skill sets. The switch to new equipment can reduce operating efficiencies and cost more in time and productivity. Before replacing equipment that is approaching end of life (EOL) or end of service life (EOSL), consider your support options.
Extending the life of your hardware investment plays an essential role in helping organisations implement eco-friendly practices to keep hardware out of landfills and protect the planet.
If it’s working, don’t replace it
If replacing equipment too soon is suboptimal, what is the alternative? The answer is simple – keep using your existing equipment. But you’ll want to prioritise using the right data centre support solution.
While OEMs offer extended warranty agreements, the coverage is expensive with limited flexibility. Companies such as Service Express help organisations get more life out of their server, storage and network investments, maintaining equipment with quality parts, experienced engineers and lower support costs.
The ongoing pandemic, supply chain slowdowns and labour issues are impacting budgets everywhere. Service Express' 2022 Data Center & Infrastructure Report states budget reductions are one of the top three challenges for IT professionals. Using a third-party maintenance provider can save between 50 to 70 per cent compared with OEM support costs. These savings can be substantial and help your IT team cross lingering projects off their growing lists.
While offering lower maintenance costs than the OEMs, Service Express also makes customer service simple (no frustrating IVR systems) and dependable. To help ensure rapid repairs, hardware monitoring automates support by opening a service ticket when a failure occurs and immediately notifying a primary engineer to respond.
Planning for hardware longevity
Extend the life of your existing investment by rethinking your traditional refresh cycle. Adding a TPM solution to your IT strategy will help save critical resources while you meet demands. You can use the savings to fund other current initiatives or, when the time is right, for a strategic refresh. But only when it becomes necessary.
Service Express is a leading global data centre solutions provider. Its 2022 Data Center & Infrastructure Report is available here.
INDUSTRY VIEW FROM SERVICE EXPRESS
Accelerating digital transformation with low code
With the pandemic changing the business landscape, digital transformation, from merely being a buzzword, transformed into a reality for many enterprises across industries. According to a recent McKinsey study, “competitive differentiation, now more than ever, emerges from superior digital capabilities and technology endowment, more agile delivery and a progressively more tech-savvy C-suite”.
While the importance of digital capabilities has never been lost on business leaders, the sense of urgency attached to digital transformation has heightened significantly – so much so that speed is becoming a top priority for leaders across geographies and industries. Research suggests that the impact is felt even more resonantly in banking and insurance.
Digital competition is largely responsible for the increased pressure, but rapidly shifting customer behaviour is the key driver for this urgency. Customers expect their financial service providers to be a partner in their day-to-day lifestyle decisions. They demand ease of access to banking services or insurance policies the same way they hail a taxi or buy things online: instantly.
This need for speed is not limited to operational responsiveness. For instance, strategic agility – how fast a bank launches a new lending product or an insurance firm adapts its underwriting philosophy and policies – matters more than ever.
Accelerating digital transformation demands a different approach from the traditional ways of managing business applications.
Low code for transformation with speed
“Business technologists want to create and execute their own ideas to drive more automation across their business applications and workflows,” says Gartner. “The needs of business-driven hyper-automation will drive the adoption of low code through 2022.”
Just as the cloud eased scalability and distributed access at an infrastructure level in the past decade, low code platforms can equip an organisation with the ability to develop their business applications faster through digital technologies that are abstracted for ease and functional richness.
Low code platforms do this by employing visual, declarative techniques instead of programming to build applications, accelerating the pace of pro developers and allowing business experts to lead or participate in solution delivery.
Low code as a concept is not new. Business automation and digital transformation platforms, such as NewgenONE from Newgen, have woven their architecture around low code philosophy and delivered solutions for more than two decades. And there is evidence of the speed advantage derived from a low code platform such as NewgenONE.
“Recently, a leading health insurance provider developed and launched a core health insurance system using NewgenONE,” says Alex de Capitani, Head of US Enterprise Operations at Newgen. “With NewgenONE’s low code capability, it was able to deliver on business expectations within eight months of expressing the need, even though most of its teams were working remotely due to the pandemic. The application has hundreds of screens, tens of processes, complex business rules, integrations, and strict security and compliance requirements. The traditional approach for such an ask would entail 2.5 to 4 times the time and effort.”
It is not surprising, then, that more and more enterprises are looking at low code platforms to accelerate their digital transformation initiatives. According to Gartner, by 2024, more than 65 per cent of application development activity will be driven by low code.
Value beyond speed: customer experience
Low code platforms are spread across a range of functional spectrums. At one end are the no-code platforms that support simpler business applications. The other end of the spectrum comprises the robust enterprise-scale process automation platforms that can enable rapid development of even complex mission-critical applications. A digital transformation platform such as NewgenONE belongs in the latter category.
The ability to deliver complex mission-critical applications with agility is a potent arsenal. Those are the applications that drive the key customer outcomes.
In banking, for instance, being able to close a large, complex, commercial loan with speed is formidable competitive leverage. However, it is not only about being fast. A digital transformation platform can tie in the end-to-end customer journey – from loan application to funding – across channels, delivering a superior omnichannel customer experience.
And, when customer dynamics shift, as has been the norm in the digital world, these customer-facing applications can be adopted quickly with low code to launch new customer-friendly products and services before the competition catches up.
