4 Steps for Selling Intelligent Process Automation to the Masses

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Seasoned leaders know that, when beginning any significant project, there are two different paths that can be taken. Path number one offers the shortest route from point A to point B. This is to simply force-feed the project to everyone, essential saying, “We’re doing this and that’s that.” The second path, on the other, may be a little less direct and take a lot longer. On this journey, time is taken to explain the strategy and the reasoning behind it. In other words, saying, “Here’s what we’re doing and why.”

Which of these paths do you think will yield better results? If you chose the second path, chances are you’ve experienced both options before and know firsthand that getting people onboard with change is almost always the wiser choice. Few industries are as familiar with the correlation between major change and feelings of fear, skepticism, resistance and other challenges as leaders in the IT realm. Implementing intelligent process automation is no different.

What’s the best way to overcome the many uncertainties and misconceptions that could delay or derail your automation project? Let’s take a look.

Appeal to their self-interest.

Most people won’t get fully behind a project unless and until they know how it will directly impact their lives – essentially, they want to know what’s in it for them. Self-preservation is human nature. Appealing to this natural instinct can help make your argument much more persuasive. Instead of simply announcing that you will be introducing intelligent process automation into the mix, show them how that change will benefit them.

Will automating a particular workflow finally put an end to those middle-of-the-night phone calls? Will it allow some employees to eliminate low-skill, manual tasks from their workload, freeing them up to focus on more strategic and meaningful work? Will learning how to work alongside artificial intelligence enable ambitious team members to develop new marketable skills that they can use to further their career?

Figure out what’s in it for each of the individuals or teams you are presenting to, as well as how intelligent automation will ultimate benefit customers and the company as a whole, and then communicate that to the masses. Paint a picture of what’s currently causing issues and then demonstrate how automation can help. By the way – the same concept applies when making the case outside of the IT department, to non-technical stakeholders, for example. Just go easy on the jargon.

Connect your proposal to specific business goals.

A big part of making a strong and support-worthy case for anything, really, involves getting people to understand that you’re not simply chasing trends. In other words, you’re not just automating for the sake of automating. If people sense that’s the case, they’re going to lose confidence and likely provide even greater resistance – especially those who are directly impacted, such as the IT team.

The case for intelligent process automation must be driven by a specific business demand, whether it’s reducing expenses, improving service levels, gaining competitive advantage, etc. Unless it’s a core competency of the organization, no automation endeavor should be a means unto itself.

If you want people to back your plan, you need to align it with specific business goals and then clearly and accurately convey those connections. Lay out these goals and explain, step-by-step, how automation will help the company achieve those goals.

Break down your plan into manageable milestones.

One major reason why many automation projects fail is because they are simply overwhelming undertakings. Even if your goal is to automate everything (or close enough), attempting to do so in one fell swoop is simply not realistic nor is it a sustainable strategy.

You’ll make a much stronger, longer-lasting argument when you develop a plan that breaks down your project into smaller, more manageable increments. This also allows for more flexibility to be able to adapt and iterate as needed along the way. At Ayehu, we almost always recommend starting with tasks and workflows that offer the quickest and most measurable wins. This will enable you to continuously prove value and gain ongoing support as you begin to proliferate automation further throughout the organization.

Identify smaller areas where automation will have the biggest immediate effect and then work your way outward from there. Remember, as they say, the proof is ultimately in the pudding. Once you’ve got those smaller wins under your belt, you’ll be in a much better position to sell the big-picture benefits as well.

Sing your own praises.

Well, not necessarily your praises, but those of your automation project. If you’ve followed the steps above, you should begin to generate ROI relatively quickly. It’s in your best interest to promote those positive results early and often. There is no case more convincing than one that features real-world, definitive and measurable results.

This step is especially important for instances where skepticism still abounds. People can resist change and choose to doubt anticipated benefits of intelligence process automation all they want, but this becomes markedly more difficult when they can see and experience those benefits firsthand.

