How Important is Industry Experience when Selecting your Tech Vendor?

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Identifying and selecting a vendor for your tech project can be a daunting task – especially when it comes to emerging technologies or when implementing a tech solution for the first time. Organisations look for a certain degree of alignment with their tech vendors – in terms of products and pricing, sure, but also in terms of demonstrable areas of expertise and culture. Several factors are involved in the selection process – vendors’ ability to deliver, to match expected quality standards, to offer the best pricing, to follow the terms of the contract and so on. They are also evaluated based on favourable reviews from the tech buyer community.

Often businesses in a particular industry tend to have their unique challenges; for example, the Financial Services industries have their specific set of compliance laws which might need to be built into their CRM systems. Over the years, vendors have built on their industry expertise and have industry teams that can advise organisations on how their business requirements can be met through technology adoption. These experts speak in the language of the industry and understand their business and technology pain points. They are able to customise their product and service offerings to the needs of the industry for a single client – which can then be repeated for other businesses in that industry. Vendors arm themselves with a portfolio of industry use cases, especially when they are entering a new market – and this often gives them an upper hand at the evaluation stage. In the end, organisations want less customisations to keep the complexity and costs down.

Do organisations evaluate vendors on industry experience?

Ecosystm research finds that industry experience can be a significant vendor selection criterion for some tech areas (Figure 1), especially in emerging technologies such as AI. AI and automation applications and algorithms are considered to be distinctive to each industry. While a vendor may have the right certifications and a team of skilled professionals, there is no substitute for experience. With that in mind, a vendor with experience in building machine learning models for the Telecommunications industry might not be perceived as the right fit for a Utilities industry implementation.

Whereas, we find that cybersecurity is at the other end of the spectrum, and organisations perceive that industry expertise is not required as network, applications and data protection requirements are not considered unique to any industry.

Is that necessarily the right approach?

Yes and no. If we look at the history of the ERP solution, as an example, we find that it was initially meant for and deeply entrenched in Manufacturing organisations. In fact, the precursor to modern-day ERP is the Manufacturing Resource Planning (MRP II) software of the 1980s. Now, we primarily look at ERP as a cross-industry solution. Every business has taken lessons on inventory and supply chain management from the Manufacturing industry and has an enterprise-wide system. However, there are industries such as Hospitality and Healthcare that have their niche vendors who bundle in ERP features with their industry-specific solutions. This will be the general pattern that all tech solutions will follow: a) an industry use case will become popular; b) other industries will try to incorporate that solution, and in the process; c) create their own industry-specific customisations. It is important, therefore, for those who are evaluating emerging technologies to cast their net wide to identify use cases from other industries.

AI and automation is one such tech area where organisations should look to leverage cross-industry expertise. They should ask their vendors about their implementations in other allied industries and, in some cases, in industries that are not allied.

For cybersecurity, their approach should be entirely different. As companies move on from network security to more specific areas such as data security and emerging areas such as GRC communication, it will be important to evaluate industry experience. Data protection and compliance laws are often specific to industries – for example, while customer-focused industries are mandated on how to handle customer data, the Banking, Insurance, Healthcare and Public Sector industries have the need to store more sensitive data than other industries. They should look at solutions that have in-built checks and balances in place, incorporating their GRC requirements.

So, the answer to whether organisations should look for industry expertise in their vendors is that they should for more mature tech areas. An eCommerce company should look for industry experience when choosing a web hosting partner, but should look for experience in other industries such as Banking, when they are looking to invest in virtual assistants.

Are some industries more focused on industry experience than others?

Ecosystm research also sought to find out which industries look for industry expertise more than others (Figure 2). Surprisingly, there are no clear differences across industries. The Services, Healthcare and Public Sector industries emphasise marginally more on industry expertise – but the differences are almost negligible.

There are some differences when we look at specific tech areas, however. For example, industries that may be considered early adopters of IoT – Transportation, Manufacturing and Healthcare – tend to give more credit to industry experience because there are previous use cases that they can leverage. There are industries that are still formulating standards when it comes to IoT and they will be more open to evaluating vendors that have a successful solution for their requirement – irrespective of the industry.

