Communications

The Latest

28 June 2022: Messaging program app Slack, will launch GovSlack in July 2022 for public sector customers. Salesforce, its parent company, secured the app’s security and operational certifications from the Federal Risk and Authorization Management Program (FedRAMP), Department of Defense Impact Level 4 (DoD IL 4), and the International Traffic in Arms Regulations (ITAR). GovSlack will be released as a complementary tool with Salesforce’s Government Cloud Plus, a dedicated instance for U.S. government customers.

Why it’s Important

Slack joins a long list of FedRAMP-certified vendors such as Google, Oracle, Cisco, Nintex, and MongoDB, that have met the stringent security standards of the U.S. government. Salesforce’s approach to offering complementary government-compliant products is strategically similar to what is provided by DocuSign, Microsoft, IBM and Snowflake, to ensure consistency in cyber security of Cloud service.

Since the majority of government agencies deal with sensitive data, meeting major public office standards and regulations can bolster a Cloud service provider’s (CSP) reputation in the industry, and expand their market to federal agencies, state and local public offices, and government-affiliated agencies. Furthermore, vendors need to expand their compliance to other countries standards such as the hosting certification framework provided by the Australian Government Digital Transformation Agency, which certifies service providers, Cloud services, and data centre facilities.

Who’s Impacted

  • CEO
  • Procurement teams
  • IT teams

What’s Next?

When considering Cloud management tools, security certifications and assessments are a sign that the vendor has best practices in place, but are not a panacea for mitigating risk. Treat them accordingly. 

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The Latest

24 May 2022: ActiveCampaign has acquired email delivery service Postmark and email authentication DMARC Digests to improve its sales and marketing communications features. With the integration of Postmark, ActiveCampaign users can send transactional emails through a drag-and-drop tool to engage more non-technical users. On the other hand, with the DMARC Digests feature, users can easily identify sources that are sending unauthenticated emails that result in DMARC failures. 

Why it’s Important

Email marketing tools are evolving rapidly, with platform features that support greater usability. In addition, allowing recipients to reply to transactional emails, such as Postmark’s feature, can help improve recipients’ engagement with the organisation.  

Similar to other Cloud analytics vendors, IBRS expects more mergers and acquisitions among customer experience automation firms. It projects more features using no-code technology to be integrated for a streamlined email building process. This will help marketers and non-developer teams to create, maintain and analyse their marketing campaigns while simplifying their workflows.

However, these drivers also mean that more email automation is on the way. In turn, this means more scrutiny of email quality, trust and delivery.

Who’s impacted

  • CMO
  • Sales and marketing teams

What’s Next?

Organisations should look at how their digital marketing can improve customer engagement. No-code/low-code platforms help cut down the time to build campaigns and also create better analysis of marketing initiatives. However, they must not only leverage new technologies and integrations that optimise each customer’s touchpoint, but also consider compliance regulations, customer analytics and engagement to accelerate return on investment (ROI) in lead conversion.

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The Latest

10 May 2022: Microsoft Research has introduced an advanced prototype of PeopleLens for young learners with visual impairment at the University of Bristol. 

The solution uses augmented reality eyeglasses tethered to a mobile device to identify people and track their direction and distance from the user. Using artificial intelligence (AI), the solution registers people in the system through facial recognition and alerts the wearer in real-time by identifying the person and their distance and direction through spatialised audio. To protect privacy, facial images in the system are not stored as photographs but as vector numbers to represent identities. The technology is not yet commercially available, but does provide hints at what the near future will

Why it’s Important

Education is something of a laggard in the application of AI, especially in Western economies. 

However, innovations such as PeopleLens provide a glimpse (pun intended) of what is possible. Using AI in education is expected to grow quickly, but where and how it will be applied is as much a matter of economics as it is technology. 

The cost of AI at scale can be a prominent issue in this case. AI computation may be inexpensive in cases where requests are relatively small, but costs can quickly add up for applications that require millions or even billions of transactions. In addition, releasing new AI algorithms is still relatively expensive, due to the high cost of investment in research and design, as well as expenditures for the development of prototypes, complementary equipment and software. Hyperscale Cloud computing helps reduce these initial expenditures, but training is still required. 

Therefore, the business cases for an AI initiative must be carefully weighed against the potential future scale versus the value to individuals. In short, does it scale economically?

In a recent IBRS interview with an Australian Microsoft Azure specialist who developed an AI model to detect improper Microsoft Teams usage among students - such as cyberbullying, aberrant behaviour and inappropriate content sharing platforms - the transactional cost was not feasible, even with the aggregate value of securing children from harassment online. Since the Teams environment hosted hundreds-of-thousands of users, each producing scores if not hundreds of messages daily, the total cost of running the solution was not a viable commercial option.