Not only will continuously promoting positive results quiet the critics, but it will also lay the groundwork for automating even more tasks and workflows in the future, which will ultimately lead to becoming a self-driving organization.

Get started on your journey to successful adoption of intelligent process automation today by downloading your free 30-day trial of Ayehu NG.

The Secret to Surviving the Tech-Led Revolution

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The Secret to Surviving the Tech-Led Revolution

Automation has been at the forefront of the digital revolution for decades, primarily because it maximizes efficiency, reduces costs and accelerates service levels. But the cloud, mobile and other innovative technologies – coupled with an ever-growing volume of raw data – have led to dramatically more complex IT environments.

According to ESG’s IT Spending Intentions Survey from 2018, 68% of those surveyed said their IT infrastructures are significantly more complex than they were just two years ago. Furthermore, 39% of respondents listed automated IT operations as a critical component of survival in today’s digital age.

In response to this increasing complexity, organizations are beginning to make the shift toward the next generation of automation – from basic to intelligent. This new level of automation involves technologies like machine learning and artificial intelligence to orchestrate workflows across a multitude of tools, systems and processes.

In fact, with the right platform, it is now possible to fully automate L2 and L3 tasks – functions which have traditionally required the use of human judgment. Now, those insights lie within the data itself and can be extracted, interpreted and leveraged autonomously by AI.

Embracing intelligent process automation is also enabling enterprises to lay the foundation for AIOps, a focus area that experts predict will boom over the next five years or so.

AI and ML: Augmenting IT Operations

AIOps is helping IT teams manage the increasing challenges created by data and digital disruption, leveraging intelligent process automation and orchestration to gain competitive advantage. Thanks to the powerful processing capabilities of artificial intelligence, IT can sort through mind-boggling amounts of data points to find the proverbial needle in a haystack.

The role of humans in this increasingly tech-driven environment is still present, though it too is evolving. Rather than relying on error-prone employees to handle the bulk of the processing work, human cognition and advanced skillsets are being used to define that proverbial needle.

In response to this, more organizations are focusing their efforts on reskilling and upskilling their existing staff to bring them up to speed on ML and AI technologies.

Making the Switch to Autonomous Operations

Autonomous operations (AO) utilizes advanced AI to deliver unassisted responses to IT incidents across the entire infrastructure. Thanks to the self-learning capabilities of ML algorithms, AO is able to continuously improve its ability to identify patterns and carry out the appropriate actions.

Again, human workers are still needed in an AO-driven environment, but in the role of supervisor as opposed to operator. Yet as the software continues to evolve and improve, and as errors consistently decrease over time, full autonomy and a zero-touch IT operations environment will one day become a very real possibility.

The Role of Data

The key to success with intelligent automation is accurate data, as this enables users to write more impactful rules. There is little to no value in static data. These days, it’s all about dynamic information which comes from things like descriptive metadata as well as relational and behavioral data.

In order to harness this dynamic data and gain adequate insights from it, organizations need to develop software-defined IT environments. Intelligent process automation is about the ability to not only proactively identify anomalies, but to also remediate those issues automatically without causing any business disruption.

The Right Way to Automate Intelligently

In today’s competitive landscape, automation is no longer an option but a necessity. That said, there’s a right way and a wrong way to leverage this game-changing technology. Start by weighing the time, effort, complexity and frequency of a given task and then benchmarking these factors against the cost of transitioning that task to intelligent process automation. From there, create a prioritized list. This will help you maximize ROI and harness the full potential of intelligent IT operations.

Not sure where to start? Why not give intelligent process automation a test drive free for 30 full days? Click here to launch your Ayehu trial today.

Transform Your Organization with AI in 5 Steps

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According to IDG’s 2018 State of the CIO report, 73% of IT executives struggle with striking a balance between the need to innovate and the demand to achieve operational excellence. One of the main reasons for this is the fact that IT frequently gets bogged down with a growing list of tools and competing priorities, all of which chip away at precious time and available resources. As a result, more organizations are turning to artificial intelligence as a way to bring technology, data and people together to drive digital transformation. Here’s how you can use AI to do the same in five easy steps.