The Healthcare Industry Example

Ecosystm Principal Analyst, Sash Mukherjee says, “In today’s fast-evolving technology market, it is important to go beyond use cases in only your industries and look for vendors that have a demonstrated history of innovation and experience in delivering measurable results, irrespective of the industry.” Mukherjee takes the example of the Healthcare industry. “No one vendor can provide the entire gamut of functionalities required for patient lifecycle management.  In spite of recent trends of multi-capability vendors, hospitals need multiple vendors for the hospital information systems (HIS), ERP, HR systems, document management systems, auxiliary department systems and so on. For some areas such as electronic health records (EHR) systems, obviously industry expertise is paramount. However, if healthcare organisations continue to look for industry expertise and partner with the same vendors, they miss out on important learnings from other industries.”

Talking about industries that have influenced and will influence the Healthcare industry in the very near future, Mukherjee says, “Healthcare providers have learnt a lot from the Manufacturing industry – and several organisations have evaluated and implemented Lean Healthcare and Six Sigma to improve clinical outcomes. The industry has also learnt from the Retail and Hospitality industries on how to be customer focused. In the Top 5 Healthtech trends for 2020, I had pointed out the similarities between the Financial and Healthcare industries (stringent regulations, process-based legacy systems and so on). As the Healthcare industry focuses on value-based outcomes, governments introduce more regulations around accountability and transparency, and people expect the experience that they get out of their retail interactions, Healthtech start-ups will become as mainstream as Fintech start-ups.”

 

It is time for tech buyers to re-evaluate whether they are restricting themselves by looking at industry use cases, especially for emerging technologies. While less industry customisations mean easier deployments, it may also hamper innovation.

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AI Driving Tech Adoption

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In our blog, Artificial Intelligence – Hype vs Reality, published last month we explored why the buzz around AI and machine learning have got senior management excited about future possibilities of what technology can do for their business. AI – starting with automation – is being evaluated by organisations across industries. Several functions within an organisation can leverage AI and the technology is set to become part of enterprise solutions in the next few years. AI is fast becoming the tool which empowers business leaders to transform their organisations. However, it also requires a rethink on data integration and analysis, and the use of the intelligence generated. For a successful AI implementation, an organisation will have to leverage other enabling technologies.

Technologies Enabling AI

IoT

Organisations have been evaluating IoT – especially for Industry 4.0 – for the better part of the last decade. Many organisations, however, have found IoT implementations daunting for various reasons – concerns around security, technology integration challenges, customisation to meet organisational and system requirements and so on. As the hype around what AI can do for the organisation increases, they are being forced to re-look at their IoT investments. AI algorithms derive intelligence from real-time data collected from sensors, remote inputs, connected things, and other sources. No surprise then that IoT Sensor Analytics is the AI solution that is seeing most uptake (Figure 1).Adoption of AI Solutions

This is especially true for asset and logistics-driven industries such as Resource & Primary, Energy & Utilities, Manufacturing and Retail. Of the AI solutions, the biggest growth in 2020 will also come from IoT Analytics – with Healthcare and Transportation ramping up their IoT spend. And industries will also look at different ways they can leverage the IoT data for operational efficiency and improved customer experience (CX). For instance, in Transportation, AI can use IoT sensor data from a fleet to help improve time, cost and fuel efficiency – suggesting less congested routes with minimal stops through GPS systems, maintaining speeds with automated speed limiters – and also in predictive fleet maintenance.

IoT sensors are already creating – and will continue to create large amounts of data. As organisations look to AI-enabled IoT devices, there will be a shift from one-way transactions (i.e. collecting and analysing data) to bi-directional transactions (i.e. sensing and responding). Eventually, IoT as a separate technology will cease to exist and will become subsumed by AI.

Cloud

AI is changing the way organisations need to store, process and analyse the data to derive useful insights and decision-making practices. This is pushing the adoption of cloud, even in the most conservative organisations. Cloud is no longer only required for infrastructure and back-up – but actually improving business processes, by enabling real-time data and systems access.

Over the next decades, IoT devices will grow exponentially. Today, data is already going into the cloud and data centres on a real-time basis from sensors and automated devices. However, as these devices become bi-directional, decisions will need to be made in real-time as well. This has required cloud environments to evolve as the current cloud environments are unable to support this. Edge Computing will be essential in this intelligent and automated world. Tech vendors are building on their edge solutions and tech buyers are increasingly getting interested in the Edge allowing better decision-making through machine learning and AI. Not only will AI drive cloud adoption, but it will also drive cloud providers to evolve their offerings.

The global Ecosystm AI study finds that four of the top five vendors that organisations are using for their AI solutions (across data mining, computer vision, speech recognition and synthesis, and automation solutions) today, are also leading cloud platform providers (Figure 2).Top Vendors Implementing AI Solutions

The fact that intelligent solutions are often composed of multiple AI algorithms gives the major cloud platforms an edge – if they reside on the same cloud environment, they are more likely to work seamlessly and without much integration or security issues. Cloud platform providers are also working hard on their AI capabilities.

