Despite its potential for relieving pressure on the workforce, automation in the workplace is often seen negatively, as a cause of job losses or a growing skills gap. Yet, done well, automation can provide critical support that frees people up to focus on more impactful work — and can lead to happier, more motivated and productive employees.

At a time when burnout has become a major issue — with Future Forum data showing 40% of workers globally experience it — automation can also help employees by simplifying work and saving them time.

So, how can IT leaders help reduce the cognitive load and automate common tasks such as creating sales decks using Salesforce data or raising purchase order requests? One way is through the digital headquarters (HQ).

Making automation a reality with the digital HQ

The key to effective workplace automation is keeping it simple and empowering end users. If a system is too complicated to set-up it becomes a burden on the tech team and is not scalable.

With most businesses still navigating the shift to hybrid, the one office that every employee comes into each day is the digital HQ — a single digital space where workflows between your people, systems, partners and customers. In transforming how teams work, communicate and collaborate, the digital HQ sits at the heart of automation initiatives, with free-flowing conversations built around specific projects or teams taking place in channels.

Heading into a tough economic climate, it’s more important than ever for organisations to keep teams motivated and engaged, so they are able to perform and deliver results quickly. Automation within the digital HQ is a major step towards this — empowering employees to liberate their time from manual tasks and helping them breeze through multiple requests that might otherwise perforate their day.   

Offering a no-code solution that everyone can use, Slack’s Workflow Builder hands control back to the team, boosting efficiency in the process. Just ask telecommunications giant Verizon, who used Slack’s digital HQ — alongside automations — to improve output and employee experience.


Personalised problem-solving

Verizon’s Planning and Engineering team were the first to identify the potential of Slack’s Workflow Builder to bring solutions to, not just their own department, but the whole company. This is because Workflow Builder is an easy-to-use tool that requires no coding experience, with over 400,000 people around the world having built workflows so far — 80% of whom are in non-IT roles. It was therefore easy for Verizon to see its potential to give teams autonomy in solving their own pain points.

Verizon launched the Citizen Builder Programme, encouraging staff to leverage automated workflows to create solutions. This level of personalised problem-solving meant issues were resolved with far greater precision than if another team had been tasked with the job. With one impactful example being how Verizon’s Wireline Network Operations team used Slack’s Workflow Builder to coordinate field technicians for last-mile service calls. Automating parts of this process not only reduced the load on the team but also led to more accurate customer appointment times — all without adding any additional pressure to Verizon’s IT team.

With an expansive telecommunications operation, and a reputation for excellent customer service, Verizon faces a huge amount of admin every day. But with Slack’s Workflow Builder, they have ensured it doesn’t take its toll on workforce motivation, and satisfaction isn’t reserved exclusively for its customers.

For more information on how Slack’s Digital HQ can help your business click here.

Application Performance Management, Change Management, Networking, Remote Work

By Saket Srivastava, Chief Information Officer at Asana

There has never been a better time to be a CIO. The pandemic has evolved how we regard the IT organization within businesses, in no small part due to the extensive role it played in keeping teams connected and able to perform during a more disconnected time than ever. No longer is the tech function conceived of as a back-office team — we are leading the charge in how the workplace adapts.

The year ahead will bring new and continuing challenges for all businesses. Organizations are once again turning to CIOs to bring about digital transformation that drives productivity, agility, and growth for the future. With two decades of experience working in technology, I’m no stranger to leading through uncertain times. With this in mind, I’ve created a survival guide for CIOs — with five key tips to help tech leaders navigate the year ahead while improving customer and employee experiences alike.

Make hyper prioritization a growth opportunity: While many organizations are faced with challenging economic conditions and resource constraints, CIOs have an exciting chance to turn these factors into new growth opportunities. Start by identifying and prioritizing which investments will have the biggest impact on your organization both in the short and long-term, enabling your teams not to spread themselves too thin focusing on less critical goals. Market constraints mean the opportunity to focus and double down on work that matters most.Scale up security investments: The move to a more distributed workforce has reset the level of flexibility employees have. However, it has also created security challenges — with more access points and sensitive information available to share and download on personal and corporate devices. Enhanced cybersecurity practices should be a priority for any CIO as they look to balance work between corporate and home offices. Additionally, make sure that your cloud technology tools use security industry best practices when it comes to how data is transmitted, stored, and processed. Internally, it’s vital for everyone to be aware of the dangers around sharing sensitive information — organizations should invest in robust security training to ensure company data isn’t compromised.Automate ongoing, low-skill tasks: Companies must increasingly focus on getting the most out of the investments they make in AI, tech, and data to optimize ongoing operational efficiencies. Automation is a sound investment to make, especially when it can free up employees to focus on high-impact work, optimize resources, and drive productivity. A few ways to get started are automating workflows through a work management platform to save employee time, reduce the need for status updates, and evolve from clunky spreadsheets and never-ending email chains; utilizing advanced data science models to understand customer pain points; and assessing the value your organization might gain from incorporating chatbots to power support teams. Tune in to customers: One of the single best investments that an organization can make in the coming year is ensuring that employees have the tools to be engaged, efficient, and productive. When teams can focus on work that drives meaningful results, it ultimately trickles down to improved customer experiences and outcomes. In the coming year, having a good read on customer needs will be crucial as many organizations battle resource constraints, challenging economic conditions, and continuing uncertainty when it comes to planning. Optimize distributed workforces: Today’s enterprise organizations rely on distributed teams, and it is important to ensure that employees collaborate effectively across time zones, geographies, and departments. One of the biggest challenges to workplace efficiency is that employees are distracted, often switching between an average of nine apps a day. This makes it easy to miss critical messages and updates from teammates. For CIOs, there will be a greater need for work management platforms to update individuals across multiple channels, integrate more productivity-focused tools, and minimize redundant cross-functional work and errors. 