“Such accelerated digital transformation is becoming a key priority for our banking and financial services customers, driven by increasingly digital customer habits,” says Ashish Deshmukh, Head of Banking and Financial Services at Newgen. “We are in a great position to leverage our experience of almost three decades in enabling success for banking customers globally and to combine that knowledge with cutting-edge technologies to deliver an accelerated digital journey for our customers.”
In this rapidly shifting landscape – where underwriting is expected in real time, insurance risk management is transforming from mitigation to incident prevention, large complex loans are expected to be quickly closed and customers can easily switch loyalties – any bank or insurance firm cannot rest on their past laurels. The need to transform is now – and the answer is a low code digital transformation platform.
Kurt Dyer, Banking Lead (Americas), Newgen Software
Kurt Dyer has worked within the financial services space for over 22 years and have been a part of the Newgen Sales Team since 2016, managing the growth effort in the northeast and midwest markets. He oversees the effort with regional and community banks as well as the credit unions in the market which are looking to leverage technology to help grow their business and meet the changing demands of their customer and member-bases. Kurt holds a B.S. in Education from the State University of New York at Cortland and an MBA from Franklin University in Columbus, Ohio.
Alessandro De Capitani, Head of US Enterprise Operations
For more information, please visit www.newgensoft.com
INDUSTRY VIEW FROM NEWGEN
Is it the end of the road for mobile apps?
The role of mobile apps as a primary interface between consumers and businesses is shifting away from walled gardens to more flexible OTT environments
While Covid accelerated the importance of mobile and contactless experiences, consumer behaviour over the past five years suggests the mobile app is no longer the gateway to a better customer experience.
For most customer-facing enterprises, some of the most sought-after real-estate is on customers’ smartphone screens – making it a hotly contested arena. However, apps are looking increasingly redundant, even at a time when all businesses are digitally transforming to meet the needs of today’s connected consumer. For brands to have any hope of growing their mobile market share with loyal, long-term customers, not only do they need to capture consumers’ attention, but they also need to ensure clients and shoppers are being served in places convenient to them – which no longer seems to be inside an app.
According to Simform, the average person has 40 apps installed on their phone – but 89 per cent of their time is split between just 18 of them. That means less than 50 per cent of apps installed are being actively used, so brands that are dependent on in-app comms to engage with customers are likely not performing too well.
Simply put, customers don’t think in channels, so neither should brands.
Global research carried out by Statista with smartphone users indicated that the majority of respondents had a clear preference for receiving communications from organisations and service providers via email (46 per cent), SMS (24 per cent) and phone (24 per cent) – suggesting that today’s consumer wants to communicate with brands via multiple channels and through easy methods convenient to them.
By comparison, the use of established social media platforms’ in-app messaging applications for engagement is relatively low, at 11 to 12 per cent. If popular social channels are not being used to communicate through the app with hosts, it’s no surprise that less well-established brands in other verticals such as retail or hospitality struggle to engage through this channel.
Similarly, research by mobile consultancy Heady uncovered a number of significant customer pain points specifically around mobile transactions, which go some way towards explaining why people are increasingly eschewing mobile apps in favour of other methods to interact with brands. It showed things like mandatory app installs to try a service before being able to make a purchase are viewed by end-users as annoying barriers to consumption rather than fast routes to gratification.
While data overall shows people do still download apps (according to Statista, 230 billion apps were downloaded in 2020), it also illustrates they just as quickly delete them, often after just a single use. The uninstall rate also jumped significantly in 2020 compared to 2019.
This is bad news for app-first brands – who are not only missing out on revenue growth opportunities but also alienating customers for the long term.
Going forward, companies must find solutions that look at engagement through the lens of the customer. Omnichannel mobile marketing and digital contact centre models are key to addressing this change in customer behaviour and expectation, offering consumers the personalised experiences they love while enabling businesses to differentiate themselves from the pack through exceptional customer experience. It’s a world away from the closed mobile app environment.
With large tech providers streaming single-use apps to your phone or actively nudging developers to store parts of their apps in the cloud, together with evidence that customers prefer the immediacy of chat apps to engage and buy from brands, we may have just entered the beginning of a future where installation becomes obsolete and the border between website and native app is blurred. This is a future without apps, and it promises to be one of ultimate simplicity and elegance.
Maria Carrelli
Interview and innovate in the Interviewing Cloud
Software engineering leaders accelerate hiring and drive innovation by shifting technical interviewing workloads to the cloud
For most software engineering leaders, interviewing has historically been thought of as a time trade-off. It’s a zero-sum game. Hire or ship. Scale or deliver. This is the dilemma facing the engineering hiring manager today. However, it represents an antiquated way of thinking. By shifting technical interviewing and hiring to the Interviewing Cloud, it’s possible to transcend the trade-off. To hire and meet delivery commitments. To interview and innovate.
With engineering time more valuable than ever, many companies invest 80 hours or more of engineering time per hire. At an industry level, this translates to $60 billion a year in time spent interviewing and screening candidates, which comes at the expense of critical coding time and limits companies’ ability to innovate and create future value.