Cybersecurity & AI

The technology area that is getting impacted by AI most is arguably Cybersecurity. Security Teams are both struggling with cybersecurity initiatives as a result of AI projects – and at the same time are being empowered by AI to provide more secure solutions for their organisations.

The global Ecosystm Cybersecurity study finds that one of the key drivers that is forcing Security Teams to keep an eye on their cybersecurity measures is the organisations’ needs to handle security requirements for their Digital Transformation (DX) projects involving AI and IoT deployments (Figure 3).Drivers of Continued Focus on Cybersecurity

While AI deployments keep challenging Security Teams, AI is also helping cybersecurity professionals. Many businesses and industries are increasingly leveraging AI in their Security Operations (SecOps) solutions. AI analyses the inflow and outflow of data in a system and analyses threats based on the learnings. The trained AI systems and algorithms help businesses to curate and fight thousands of daily breaches, unsafe codes and enable proactive security and quick incident response. As organisations focus their attention on Data Security, SecOps & Incident Response and Threat Analysis & Intelligence, they will evaluate solutions with embedded AI.

AI and the Experience Economy

AI has an immense role to play in improving CX and employee experience (EX) by giving access to real-time data and bringing better decision-making capabilities.

Enterprise mobility was a key area of focus when smartphones were introduced to the modern workplace. Since then enterprise mobility has evolved as business-as-usual for IT Teams. However, with the introduction of AI, organisations are being forced to re-evaluate and revamp their enterprise mobility solutions. As an example, it has made mobile app testing easier for tech teams. Mobile automation will help automate testing of a mobile app – across operating systems (Figure 4).  While more organisations tend to outsource their app development functions today, mobile automation reduces the testing time cycle, allowing faster app deployments – both for internal apps (increasing employee productivity and agility) and for consumer apps (improving CX).Adoption of AI for Mobile Automation

CX Teams within organisations are especially evaluating AI technologies. Visual and voice engagement technologies such as NLP, virtual assistants and chatbots enable efficient services, real-time delivery and better customer engagement. AI also allows organisations to offer personalised services to customers providing spot offers, self-service solutions and custom recommendations. Customer centres are re-evaluating their solutions to incorporate more AI-based solutions (Figure 5).

 

The buzz around AI is forcing tech teams to evaluate how AI can be leveraged in their enterprise solutions and at enabling technologies that will make AI adoption seamless. Has your organisation started re-evaluating other tech areas because of your AI requirements? Let us know in the comments below.

 


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Technology Enabling Transformation in the Oil and Gas Industry

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The Oil and Gas industry has seen volatile times and is affected by its own set of unique challenges ranging from commodity price fluctuations, a potential supply crunch, geo-political events, and energy policies including energy transition. Moreover, the challenges and requirements are distinct at different stages of operations – upstream, midstream and downstream. The industry has been an early adopter of a few emerging technologies and is looking to leverage them to remain competitive and better employee management.

 

Drivers of Transformation in the Oil and Gas Industry

Remaining competitive in an evolving market

Oil and Gas companies are having to clean up old processes, as the market gets increasingly competitive. Ecosystm research finds that the top business priorities for Oil and Gas companies do not stop at cost reduction and revenue growth. The industry also has to focus on employee experience and safety, compliance, and increasingly even customer experience. And they must remain competitive through potential disruption in supply, demand and production; the rising costs of processes; and ongoing exploration costs. Oil and Gas companies are also focusing more on their downstream operations including retail in order to remain competitive.

Shortage of skilled workforce

The industry also faces the challenge of skills shortage. A survey conducted by the Global Energy Talent Index (GETI) found that nearly 70% of Oil and Gas professionals think the industry is already facing skills shortage or will be hit by it within the next 5 years. This is due to a number of reasons, including a reluctance of younger professionals to commit to a profession that has harsher conditions than many. Moreover, as energy transition becomes a topic of global discussion, many have a perception that the industry is not sustainable in the future. The industry also goes through cycles where they cut back on exploration and production, which results in the loss of skills and inadequate knowledge transfer. It has a long-term challenge around knowledge management.