Step 1: Understand what you can and cannot solve.

While AI has the potential to transform an entire organization, machine learning technology is not yet capable of fully replacing the experience of skilled professionals. Instead, IT teams can leverage automation powered by artificial intelligence to free up skilled workers to do what they do best: apply their expertise to develop solutions for highly prioritized issues.

Machine learning algorithms can sift through mountains of data to spot trends, deliver insights and identify potential solutions. Automation can assist in resolving certain issues. But it’s up to the IT department to apply the deep analysis necessary to achieve business goals.

Step 2: Identify and prioritize problems to address.

Artificial intelligence can help address the two biggest IT challenges: maximizing operational efficiency and improving the customer experience. The role of CIO has taken on much greater importance, with 80% of businesses viewing IT managers as strategic advisors for the business. As such, these individuals, along with others in IT, are responsible for defining key areas of focus for new technology, such as AI solutions. In order to achieve buy-in, new solutions should be presented in a way that closely aligns with broader organization-wide goals.

Step 3: Pinpoint gaps in technology and skills.

The IT skills gap is an ever-present problem, and it doesn’t appear to be going away any time in the near future. In addition to the talent shortage, IT budgets are stagnating. AI solutions can help to mitigate both of these issues by empowering IT teams to do more with less, and at a much faster rate than they could on their own.

Keep in mind, of course, that key skills are still necessary in order to drive these solutions. To address this, many organizations are looking to reskill existing staff. Thankfully, today’s automation tools do not require a PhD to operate them. Regardless, decision-makers should look for a data-based platform that features AI-powered technology.

Step 4: Develop your strategy.

Once you’ve identified which problems AI is capable of solving for your organization, defined the specific challenges you’d like to overcome, achieved buy-in for adoption and assessed what resources you have to work with, the four step is to develop your strategy for deployment. This strategy should include the following main segments:

  • Roadmap – from proof of concept to continuous process improvement
  • Testing Plan – defining what you want to accomplish and what metrics will indicate progress
  • Team – investing in and arranging training for IT staff

Step 5: Prepare for scale.

Any broader AI strategy should involve mapping out data across all systems, services, apps and infrastructure. This includes both structured and unstructured data as well as data in a variety of different formats. It’s essential to select a solution that is capable of ingesting, normalizing and formatting all data sources for analysis.

Further, it’s critical to choose a platform that offers room to mature and scale. And keep in mind, also, that while the “land and expand” concept may work for some companies, others – particularly those with a higher risk tolerance – may be better off to push transformation across the entire organization at once. Generally speaking, however, stable and sustainable change begins by starting small and building on early successes. The key is leaving enough room to grow.

Want to experience some of those early successes now? Launch your free 30-day trial of Ayehu NG and put the power of AI and intelligent automation to work for your organization today!

How to Leverage Intelligent Automation to Better Manage Alert Storms [Webinar Recap]

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Author: Guy Nadivi

As most of you already know, there’s a digital transformation underway at many enterprise organizations, and it’s revolutionizing how they do business. That transformation though is also leading to increasingly more complex and sophisticated infrastructure environments. The more complicated these environments get, the more frequently performance monitoring alerts get generated. Sometimes these alerts can come in so fast and furious, and in such high volume, that they can lead to alert storms, which overwhelm staff and lead to unnecessary downtime.

Since the environments these alerts are being generated from can be so intricate, this presents a multi-dimensional problem that requires more than just a single-point solution. Ayehu has partnered with LogicMonitor to demonstrate how end-to-end intelligent automation can help organizations better manage alert storms from incident all the way to remediation.