Yet, despite that investment, hiring managers are still struggling to provide enough capacity to screen and interview candidates at the scale required to meet hiring targets. The lack of interview availability slows hiring, and the time being invested is not effective. Do-it-yourself interviews are often unstructured and inconsistent. Most organisations aren’t able to conduct enough first-round technical interviews with the quality and consistency needed to meet hiring targets. We call this the Interview Gap.
The Interview Gap exists because interviewing is not anyone’s primary job. Software engineers are not evaluated or rewarded for how they interview. Furthermore, very few organisations have the ability to build the platform and content required to provide the tooling required to interview efficiently, consistently and with equity.
At Karat, we built the world’s first human and tech Interviewing Cloud to help organisations maximise their interviewing investment to win the race for technical talent in a world that faces a multi-decade shortage of software engineers. Today, Karat conducts more first-round technical interviews than any company on the planet.
What is the Interviewing Cloud?
Put simply, the Interviewing Cloud is the on-demand delivery of first-round technical interviews, 24/7, independent of location, for engineering candidates anywhere in the world.
The Interviewing Cloud combines a global network of Interview Engineers and purpose-built interviewing infrastructure to deliver predictive, fair and enjoyable interviews at scale. Interview Engineers are experienced developers who conduct technical interviews. They use a structured approach, a consistent process and proven content that produces the strongest hiring signal for clients and an enjoyable, flexible interview experience for candidates.
The Interviewing Cloud unlocks valuable engineering time and delivers unique analytics and insights. These insights can help identify market benchmarks on candidates, examine every step in the hiring processes and optimise the pipeline to accelerate hiring velocity, improve the quality of hires and inform strategic hiring decisions.
The advantages of cloud interviewing
1. Increased engineering productivity
The Interviewing Cloud increases interview capacity without the engineering productivity trade-off. Shifting technical interviewing from your organisation to the cloud immediately unlocks engineering time, which is redeployed to innovation on an ongoing basis.
On average, organisations get back two hours of productive engineering time for every first-round technical interview – not to mention further efficiency gains in the final interview round when multiple engineers are interviewing one candidate. Most companies invest at least five hours of engineering time in every final round interview, with some up to eight hours per final round candidate, so this ability to optimise the hiring signal is critical in reclaiming productive engineering time.
Finally, there are even longer-term gains in engineering productivity that result from the incremental hires made when final round interviews become more efficient and hiring accelerates. By hiring more engineers sooner than they would have otherwise, engineering organisations increase productivity that is entirely invested in innovation. The net impact for engineering organisations is that they unlock up to five hours of productive engineering time spent innovating for every first-round technical interview Karat conducts on their behalf.
2. Improved hiring signal
The Interviewing Cloud produces a stronger hiring signal than traditional interviewing because of the consistency of the interview process and content. Every first-round technical interview for a given role is executed consistently, measuring the same competencies, aligned and calibrated to your specific hiring bar. The presence of a human conducting the interview reduces both false positives and false negatives and therefore increases hiring efficiency and yield. By optimising the hiring signal in these ways, Karat has helped organisations achieve onsite interview efficiency and yield that is up to three times higher than the status quo.
3. Competitiveness for engineering talent
The Interviewing Cloud accelerates hiring velocity and improves hiring efficiency for organisations. It also delivers interviews more quickly for candidates, moving at the speed the candidate prefers to go at. Given the increasing shortage of engineers, this is crucial in competing for talent. By offering on-demand interviewing capacity 24/7, Karat moves candidates from technical interview invitation to completion up to four times faster than traditional DIY interviewing.
| Time in Karat process | Per cent scoring in top two tiers | Onsite to offer rate | Closed offer % | Candidates per hire |
| 3 days or less | 36% | 37% | 59% | 15 |
| 3 to 7 days | 33% | 36% | 57% | 18 |
| 7 to 14 days | 31% | 32% | 54% | 22 |
| 14+ days | 26% | 30% | 52% | 29 |
In a candidate-first world, creating an enjoyable and equitable hiring process is paramount, and the Interviewing Cloud creates opportunities for more enjoyable and equitable hiring. Elastic interviewing capacity means that candidates can schedule interviews on their terms wherever they’re located in the world. Furthermore, half of all candidates interviewing on Karat’s cloud elect to interview on evenings and weekends.
It also means that recruiting teams can send as many candidates as possible to do first-round technical interviews, reducing the bias that often comes with traditional screening processes – whether human or machine-driven. This opens up opportunities for more candidates and often leads to hires you wouldn’t have made otherwise. It also unlocks opportunities for innovations like a redo interview, which especially benefits candidates from underrepresented and non-traditional backgrounds who often have less exposure to technical interviews than their overrepresented counterparts, and reduces false negatives.
4. Fair and equitable hiring
Having a structured interview process, consistency and content also neutralise the systemic bias inherent in DIY interviewing. Structurally, CV-blind interviews remove a pervasive source of screening and interviewing pedigree bias. Consistency ensures that an interviewer’s style won’t impact a candidate’s performance. And when content is designed specifically for the competencies required for a job, the subsequent recommendations are based on a more predictive measurement system.
The presence of a human in the interview reduces false negatives compared to automated tech-only code tests or AI screening tools by introducing the ability to provide guidance to the candidate when needed. Not only does this more closely mirror real-world working and collaborating within engineering teams, but it also disproportionately benefits non-traditional candidates. By reducing these false negatives, hiring yield increases and a wider range of candidates can demonstrate their highest levels of ability.