Safety and environmental regulations

The industry  has to contend with green energy movements and environmental regulations.  There are several country-level regulations around air and water quality. Most Oil and Gas companies have cross-border operations and have to comply with a number of regulations on harmful emissions, greenhouse gases and offshore activities, in several countries. Increasingly, all leading Oil and Gas companies have to work in alignment with the Paris Agreement when developing solutions across functions – exploration, extraction and supply chain. There are also worker safety regulations and standards that they have to comply with.

The global Ecosystm AI study reveals the top priorities for Oil and Gas companies that are focused on adopting emerging technologies (Figure 1). It is very clear that the key areas of focus are process automation, asset and supply chain management and compliance.

 

Technology as an Enabler of Oil and Gas Transformation

Several emerging technologies are being used by the Oil and Gas industry as they continue their struggle to remain competitive across the different stages of operations – upstream, midstream and downstream.

IIoT

As the costs of sensors go down, connectivity widens and computing power increases, the industry is seeing greater uptake of Industrial IoT (IIoT) solutions. From wearables (to monitor employee safety) to drones with smart cameras (for remote inspections, environmental monitoring), IoT solutions have an immense role to play in the Oil and Gas industry. The industry has had to be cautious about the choice of devices, however, due to pervasive inflammable hydrocarbons and the related regulations.

Not only are they implementing sensors, Ecosystm research finds that 30% of Oil and Gas companies are also leveraging the IoT sensor data for analytics and intelligence. A common application is in predictive maintenance. Two years ago, Chevron launched predictive maintenance solutions in its oil fields and refineries. While the pilot ran on heat exchangers,  the company aims to connect all assets by 2024 and expects to save millions on asset management.

AI

AI and machine learning have applications across Oil and Gas operations, leveraging  IoT sensor data. “Smart fields” where production is monitored centrally, has a high level of automated controls. AI/Analytics is allowing companies to run simulations, use predictive data models and identify patterns to gauge risks associated with new projects. This has an impact on production, exploration and making efficient use of existing infrastructure. Oilfield services company Baker Hughes has worked on an AI-based application that allows well operators to view real-time production data and predict future production with more accuracy.

AI is also helping organisations monitor environmental risk and has the potential to help Oil and Gas companies with their compliance requirements. Gazprom Neft, one of the largest suppliers of natural gas to Europe and Seismotech are exploring using AI for seismic data processing, for solutions that are specific to the needs of the industry.

While the applications of AI in the industry are often focused on upstream activities, AI has applications across all operations. In the midstream, transporting crude oil to refineries has always had its unique challenges.  Since transport lead times are long and prices fluctuate based on the availability of products, organisations benefit from demand forecasting and price risk modelling. While the common perception of the industry does not include customer interactions, the truth is that the industry is increasingly focusing on the retail space. The need is enough for Shell to begin experimenting with virtual assistants as far back as in 2015, to interact with their retail customers. In fact, the company anticipates a higher adoption of AI in the industry and is collaborating with Udacity to bridge the skills gap.

Technologies empowering employees

As discussed earlier, one of the key challenges of the industry is the inability to manage a reliable knowledge management system that can help consistent knowledge and skills transfer. A single source of truth that can be accessed by all employees on processes, including safety requirements has an immense role to play to help with the skills shortage in the industry.

Enterprise mobility is another tech area that holds immense potential for the industry, with its huge proportion of mobile workers, many in remote locations. Mobility solutions can help in productivity, process optimisation and monitoring of health and safety of the employees and are increasingly incorporating wearables and location-based services.  GIS and GPS systems are helping employees with accurate directions, easier access to drilling locations and more. Given the number of devices, platforms and OSs, the industry is seeing an increased interest in unified enterprise mobility (UEM) solutions. Ecosystm finds that more than a third of Oil and Gas companies have implemented or are evaluating UEM, while another 20% are expressing early interests.

Blockchain

The sheer quantity of documents, transaction records and contracts that a typical Oil and Gas company has to manage – including cross-border transactions – poses some difficulty for the industry. The companies have to reconcile and handle issues involving multiple contractors, sub-contractors, and suppliers. Supply chain and inventory management is also a challenge. With the adoption of Blockchain, the industry can automate the management of purchase orders, change orders, receipts, and other trade-related documentation, as well as inventory data with more efficiency and transparency. Blockchain is enabling a seamless supply chain, improved project management and simplifying contractual obligations at each point along the way. Gazprom Neft’s aviation refuelling business is an early adopter of Blockchain-based smart contracts. All refuelling operations are undertaken exclusively on the basis of digital contracts approved by both parties near real-time and eliminates the possibility of any breach of contract and makes the accounting process more transparent.