The need for that sort of best-of-breed solution is being driven by some consistent trends across IT reflecting a shift in how IT teams are running their environments, and how costly it becomes when there is an outage. Gartner estimates that:

Further exacerbating the situation is the complexity of multi-vendor point solutions, distributed workloads across on-premise data centers, off-premise facilities, and the public cloud, and relentless end-user demands for high availability, secure, “always-on” services.

From a monitoring standpoint, enterprise organizations need a solution that can monitor any infrastructure that uses any vendor on any cloud with any method required, e.g. SNMP, WMI, JDBC, JMX, SD-WAN, etc. In short, if there’s a metric behind an IP address, IT needs to keep an eye on it, and if IT wants to set a threshold for that metric, then alerts need to be enabled for it.

The monitoring solution must also provide an intuitive analytical view of the metrics generated from these alerts to anyone needing visibility into infrastructure performance. This is critical for proactive IT management in order to prevent “degraded states” where services go beyond the point of outage prevention.

This is where automating remediation of the underlying incident that generated the alert becomes vital.

The average MTTR (Mean Time To Resolution) for remediating incidents is 8.40 business hours, according to MetricNet, a provider of benchmarks, performance metrics, scorecards and business data to Information Technology and Call Center Professionals.

When dealing with mission critical applications that are relied upon by huge user communities, MTTRs of that duration are simply unacceptable.

But it gets worse.

What happens when the complexities of today’s hybrid infrastructures lead to an overwhelming number of alerts, many of them flooding in close together?

You know exactly what happens.

You get something known as an alert storm. And when alert storms occur, MTTRs degrade even further because they overwhelm people in the data center who are already working at a furious pace just to keep the lights on.

If data center personnel are overwhelmed by alert storms, it’s going to affect their ability to do other things.

That inability to do other things due to alert storms is very important, especially if customer satisfaction is one of your IT department’s major KPI’s, as it is for many IT departments these days.

Take a look at the results of a survey Gartner conducted less than a year ago, asking respondents what they considered the most important characteristic of an excellent internal IT department.

If an IT department performed dependably and accurately, 40% of respondents considered them to be excellent.

If an IT department offered prompt help and service, 25% of respondents considered them to be excellent.

So if your IT department can deliver on those 2 characteristics, about 2/3 of your users will be very happy with you.

But here’s the rub. When your IT department is flooded with alert storms generated by incidents that have to be remediated manually, then that’s taking you away from providing your users with dependability and accuracy in a prompt manner. However, if you can provide that level of service regardless of alert storms, then nearly 2/3 of your users will consider you to be an excellent IT department.

One proven way to achieve that level of excellence is by automating manual incident remediation processes, which in some cases can reduce MTTRs from hours down to seconds.

Here’s how that would work. It involves using the Ayehu platform as an integration hub in your environment. Ayehu would then connect to every system that needs to be interacted with when remediating an incident.

So for example, if your environment has a monitoring system like LogicMonitor, that’s where an incident will be detected first. And LogicMonitor, now integrated with Ayehu, will generate an alert which Ayehu will instantaneously intercept.

Ayehu will then parse that alert to determine what the underlying incident is, and launch an automated workflow to remediate that specific underlying incident.

As a first step in our workflow we’re going to automatically create a ticket in ServiceNow, BMC Remedy, JIRA, or any ITSM platform you prefer. Here again is where automation really shines over taking the manual approach, because letting the workflow handle the documentation will ensure that it gets done in a timely manner, in fact in real-time. Automation also ensures that documentation gets done thoroughly. Service Desk staff often don’t have the time or the patience to document every aspect of a resolution properly because they’re under such a heavy workload.

The next step, and actually this can be at any step within that workflow, is pausing its execution to notify and seek human approval for continuation. Just to illustrate why you might do this, let’s say that a workflow got triggered because LogicMonitor generated an alert that a server dropped below 10% free disk space. The workflow could then go and delete a bunch of temp files to free up space, it could compress a bunch of log files and move them somewhere else, and do all sorts of other things to free up space, but before it does any of that, the workflow can be configured to require human approval for any of those steps.