Hiring in a talent-first world
As the race for technical talent continues to intensify, every hiring and talent decision is of critical importance. By offering on-demand interviews and flexible scheduling, your company can show up on your candidates’ terms and at the speed they’re demanding in today’s talent-first world. Make sure you’re saying yes to the right people and doing it in a way that enhances your engineering organisation’s delivery goals.
To learn more about how the largest independent residential real estate brokerage in the US is using the Interviewing Cloud to disrupt the real estate tech sector, check out Karat’s case study
By Shannon Hogue, Head of Solutions Engineering, Karat
INDUSTRY VIEW FROM KARAT
Participation is the spark needed to ignite customer experience in 2022
A burgeoning appetite to share and recommend goods and services means your best customers will play key roles in your growth
For marketers yet to turn their attention to the extraordinary customer acquisition mechanic of earned growth, referral might be the last marketing channel to come to mind.
For those already giving their customers a participating role in their brand’s successes, it’s the last marketing channel they’d switch off.
This was literally true for the Head of UK Marketing at one of Europe’s largest online florists. She knew the customer lifetime value the business derived from referral marketing exceeded that of both paid search and paid social.
The business had so much confidence in its referral marketing programme as a growth driver that when it was forced to ‘turn off’ marketing in May 2020 after the COVID-19 pandemic prompted the first lockdown, referral marketing was the only channel it left running,
The florist grew its UK referrals by 800 per cent, despite promoting it at fewer points in the customer journey than previously.
But then, the florist had already racked up the kind of referral results across its eight country markets that gave it confidence in plumping for advocacy as the sole marketing channel to help navigate a new crisis.
The online florist has generated close to £17 million in sales through customer recommendations alone since launching a referral scheme in 2014.
More than 60 per cent of referrals made by its customers convert into new customers. And of those new customers, 35 per cent go on to refer the brand to their friends and family.
The head of marketing, meanwhile, says her team tests constantly to learn how various markets and customer cohorts respond differently to messaging and incentives through referral campaigns.
Such success stories were once rare for a marketing channel that is now fast growing into its own skin and becoming comfortable with a more pivotal, strategic status in the marketing stack.
A recent Harvard Business Review article co-authored by Fred Reichheld, the creator of Net Promoter System, explores earned growth’s commercial benefits and the metrics that make it meaningful.
Regarding the advocacy that earned growth is built upon, it states: “Firms today undervalue referrals. They treat them as icing on the cake rather than an essential (perhaps the most essential) ingredient for sustainable growth.”
Traditional household brands and established retailers are now joining pure-play online businesses in approaching customer acquisition and experience with an ‘advocacy-first’ mindset.
This shift towards earned growth isn’t a replacement for anything. Comprehensive Referral Engineering programmes act as a valuable addition to, and amplifier of, existing marketing strategies.
A menswear brand put its first-party referral data to work across its paid social channels to target consumers that looked like its most valuable referrers. The experiment saw a 65 per cent increase in conversion rates, a 30 per cent jump in return on ad spend and a 12 per cent reduction in the cost of acquiring new customers.
The trend your customers won’t let you ignore
Crucially though, none of the above speaks to the single most important opportunity addressed by a move towards earned growth.
That is, that advocacy – and importantly, the level of participation it encourages in those we sell to – is slowly shifting the emphasis of marketing from the brand to the customer.
Referral is data-driven, but it’s absolutely customer-led.
Amplified in the past two years by the forced loss of so many day-to-day freedoms we once took for granted, consumers are hungry for autonomy and self-determination. They want a more direct role in the way they shop for, and engage with, the products and services with which they choose to identify.
Influencer marketing may be big business, with suggestions the industry was set to grow to $13.8 billion at the end of 2021, but our research finds almost 60 per cent of people are more likely to buy a product recommended by a friend or family member than by a celebrity or social media creator.
When it comes to influencing, it’s the people we know who have the real power as opposed to beautiful strangers with well-oiled content-creating machines.
Consumers want to participate: to interact, share and recommend. Your buyers’ e-commerce journeys don’t begin on screens. Increasingly they start with offline conversations – not about your brand or product but about their interests, their needs and their lives.
What does that mean for your brand? Well, it means your best marketing in 2022 will likely happen in the most ‘un-marketing’ moments.
It means your effective media channels will include everyday occasions in your customers’ lives: chats between parents at the school gates; picnics and pub nights; weekend walks and barbecues with friends; Sunday roasts with the family.
Their participation will become as crucial in delivering experiences that match your customers’ expectations as personalisation has been in recent years.
For while automation driven by big data transformed customer experience capability, the spreadsheets and numbers that dominate our customer experience conversations risk becoming somewhat divorced from the end-users they represent.
Abstract scores only tell us so much about our customers’ values, their beliefs, their versions of what a relationship with our brands should look like.
‘If you’re only leaning on data, you’re not taking into account human condition, experiences and feedback,’ said Denver-based organisational psychologist Melissa Doman.
New perspectives and a shared commitment to twinning first-party data with more innovative partnerships will get brand marketers closer to the customer stories that end-users would recognise, buy into and participate in.