CIOs have a breadth of touchpoints across any business. By optimizing both employee and customer experiences, they have a golden opportunity to help reduce friction and increase productivity. This will prove pivotal in positioning organizations not just for the year ahead, but also for longer-term growth. It’s a tall order, but by focusing on the priorities above, CIOs can ensure their enterprise remains nimble, relevant, and able to pivot around whatever the future may hold.

To learn more, visit us here.

Saket Srivastava, Chief Information Officer at Asana


Digital Transformation, IT Leadership

In spite of long-term investments in such disciplines as agile, lean, and DevOps, many teams still encounter significant product challenges. In fact, one survey found teams in 92% of organizations are struggling with delivery inefficiency and a lack of visibility into the product lifecycle.[1] To take the next step in their evolutions, many teams are pursuing Value Stream Management (VSM). Through VSM, teams can establish the capabilities needed to better focus on customer value and optimize their ability to deliver that value.

While the benefits can be significant, there are a number of pitfalls that teams can encounter in their move to harness VSM. These obstacles can stymie progress, and erode the potential rewards that can be realized from a VSM initiative. In this post, I’ll take a look at four common pitfalls we see teams encounter, and provide some insights for avoiding these problems.

Pitfall #1: Missing the value

Very often, we see teams establish value streams that are doomed from inception. Why? Because they’re not centered on the right definition of value.

Too often, teams start with an incomplete or erroneous definition of value. For example, it is common to confuse new application capabilities with value. However, it may be that the features identified aren’t really wanted by customers. They may prefer fewer features, or even an experience in which their needs are addressed seamlessly, so they don’t even have to use the app. The key is to ensure you understand who the customer is and how they define value.

In defining value, teams need to identify the tangible, concrete outcomes that customers can realize. (It is important to note in this context, customers can be employees within the enterprise, as well as external audiences, such as customers and partners.) Benefits can include financial gains, such as improved sales or heightened profitability; enhanced or streamlined capabilities for meeting compliance and regulatory mandates; and improved competitive differentiation. When it comes to crystalizing and pursuing value, objectives and key results (OKRs) can be indispensable. OKRs can help teams gain improved visibility and alignment around value and the outcomes that need to be achieved.

Pitfall #2: Misidentifying value streams

Once teams have established a solid definition of value, it’s critical to gain a holistic perspective on all the people and teams that are needed to deliver that value. Too often, teams are too narrow in their value stream definitions.

Generally, value streams must include teams upstream from product and development, such as marketing and sales, as well as downstream, including support and professional services. The key here is that all value streams are built with customers at the center.



Pitfall #3: Focusing on the wrong metrics

While it’s a saying you hear a lot, it is absolutely true: what gets measured gets managed. That’s why it’s so critical to establish effective measurements. In order to do so, focus on these principles:

Prioritize customer value to ensure you’re investing in the right activities.Connect value to execution to ensure you’re building the right things.Align the execution of teams in order to ensure things are built right.

It is important to recognize that data is a foundational element to getting all these efforts right.

It is vital that this data is a natural outcome of value streams — not a separate initiative. Too often, teams spend massive amounts of money and time in aggregating data from disparate resources, and manually cobbling together data in spreadsheets and slides. Further, these manual efforts mean different teams end up looking at different data and findings are out of date. By contrast, when data is generated as a natural output of ongoing work, everyone can be working from current data, and even more importantly, everyone will be working from the same data. This is essential in getting all VSM participants and stakeholders on the same page.

Pitfall #4: Missing the big picture

Often, teams start with too narrow of a scope for their value streams. In reality, these narrow efforts are typically really single-process, business process management (BPM) endeavors. By contrast, value streams represent an end-to-end system for the flow of value, from initial concepts through to the customer’s realization of value. While BPM can be considered a tactical improvement plan, VSM is a strategic improvement plan. Value streams need to be high-level, but defined in such a way that they have metrics that can be associated with them so progress can be objectively monitored.