The human can either grant or deny approval so the workflow can continue on, and that decision can be delivered by laptop, smartphone, email, Instant Messenger, or even via a regular telephone. However, note that this notification/approval phase is entirely optional. You can also choose to put the workflow on autopilot and proceed without any human intervention. It’s all up to you, and either option is easy to implement.

Then the workflow can begin remediating the incident which triggered the alert.

As the remediation is taking place, Ayehu can update the service desk ticket in real-time by documenting every step of the incident remediation process.

Once the incident remediation is completed, Ayehu can automatically close the ticket.

And finally, it can go back into LogicMonitor and automatically dismiss the alert that triggered this entire process. This is how you can leverage intelligent automation to better manage alert storms, as well as simultaneously eliminating the potential for human error that can lead to outages in your environment.

Gartner concurs with this approach.

In a recently refreshed paper they published (ID G00336149 – April 11, 2019) one of their Vice-Presidents wrote that “The intricacy of access layer network decisions and the aggravation of end-user downtime are more than IT organizations can handle. Infrastructure and operations leaders must implement automation and artificial intelligence solutions to reduce mundane tasks and lost productivity.”

No ambiguity there.

Ayehu

Preparing for the Future of Work: Transitioning to Intelligent Automation

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These days, a growing number of organizations are making the shift toward integrating intelligent automation as a critical component of their business model. But it should never be about automating just for the sake of automating. That’s not going to help you win the AI race. The future of work will involve more of a hybrid approach that balances artificial with human intelligence for a “best of both worlds” kind of environment.

From the top down, it’s important to identify and address the challenges companies will face when implementing initiatives around critical areas, such as analytics, intelligent process automation, digital and AI. There is no shortage of lessons to be learned and common themes from which to gain knowledge. For those charged with preparing their organizations for what the future of work will inevitably become, here are five key insights to keep in mind.

Expect the unexpected.

While it’s true that business leaders can learn from others who have gone before, the fact is, every hybrid AI initiative is unique. As such, it’s important to design fluid systems that are capable of accommodating requirements, expectations and business challenges that are often unexpected. To some degree, the future of work is a moving target. Systems that can adapt and evolve will be the ultimate key to success.

Mistakes will happen.

It’s been said that failure is the key to success. This is an important mantra to keep top of mind when preparing for the future of work. Remember that when it comes to any type of change process, mistakes are inevitable. When and if you do fail, the key is to fail fast and bounce back by reflecting, regrouping and iterating your subsequent attempts with a greater understanding of what you’ll need to do in order to succeed. Decision-makers must also recognize that change is a necessary investment that requires the right communication and resources at the right time.

Start with small, measurable wins first.

Automating at scale isn’t something that takes place overnight – at least not if it’s done correctly. As you move toward the future of work and strive for digital transformation, it’s wise to start with smaller wins that can quickly generate ROI. To begin, focus on the tasks already being performed by the organization that are menial, repetitive and mature. Capturing those quick wins early will gain you buy-in and provide a solid foundation upon which to build out an organization-wide automation strategy.

Identify and communicate the ‘hows’ and ‘whys’ across the enterprise.

When it comes to good governance, it’s critical that executives carefully develop their strategic plans around intelligent automation. More importantly, they must openly and consistently communicate the hows and whys behind their decisions to everyone across the organization. As mentioned, incorporating the valuable skills of humans in with the benefits of automation and AI is the ideal scenario. As such, proactively reskilling, retraining and reorganizing employees will become essential over the coming months and years.

Automate accordingly to address business problems.

Some organizations find it necessary to enlist the help of consultants or outsourced companies to help them identify the best processes to begin the automation journey. Don’t be afraid to admit if this assistance is something that could benefit your organization. Either way, the goal is to gain a deeper understanding of business priorities so you can identify quick successes. Ideally, the automation strategy should be one that is a joint initiative between the IT department and the rest of the business.