Referral is a rare marketing discipline, carried out in the culture and language of consumers – normal people who don’t share the marketer’s vocabulary of ‘funnels’, ‘touchpoints’ and ‘conversions’.
Our businesses are drowning in third-party data (though perhaps not for much longer). Yet how much does this data really tell us about our customers? There’s an unfilled gap between the reported customer insight that much of our data promises and the legitimacy of customer participation. It’s a gap similar to that between reading sheet music and being in a live audience while witnessing a spine-tingling performance.
After thousands of years of retail, your customers still sell your stuff better than you do, without even trying. Now we have the expertise to understand the psychology of referral and the science to drive, track and measure it, you can give your best customers the power to grow your companies.
INDUSTRY VIEW FROM MENTION ME
Three data objectives for marketing success in 2022
As we head into a new year, it’s an exciting time to be the kind of marketer that sees the discipline of marketing as a science as much as an art. With consumers interacting with brands across an ever-widening spectrum of touchpoints, marketers have near-infinite opportunities to harness data to understand their customers better than ever.
But there’s an elephant in the room here – despite the riches available to us, marketing is far short of being the data-driven discipline that it could be. In fact, Capgemini’s recent CMO report indicated that only 11 per cent of marketers could call themselves “data-driven” – a fairly damning indictment. So what happened here, and is it set to change going into 2022? More to the point, what should you be looking to do to get ahead of the curve this year?
New year, new landscape?
It’s no secret that Covid-19 has impacted marketing efforts across the board, and advances in data discipline were among the hardest hit. Budget cuts meant the kind of infrastructural projects needed to advance a data-driven agenda were paused or cut, and unpredictability meant that marketing strategies that were trending towards the data-driven were often thrown out in favour of mass-marketing tactics, as circumstances changed rapidly and marketers struggled to react. Overall, the disruption to working patterns, office hours and team culture meant that the kind of agile work environment needed to work with data was often put on pause.
So with the pandemic (hopefully) on the way out, are we set for a new era of data-driven marketing? Maybe.
It’s important to remember that when it comes to lack of innovation in data, Covid is not the whole story: as important has been the rising tide of privacy. With regulations such as GDPR, ePrivacy and CCPA being introduced almost daily, marketers around the world are feeling the pressure and slowing their progress towards becoming a data-driven function.
So what happens now?
Identifying what to do next
To identify what the new starting line looks like going into 2022, we commissioned a survey of 500 senior marketers with the aim of showing how different data practices correlate with overall marketing success. Respondents were initially asked how far above (or below) they achieved on their 2021 targets as a measure of their success. According to their attainment, they were then sorted into five distinct success archetypes:
- The Top 1 per cent: Achieved between 70-100 per cent above target
- The Overachievers: Achieved between 30-60 per cent above target
- The Moderate Marketers: Achieved target or exceeded it by 20 per cent
- The Struggling Marketers: Achieved between 10-50 per cent below their target
- The Bottom-Tier Marketers: Achieved between 60-100 per cent below their target or lower
The respondents were then asked questions designed to analyse the degrees by which they leverage customer data, and these responses were indexed against their success. By studying what the most successful marketers are doing with their data, we’ve produced three key objectives that everyone should look to achieve in 2022 in order to stay ahead of the pack.
1. Achieve a single view of the customer by the end of the year
For many, the single customer view is the holy grail of marketing – it requires painstaking unification of dozens (perhaps hundreds) of data sources, which is an organisation-wide challenge. Research showed that the more successful the marketer, the more likely they are to have a golden record – and adoption of a single customer view falls of a cliff when we begin to look at less successful marketers:t
But while the most successful marketers are ahead of the pack in terms of unifying their data into one single customer view, it won’t be long before other marketers catch up to them. Of the marketers who’ve yet to achieve a single customer view, they expect to do so before the end of 2022:
This timeline sends a clear message that this first, foundational stage of the race for data-driven marketing is very nearly over.
2. Get a CDP (and maybe trade in your DMP)
Customer Data Platforms (CDPs) saw an incredible surge in adoption in 2021, with the industry reaching an estimated $1.6 billion in revenue. In looking at their relationship to marketing success, the research was clear: the more successful marketers have already begun making the shift to CDPs.
CDP adoption yielded a 39 per cent increase between the least and most successful marketers –the biggest jump out of the five platforms surveyed. And while the most successful marketers transition to CDPs, the less successful marketers continue to cling to platforms such as DMPs. The latter primarily rely on third-party data, retain data for shorter periods of time, and are unable to identify users to create the most accurate audiences possible the way a CDP can.
Other data-related technologies show an interesting variance in adoption. Data warehouses and marketing automation platforms both show higher adoption rates across all segments – the fact that neither of these see a drop as CDPs become more common reflects how CDPs function to integrate with these technologies as sources, rather than replace them.
However, all of this should be seen in the context that overall data technology adoption has a long way to go – the highest adoption rates level out at around 50 per cent, meaning that those marketers who intend to achieve a single customer view in 2022 will need to move quickly to bring the right stack on board.
3. Get confident (but not overconfident) in data privacy
Third-party cookie deprecation is just one data fire marketers have to put out. Ever since the introduction of new data regulations such as GDPR and CCPA, marketers have faced a huge challenge in how to capture, store and use customer data in a way that doesn’t fall foul of the law.