 

As the market continues to be volatile for Oil and Gas companies and uncertainties loom in the future, the industry will increasingly depend on technology to remain competitive.

 


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Selecting the Right Vendor for your Tech Investments

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With the advancements in the technology landscape, the CIO’s role has become increasingly complex. One of the key challenges they face is in emerging and newer technology implementations, which require them to identify and partner with newer tech vendors. The common challenges that tech buyers face today include:

  • The emergence of newer technologies that are catching the fancy of the C-suite and they are expected to adopt and deliver
  • Getting management buy-in for IT investments (increasingly including discussions on ROI)
  • Need to involve business stakeholders in tech decision-making
  • Lack of sufficiently skilled internal IT
  • Engagement with multiple tech vendors (including newer vendors that they have to establish a relationship with)
  • Digital transformation projects that might require an overhaul (or at least a re-think) of IT systems
  • Backdrop of compliance and risk management mandates

Many of these challenges will require the sourcing of new technology or a new tech partner and rethinking their vendor selection criteria. And selecting a tech vendor can be hard. The mere fact that there is an industry whose sole purpose is to help businesses select tech vendors goes to show the massive gap between what these providers sell and what businesses want. If there was easy alignment, the Tech Sourcing professionals and businesses would not have existed.

But over my time working with Tech Sourcing professionals, CIOs and business leaders, I have picked up on a few key factors that you should incorporate in your vendor selection process best practices. First and foremost, you are looking for a partner – someone who will be with you through the good and bad. Someone whose skills, products, services – and most importantly – culture, match your business and its needs.

I believe that the technology ecosystem is not really as competitive as we think. Yes, in practice Google competes with Microsoft in the office productivity space. But I often hear about companies moving from one to the other not for features, function or even price – but for a cultural match. Some traditional businesses were hoping Google can help them become more innovative, but in reality, their business culture smothered Google and meant they could not benefit from the difference in the ways of working. And I am not suggesting Microsoft is not innovative – more that Office represents the traditional ways of working – and perhaps can help a business take a more stepwise approach to change its own culture.

And I regularly hear about IT services deals (managed services, systems integration, consulting etc) going to the company that made the most sense from a cultural fit – where they were willing to take on the culture of their customer and embrace that way of working. In fact, I have been brought into many deals where a company hired a strategic consultant to create a new digital strategy or AI strategy, only to receive a document that is unworkable in their business and their culture.

So, I believe every strategic technology relationship should start and end with a cultural match. This company is a partner – not just a provider. How do you determine if they are a partner and measure cultural match? Well, that is the topic of an upcoming report of mine, so watch this space!

 

Questions You Should Ask Before Stepping in the Ring

There are also a number of questions that you should ask along with the partnership discussion:

  • How will this solution change the organisation?
  • What are the risks either way (of implementing or not implementing the solution)?
  • Does the solution solve a key business problem?
  • Is it likely to have more impact than the solution it is replacing?
  • Where will the funding for the implementation come from?
  • Have you calculated the ROI and the time to deployment?
  • Have you baselined the current scenario so that you can measure improvement?

These can inform you of the business impact of the solution – and what you need to do to prepare for successful implementation (if you plan for success, you are more likely to be able to get faster benefits than if you do not plan for the change!)

 

Engagement Criteria for Your Shortlisting Process

In order to determine vendor selection process best practices, Ecosystm research tries to unearth the top criteria that organisations employ when shortlisting the vendors that they want to engage, across multiple technologies.

There is still a skills gap in internal IT and organisations want technical guidance from their Cloud and IoT vendors. With the plethora of options available in these tech areas, CIOs and IT teams also tend to look at the brand reputation when engaging with the vendor. Very often, organisations looking to migrate their on-prem solutions on the cloud engage with existing infrastructure providers or systems integrators for guidance, and existing relationships are significant. IoT solutions tend to be very industry-specific and a portfolio of specific industry use cases (actual deployments – not proofs of concept) can be impactful when selecting a vendor for planned deployments.

Artificial intelligence (AI) deployments are often linked with digital transformation (DX). Organisations look for a vendor that can understand the organisational strategy and customise the AI solutions to help the organisation achieve its goal. Adoption of AI is still at a nascent stage globally across all industries. Many organisations do not have the right skills, such as data scientists, yet. They appreciate that integration with internal systems will be key to reap the full benefits of the solutions, especially if the entire organisation has to benefit from the deployments. They also anticipate that they would have to have a continuous period of engagement with their vendors, right from identifying the right data set, data cleaning to the right algorithms that keep learning. Organisations will look at vendor partners who are known for delivering better customer experience.