In the case of PeopleLens, on the other hand, the number of transactions per individual may be relatively high, but the number of transactions as an aggregate is relatively low. As such, it is potentially an example of where the value returned is acceptable when compared against the cost. 

Who’s impacted

  • CEO
  • Innovation managers
  • Education policy strategists
  • AI solution development teams
  • Product research teams

What’s Next?

Industries that are planning to leverage AI effectively and at scale should ask for examples of how different AI-powered solutions are being justified.  

For most organisations, AI will be leveraged as features from within SaaS solutions, such as SalesForce's Einstein and Microsoft's use of GPT3 inside the PowerPlatform. 

However, for those looking to create new applications that leverage Cloud and ML capabilities, transactional volume should be carefully considered early in the planning stage to accrue the most value from the investments in research, design, development and production in the long run.

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The Latest

10 May 2022: Microsoft has integrated the Z-code Mixture of Experts (MoE) models to Translator and other Azure AI services to improve the quality and accuracy of its translation capabilities. Through the Z-code MoE, the models can speed up language translations on Microsoft Word, PowerPoint and PDF files. 107 languages are currently supported. 

Why it’s Important

Pretrained ML models now produce faster translations with consistency and help human translators reduce their workload, especially for repetitive writing and translation tasks. IBRS has observed that hyperscale machine translation has already progressed in terms of computational efficiency. Capabilities such as Z-code save runtime costs by using parameters that are only relevant for specific translation tasks.

However, to match (or sometimes surpass) the quality of human translators, genre-specific translation engines trained specifically on different types of content must be employed. The generic models offered by the hyperscale Cloud vendors are often insufficient. 

Genre-specific machine translation engines involve training highly nuanced models. Solutions such as those from Omniscien Technologies, for instance, provide far more accurate models that can be curated. In addition, these specialised models also allow for the translations to run on an organisation's own infrastructure, which is a consideration for organisations that need to translate sensitive or private content without digressing from the context of the original text.

Who’s impacted

  • CEO
  • Corporate communications teams

What’s Next?

Machine translation services will eventually make their way into the daily life of most people, much like how global positioning systems (GPS) have been integrated into mobile devices. 

Currently, free machine translation tools such as Google Translate and Bing Translator are not nuanced and far less accurate when compared to the output of human translators. Translation apps such as SayHi, allow speech-to-text translation in real-time while Papago and Waygo feature image recognition that automatically translates text on pages, signs and screen. However, these still cannot produce highly accurate translations based on context and language registers.

As such, translation at a basic level (word-for-word, literal) is not good enough for all use cases. For example, translating medical information, patents, user manuals or outputs for e-discovery requests requires a much higher fidelity of translation that must include referential, cohesive and natural-sounding output. For these cases, consider specialised machine translation solutions alongside (and possibly complementing) the more general offerings from the hyperscale Cloud vendors.

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The Latest

16 August 2021: Zoom is best known for its video conferencing solution, which set new standards for ease of use and quick adoption, which in turn saw its usage skyrocket during the first months of COVID-19 lockdowns. The firm’s brand is now so ingrained that staff often refer to video conferencing as ‘zoom calls’ and the public use the terms ‘zooming’ and ‘zoom me’, even when Zoom may not be technology in use. Unfortunately for Zoom, its strong brand recognition with video calls often obscured the breadth of its unified communications (UC) ecosystem.

Zoom is attempting to reposition its brand as an end-to-end UC platform. The topics for its planned Zoomtopia summit, scheduled for the 14th of September, are clear indicators of where Zoom will focus its efforts in the coming year: 

  • Public sector
  • Education
  • Healthcare
  • Financial services

IBRS recent interviews as part of the Cloud economic study found these four sectors have all been particularly impacted by COVID-19 in terms of service delivery volume and increasing expectations on multichannel (if not omnichannel) experiences. So Zoom’s targeting makes sense. 

Why it’s Important.

The requirements for UC are shifting from internal standardisation (cost optimisation, ensuring staff can communicate efficiently and switch between communications modes) to external flexibility (delivering services using end-points that the public have on hand). It is for this reason that both Microsoft Teams and Zoom are finding their way into call centre strategies. It is not just that these video communications technologies fit within a larger communications ecosystem, but that the majority of the public are familiar with the services and likely have clients already installed on their devices. The mature wave of UC, which IBRS introduced 14 years ago, is moving from the trailblazers into the mainstream.

Who’s impacted

  • User experience / customer journey teams
  • Development team leads
  • Customer service teams
  • Call centre teams

What’s Next?

There two key triggers for replatforming an organisation’s UC environment, or at least introducing a new UC platform:

  • An overhaul of call centres, possibly in conjunction with CRM modernisation.
  • Replacement of legacy PBX or VoiP solution

 

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  1. Unified Communications: the future is full of MUC
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