But there’s good – and perhaps surprising – news here. Across the board, marketers have exhibited a high level of confidence in the compliance standards of their data practices, with nearly 100 per cent confidence among the front-runners:
But there’s a problem. You’ll remember that earlier, we asked marketers whether they had a single view of the customer – what we see is that there’s a significant proportion of those marketers who don’t have a golden record who do express confidence about their data compliance. As we can see below, nearly one-third of Struggling Marketers who are confident about their data compliance lack a single customer view:
Why is this an issue? It goes back to the challenge of how data consent is captured in today’s multi-touch, multi-channel journeys: it’s highly likely that consent is captured across multiple tools (for example a consent management platform, a loyalty programme and email marketing), which means an individual can express (and withdraw) consent in many different places. Unless those choices are resolved, it’s likely that activating that data can fall foul of regulations.
This is why the single customer view is important: it means having a comprehensive view of a customer’s consent preferences across those multiple touchpoints and channels. This is why the marketer without a golden record might have misplaced confidence in their compliance.
Before you can feel any degree of confidence in your data privacy practices, you need to prioritise the consent journey just as much as the customer journey – and that starts with achieving a single view of the customer.
The way forward
Confidence aside, there are still some challenges ahead for all marketers when it comes to accessing and using their customer data to deliver the highest value to the customer. While it’s still early days, we should expect rapid acceleration of data-driven marketing practices as we enter a post-Covid world. For now, most of us are in the starting phase of creating the usable dataset – the proverbial golden record of a single customer view. As most marketers complete this foundational phase in 2022, we can expect the second stage to truly begin, in the form of the race for skilled talent and pioneering machine learning.
To uncover more data trends impacting marketing in 2022, download The Data Secrets of Successful Marketers research report.
INDUSTRY VIEW FROM ZEOTAP
We’re all data driven digital marketers now
Within the past year, there has been a growing realisation that digital, social and technology innovation are the primary means for acquiring and retaining customers. The divide between traditional and digital marketing remains, and has become starker – fuelled through the growth of the e-commerce sector, borne out of survival and boosted by the newly adopted buying habits, with changing customer behavior driven by the pandemic.
Those who were frequent online shoppers already continued with even greater intensity. However, the sector gained a new segment: those who rarely if ever shopped online, but were forced to change their habits out of necessity. The optimisation of e-commerce marketing channels became key to marketing effectiveness.
So what do companies who still have a large traditional marketing portfolio need to think about?
Traditional versus digital marketing
Communication with customers has evolved over the past 20 years with the huge cultural shifts of social media and mobile marketing. The communication shifted from “one-to-many” to “one-to-one”, with a much more targeted approach to customers’ needs, actions and wants. The approach was also influenced by recent transformational events, such as the worldwide pandemic.
According to a McKinsey report (June, 2020), these consumer behaviour changes are here to stay with the major shift towards e-commerce and trusted brands. Working from home and other restrictions are leading to consumers spending a lot of time online for both shopping and entertainment. Thus, the customer journey and user experience will be vital for brands during the recovery period. While traditional marketing is mostly built on raising customer awareness and trying to reach the target segment with TV, print, PR and direct selling, digital marketing focuses on driving engagement and personal connection with the customers.
Traditional marketing analysis is still driven by the creation of target personas with a subjective projection of the ideal customer whom marketers hope to reach with brand messaging. In contrast, the digital approach allows marketers to analyse customer behaviours, communicate with them directly with personalised messaging, collect the feedback online, build closer relationships with customers and consequently make smarter decisions about marketing strategy from these data.
Although this is simple in theory, there are new challenges marketers need to consider such as marketing attribution, tracking issues and walled gardens to consider before even measuring the contribution of each marketing channel. Thus, the demand for measurement was created, which can be successfully managed through AI models and predictive data analytics. The high-pressure competition in digital marketing means you cannot succeed without deep knowledge of your target consumers, and this knowledge can be only accumulated through data analytics.
Intelligent marketing combines traditional and digital
The challenge, then, is to become data-driven and unlock the potential in your own customer data, yet still take advantage of the branding power of traditional marketing. The analytical challenge here is the measurement of online and offline together, for holistic customer journey optimisation. Many businesses investing millions in marketing do not bother to invest in marketing analytics to accurately measure all the touchpoints a customer has gone through, from point A (seeing the brand on Facebook, or on a billboard) to point B (looking for a specific product with a generic search, or favourite brand search) to the final point C (the actual conversion). It leads to inefficient marketing and pressure on the marketing team to manage rising costs.
Better customer analytics helps manage budgets without losing sales. A holistic attribution solution incorporates both econometrics with digital attribution, incorporating social and offline brand marketing as well factors such as seasonal and regional variations. This provides a solution for measuring the customer journey both online and offline, which is crucial, especially where users are constantly using multiple devices, making accurate tracking a challenge. Once you have the initial attribution measurement sorted for marketing effectiveness, the next challenge is how to use the data to increase conversions, retention, ROI and make more intelligent marketing decisions overall.
Predictive customer analytics removes guesswork
The main advantage of using AI/machine learning models is the ability to predict your customer's next action on a case-by-case basis by analysing anonymised first-party customer data. This is far more precise than traditional marketing analysis based on generalised market research reports.