This is true for cybersecurity solutions as well, as organisations are driven to continue their investments to adhere to the internal risk management requirements. Given how fragmented the cybersecurity landscape has become, organisations will also wish to engage with vendors that have an end-to-end offering, especially a managed security service provider (MSSP). Cybersecurity vendors are increasingly strengthening their partner ecosystem so that they can provide their client with the single-point-of-contact that they want.

Of the technologies mentioned in the figure, mobility is arguably the most mature. As organisations revisit their enterprise mobility solution as they go increasingly ‘Mobile First’, their requirements from their mobility vendors are more specific. They have decided over the years which OSs they want to support their enterprise applications and are looking for vendors with robust cloud offerings.

The vendor selection criteria will likely be different for each technology area. And as your knowledge and understanding of the technology increases, you should be able to drill the requirements down to the solution level, while making sure you engage with a vendor with the right culture.

 

Tim Sheedy’s upcoming report, ‘Best Practices for Vendor Evaluation and Selection’ is due to be published in February 2020.

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Innovation in the Workplace Soon to be Pervasive

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The adoption of new digital and data-centric technologies is transforming the workplace and making it more productive. The concept of the workplace has evolved over time, and it is no longer tied to the tradition of working from a fixed physical location. Rather, the workplace has expanded its horizon and has evolved into a wider virtual environment empowered by technologies such as smartphones, wireless connectivity, virtual and augmented reality, collaboration tools and a range of productivity technologies.

Innovation has continued to revolutionise the workplace. It has been 40 years since digital technology transformed the back offices of large organisations; 30 years since the PC revolution revolutionised the front office with productivity tools such as word processors and spreadsheets for all information workers; just 20 years since the Internet became a common business tool and; the smartphone, particularly the iPhone made its way into the workplace.

Each of these waves of technology contributed towards workplace transformation and has made way for the new wave of transformation – through emerging technologies such as Artificial Intelligence (AI) and newer business models (as-a-service and cloud-based delivery of personal productivity tools).

Organisations are being driven towards a “Mobile First” strategy to empower their “Smart employees” – no longer thinking of migrating their web apps to mobile apps, as and when required. They are looking to implement and develop mobile apps first. In the global Ecosystm Mobility study, only about 2% of organisations indicate the absence of a Mobile-First strategy and this is a good indication of the transformation that lies ahead.

Adoption-of-Mobile-First-Strategy-Vision

 

To be able to implement a Mobile-First vision, become a Smart Workplace and for a seamlessly integrated environment, organisations will need to invest in multiple technologies simultaneously.  These include:

  • Collaboration tools: Software and tools that help individuals in the workplace to collaborate and work together on a project in a smart and efficient way with shared data and resources – irrespective of their locations. Although the concept of collaboration is not new, technologies such as AI and Cloud allow for greater collaboration. This has driven leading players in the market to also offer Cloud solutions. Microsoft is a good example, where Cloud brought added features and services to their MS Office suite to match the requirements of an evolving workplace.
  • Social media: A technology that was popularized in the consumer space evolved into a major collaboration and productivity technology for enterprises. This opens up the possibility of incorporating sophisticated analysis tools, many of them driven by AI technology, leveraging social networks. Using social media in the workplace has also improved employee experience, as it enables the employees to interact in similarly efficient ways in the workplace, as they do in their personal lives.
  • Workflow and content management: Digitalisation is opening newer avenues, simplifying the way work gets done and exploring ways to improve existing processes and workflows. Workflow and content management systems have improved the way employees produce and manage business information thus making processes more efficient, cost-effective, and secure.
  • Mobility: The advent of smartphones, wireless networking, and mobile applications have enabled employees to work from any place and any time. This has expanded the workplace boundaries and employees can stay connected with the work while on the move.
  • Unified Communications: There are multiple channels of communication – voice, data, image, video – open to employees today, depending on the level of communication required to perform their jobs. Organisations are increasingly implementing one integrated corporate communication system.

 

Workplace innovation is already pervasive in customer focussed industries. However, workplace innovation is also combining with other emerging technologies such as AI and IoT to transform workplaces in supply-chain intensive industries as diverse as Manufacturing, Transport & Logistics, Energy & Utilities, and Mining & Resources.  As this trend continues, we will start to see even more innovations to our places of work.

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