Tips for navigating the four pitfalls

 Put your clients at the heart of your value streams and strategize around demonstrable and measurable business outcomes.

Value streams are often larger than we think. Have you remembered to include sales, HR, marketing, legal, customer service and professional services in your value stream?

Measure what matters and forget about the rest. We could spend our days elbow deep in measuring the stuff that just doesn’t help move the needle.

 Learn More

To learn more about these pitfalls, and get in-depth insights for architecting an optimized VSM approach in your organization, be sure to check out our webinar, “Four Pitfalls of Value Stream Management and How to Avoid Them.”

[1] Dimensional Research, sponsored by Broadcom, “Value Streams are Accelerating Digital Transformation: A Global Survey of Executives and IT Leaders,” October 2021

Devops, Software Development

From telecommunications networks to the manufacturing floor, through financial services to autonomous vehicles and beyond, computers are everywhere these days, generating a growing tsunami of data that needs to be captured, stored, processed, and analyzed.

At Red Hat, we see edge computing as an opportunity to extend the open hybrid cloud all the way to data sources and end users. Where data has traditionally lived in the datacenter or cloud, there are benefits and innovations that can be realized by processing the data these devices generate closer to where it is produced.

This is where edge computing comes in.

What is edge computing?

Edge computing is a distributed computing model in which data is captured, stored, processed, and analyzed at or near the physical location where it is created. By pushing computing out closer to these locations, users benefit from faster, more reliable services while companies benefit from the flexibility and scalability of hybrid cloud computing.

Edge computing vs. cloud computing

A cloud is an IT environment that abstracts, pools, and shares IT resources across a network. An edge is a computing location at the edge of a network, along with the hardware and software at those physical locations. Cloud computing is the act of running workloads within clouds, while edge computing is the act of running workloads on edge devices.

You can read more about cloud versus edge here.

4 benefits of edge computing

As the number of computing devices has grown, our networks simply haven’t kept pace with the demand, causing applications to be slower and/or more expensive to host centrally.

Pushing computing out to the edge helps reduce many of the issues and costs related to network latency and bandwidth, while also enabling new types of applications that were previously impractical or impossible. 

1.    Improve performance

When applications and data are hosted on centralized datacenters and accessed via the internet, speed and performance can suffer from slow network connections. By moving things out to the edge, network-related performance and availability issues are reduced, although not entirely eliminated.

2. Place applications where they make the most sense

By processing data closer to where it’s generated, insights can be gained more quickly and response times reduced drastically. This is particularly true for locations that may have intermittent connectivity, including geographically remote offices and on vehicles such as ships, trains, and airplanes.

3. Simplify meeting regulatory and compliance requirements

Different situations and locations often have different privacy, data residency, and localization requirements, which can be extremely complicated to manage through centralized data processing and storage, such as in datacenters or the cloud.

With edge computing, however, data can be collected, stored, processed, managed, and even scrubbed in-place, making it much easier to meet different locales’ regulatory and compliance requirements. For example, edge computing can be used to strip personally identifiable information (PII) or faces from video before being sent back to the datacenter.

4.    Enable AI/ML applications

Artificial intelligence and machine learning (AI/ML) are growing in importance and popularity since computers are often able to respond to rapidly changing situations much more quickly and accurately than humans.

But AI/ML applications often require processing, analyzing, and responding to enormous quantities of data which can’t reasonably be achieved with centralized processing due to network latency and bandwidth issues. Edge computing allows AI/ML applications to be deployed close to where data is collected so analytical results can be obtained in near real-time.

Red Hat’s approach to edge computing

Of course, the many benefits of edge computing come with some additional complexity in terms of scale, interoperability, and manageability.

Edge deployments often extend to a large number of locations that have minimal (or no) IT staff, or that vary in physical and environmental conditions. Edge stacks also often mix and match a combination of hardware and software elements from different vendors, and highly distributed edge architectures can become difficult to manage as infrastructure scales out to hundreds or even thousands of locations.

The Red Hat Edge portfolio addresses these challenges by helping organizations standardize on a modern hybrid cloud infrastructure, providing an interoperable, scalable and modern edge computing platform that combines the flexibility and extensibility of open source with the power of a rapidly growing partner ecosystem.

The Red Hat Edge portfolio includes:

Red Hat Enterprise Linux and Red Hat OpenShift, which are designed to be the common platform for all of an organization’s infrastructure from core datacenters out to edge environments.Red Hat Advanced Cluster Management for Kubernetes and Red Hat Ansible Automation Platform provide the management and automation platforms needed to drive visibility and consistency across the organization’s entire domain.Finally, the Red Hat Application Services portfolio provides critical integration for enterprise applications while also building a robust data pipeline.

The Red Hat Edge portfolio allows organizations to build and manage applications across hybrid, multi-cloud, and edge locations, increasing app innovation, speeding up deployment, and updating and improving overall DevSecOps efficiency.

To learn more, visit Red Hat here.

Edge Computing