Digital marketing allows you to collect and analyse data about your own consumers and website visitors, but most companies do not fully leverage this valuable data. Analysis of the individual customer journey unlocks a personalised approach to building retention and increasing conversions online. Imagine if you could predict that a customer is more likely to buy if a certain offer is made at a certain time to encourage them further in the sales funnel? Customers can be accurately scored on the likelihood to convert, using machine learning, so that you can identify which segments of customers you can nudge into conversion with targeted marketing.
When marketers can predict who is likely to buy what, they can create highly personalised offers and actions to move the journey forward. This tactical predictive approach naturally complements analysis of which marketing channels and actions drive overall conversion and retention using the same customer data and predictive models.
The headline is, you no longer have to build your marketing strategy on guesswork! Machine learning modeling is here, and can solve the problems with attribution and other data analytics issues leading to low ROI.
That makes sense for customer acquisition, but what about retention?
Predictive data modelling can be applied to customer lifetime value (CLV) and retention. The idea is to combine analysis of the customer journey for repeat buyers, with data on how customer segments buy over an extended period. Marketing effectiveness allows smarter decisions about which campaigns and channels drive customer sales, while CLV allows you to adjust the focus to the most valuable customer segments – loyal customers making regular high-value purchases. Machine learning models also can be used to predict which customer is more likely to purchase again, and CLV values the customer as well as the specific sale, which in turn directs marketing efforts towards these customers.
In conclusion, using predictive customer analytics moves you beyond the limits of traditional marketing analysis, so you can focus on effective optimisation of both traditional and digital marketing. Traditionally focused marketers who do not take advantage of the abundance of digital data risk being left behind with an increasingly wasted budget. Now is the time to put data-driven digital marketing first, with traditional marketing in support, instead of the other way around.
For more information please visit www.metageni.com
INDUSTRY VIEW FROM METAGENI
Fight cyber-security threats with actionable data
Cyber-security programs haven’t caught up to the growing digital risks, but utilising data can protect more than you think
The news has been flooded recently with big-name organisations hit hard by cyber-attacks. The effects were alarming enough to prompt an executive order from the US government requiring government agencies to meet certain cyber-security standards.
Yet, to remain competitive in most industries, there continues to be a push for third-party connections to company networks and the ongoing adoption of SaaS products. Cloud-based solutions have taken over the world of business, with organisations adopting an average of 3.7 public cloud services in 2021, according to Flexera. However, SaaS adoption can introduce risk to networks.
This has forced organisations to re-evaluate the effectiveness of the cyber-security controls they have in place. The same tools you have used for years to manage security posture aren’t going to have the same effect in this age of digital transformation. With access to trusted and actionable data, security teams can take back control of network endpoints and help their company remain a trusted partner, provider and better business investment.
Cyber-security transformation
You’ve hired more security managers and IT support staff. You’ve added cyber-security questions into your vendor onboarding assessment and held yearly breach prevention training for your employees. The problem is, with the sophistication of cyber-criminals in today’s digital world, proper cyber hygiene requires program-wide transformation and continuous management.
This sounds daunting, but you might be surprised how the proper use of data can help with fending off cyber-threats. With up-to-date metrics providing consistent insight into your network’s endpoints, security managers can offer visibility into your entire network (and the risks hiding within); quantify network risks in terms of financial loss; and communicate cyber-security risk to the board of directors successfully.
By consistently focusing attention on these three areas, you’ll begin to understand the impact of your cyber-security decisions, communicate changes to key stakeholders and have a comparative view of your program’s performance over time.
Identify where risk exists in your network
This might seem obvious, but we’re talking about a bigger picture than the assessments done monthly or quarterly by many security teams. Threat actors can infiltrate networks through seemingly insignificant entry points, third-party networks or a piece of shadow IT connected through an unknown software or device. Gaining a complete view of every endpoint on your network and identifying if there’s any risk associated with them is critical.
Using an automated data-scanning technology that monitors your entire network continuously, without manual effort or initiation from your security team, will facilitate quicker identification and remediation of risks. Data-backed scanning solutions such as BitSight’s Attack Surface Analytics provide a continuous view into your network and can alert your team to vulnerabilities that might not have been discovered with manual scanning processes.
Identifying all of the risks throughout your organisation’s network will also help teams strategise and prioritise remediation efforts. Without a complete view of your network, it is impossible to allocate resources effectively to address the most critical risks. Deploying an automated risk monitoring tool is an important first step in transforming to better continuously manage risk.
Quantify risk in financial business terms
After you gain a complete view into your network’s risk landscape, the question turns towards prioritising risk management to best benefit your business. The majority of, if not all, business decisions rely upon what will best benefit the fiscal performance of the organisation: why shouldn’t your cyber-security choices do the same?
Instead of addressing risk on an ad-hoc basis, prioritise risk mitigation efforts based on the potential financial impact of the vulnerability. BitSight Financial Quantification for Enterprise Cyber Risk is the only solution to quantify the exposure of risks in an organisation’s network to reflect the financial impact.
With financial data to inform decision-making, risk managers can better reduce both cyber and financial risks in their organisation and promote business continuity.
Bring cyber-security data to the board level
Company executives might also have a newfound interest in cyber-security performance. This year has consisted of large and reputable companies being hit hard, financially and reputationally, by cyber-attacks. Security managers need to be prepared to demonstrate how an organisation is defending against attacks like ransomware, where money allocated to cyber-security programs is being spent, and how the organisation falls compared to competitors. Effective tools are needed to communicate the importance of cyber-security risk management to business decision-makers.
Providing cyber-security data in understandable performance reports is critical to implementing a company-wide security transformation. Reports need to be high-level to meet the experience of board members that might not have had to think about cyber-security in the past but provide enough actionable detail to help decisions get made.
BitSight Executive Reporting offers dozens of customisable reports to present cybersecurity data with the necessary context for organisations looking to better defend against cyber-threats. With options to demonstrate historical performance, performance compared to industry standards and peers, overall security ratings and scores in specific risk vectors, as well as many more depending on your organisation’s needs, security managers no longer need to worry that their message will be lost when presenting to company decision-makers.
BitSight data demonstrates a correlation between strong, consistent security performance and a reduced likelihood of experiencing a breach such as a ransomware attack. By consistently following best practices, and making cyber-security processes part of your organisation’s daily routine, security managers are creating more robust, all-around secure cyber-security programs.
To get started implementing the strategies discussed in this article, read BitSight’s eBook, Ransomware: The Rapidly Evolving Trend. To learn more about BitSight, visit bitsight.com
by Stephen Boyer, Co-Founder and CTO, BitSight
INDUSTRY VIEW FROM BITSIGHT
Chance encounters in the workplace help build trust – so how do you replicate that online?
For many of us it feels like there’s no going back – at least not full-time. We’ve had working from home foisted upon us. We’ve worked through it. We don’t want to give it all up.
Yes, there are employers who want everyone back into the office. Google, for example, plans to end its global voluntary work-from-home policy on January 10. But other employers are happy to let staff continue to work remotely. Australian software company Atlassian, for one, is insisting only that its employees come into the workplace four times a year.
Studies and surveys are consistently clear: most of us don’t believe our productivity has been harmed, and those who do are offset by those who think they are more productive. Crucially, many managers feel the same way.
The real sticking point in working from home is not the “work” part. It’s the loss of the fun parts of a workplace – the informal networking and socialising that’s good for the individual as well as the group.
Experiments in online socialising
Managers have had their reasons for being averse to remote working. Quite apart from worries about individual productivity, many studies have shown how proximity promotes communication. For example, when Harvard organisational researchers Ethan Bernstein and Ben Waber examined a major US retailer occupying a campus with more than a dozen buildings, they found just 10% of all communications took place between employees whose desks were more than 500 metres apart.
Over the past 18 months there have been many experiments with using technology to replicate this communication. I’ve been part of one as a university academic, moving all my teaching online, and another as an organisational consultant, helping a small enterprise make the shift to remote operations.
My client, a small private TAFE college, has 11 permanent staff as well as casuals. In May 2020 the college asked me to help it move all business processes – teaching, office communications, support services and more – online. This had to be done on a shoestring given the financial impact of the pandemic. In this work we agreed it was fundamental to address the need for socialising.
This presented some challenges, particularly for a small organisation.
The value of ‘casual collisions’
Work-based socialising occurs in two broad ways.
First are “organised” social activities, such as sharing a morning tea, getting lunch, or having drinks on Friday night. To some extent these aspects are the easiest to simulate, using conferencing apps. For my client, this included activities such as virtual drinks and online games.
More difficult to replicate are what organisational expert Jessica Methot and her fellow researchers call “casual collisions”. As they wrote in the Harvard Business Review in March:
The tidbits we learn about our colleagues – for instance, that they play guitar or love dogs – build rapport and deepen trust. Research even suggests that chance encounters and spontaneous conversations with our coworkers can spark collaboration, improving our creativity, innovation, and performance.
One of the best-known examples of designing a workplace for chance encounters is the headquarters of Pixar Animation Studios, which Steve Jobs oversaw during his exile from Apple. The building has a central atrium with bathrooms only on the ground floor, the idea being to create more opportunities for people to run into one another.
Yet the research by Methot and her colleagues also shows small talk can be both uplifting and distracting. This makes attempts to use software to replicate this informal, unstructured socialising even trickier.
Building an online networking space
In seeking to provide staff with an online substitute for casual collisions and chats in the lunch room, we chose an “enterprise social networking service” called Yammer. There are alternatives, each with their own strengths, but Yammer has the advantage of functionality similar to Facebook. The idea was to provide staff with an intuitive tool to communicate, and then leave it to them to use it as they liked.
It’s a work in progress. We’ve learnt some things along the way. One complaint was we didn’t provide enough initial training on how to use Yammer’s main options, which meant some staff took time to appreciate its use.
But most feedback has been positive. Despite the unplanned (and therefore chaotic) nature of the move, surveys indicate most staff think communication has actually improved. We appear to have avoided distance destroying dialogue and breeding distrust, as reported in other workplaces.
Can technology ever fully replace the serendipitous exchanges of a physical workplace? I doubt it. But done well it may provide enough of a facsimile to ensure there’s no downside to staff continuing to work a few days a week from home.
Michael Baron, Lecturer, Charles Sturt University
This article is republished from The Conversation under a Creative Commons license. Read the original article.