Ultimately, what these five insights have in common is that they require executive buy-in, AI investment that is strategic and a shift toward a business model that involves a convergence of innovative technologies. Master these five steps and your organization will be much better positioned to be successful in the future of work.

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4 Ways Digital Transformation will Impact IT Support

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The IT help desk, as it once existed, has changed. Driving that evolution has been the changing demands and expectations of digital customers. Simply put, digital is revolutionizing the world of IT support and service. These newer and more complex requirements of digital customers (which include employees) are causing IT teams to re-evaluate what they have to offer in terms of support and capabilities. If your organization or team is at a similar crossroads, here are four key areas on which to focus. 

IT Support Strategies

Regardless of whether your IT service desk happens to support a company of ten or a multi-location, enterprise level organization, the time to start thinking digital is now. A great place to begin is by uncovering how employees have evolved into so-called “digital consumers” and, more significantly, how this evolution has changed the expectations they have of IT support.

To do this, evaluate the gap between your current situation and those changing expectations. In particular, look at your current channels of support. Poll employees to determine whether they feel the current channels they are using to contact IT support are sufficient and effective. Figure out what channels they might prefer. Also, examine common customer use cases and needs. Then, use this information to develop a strategy that incorporates newer, more innovative support channels (like self-service chatbots and virtual support agents).

Operating Models

How does your IT service desk engage with customers? The focus here should be more on this approach as opposed to best practices and ITSM processes. To bring your operating models in line with digital transformation, ask yourself and your team the following questions:

  • Is your approach to IT support adequately in line with your realistic business needs and expectations? For example, what is the overall goal? Cutting IT support costs? Minimizing lost time and revenue at a business level? Understand your objectives and align your strategy accordingly.
  • Do your IT support agents understand “personas” of its customers (i.e. the common characteristics and behaviors they share)? Do your operational practices accurately reflect these personas?
  • How does your IT support desk measure success? Is it primarily related to how the IT service desk has helped and/or improved customer and business operations?

Once you’ve answered these questions, use the data you’ve gathered to identify any and all disconnects between IT support status quo and the actual needs and desires of both the customer as well as the business as a whole. These gaps are where changes must be made.

IT Support Technologies

Without question, the future of IT support will rely heavily on automation. In fact, newer technologies have already made it possible for organizations to augment their human workforce by leveraging ever-improving artificial intelligence capabilities. With these advanced technologies deployed in the right areas, IT support teams are able to more effectively deliver on the increasing demands of digital customers.

Whether your service desk is already leveraging virtual support agents or is planning to in the near future, it’s important to ask the right questions. In particular:

  • Are your virtual agents being used to their fullest potential?
  • Are your virtual support agents being employed at the right points during the customer journey?
  • Do end-users feel that the VSAs improve their support experience?
  • Have you established a robust and accurate knowledge-base from which the VSAs can draw?

This last point is key, as virtual IT support will only be as good as the data behind it. That being said, creating an environment that blends high-tech automation with the human touch of IT support agents will position your organization for greater success.

IT Support Staff

The question of whether human service desk agents will be assisted, augmented and possibly even replaced by virtual support agents is no longer an “if,” but rather a “when.” Getting employees onboard with the concept of artificial intelligence isn’t always easy, especially those L1 agents who view automation as a threat to their livelihood. But it’s essential for an organization of today to remain competitive tomorrow.

Educate your IT support team on the value and benefits that AI has to offer. Make it about them – how AI will make their lives easier, enable them to perform more meaningful work, provide an opportunity to learn new skills and make themselves more marketable, etc. – not just about the company. And start investing in your current workforce. Identify champions of the cause and reskill them so they’ll be ready to face the digital future with confidence. Get them excited about the possibilities that lie ahead!

There is no longer any doubt. IT support as we know it today is changing. Only those organizations that are willing to adapt and evolve their strategies, models, technologies and people alongside those changes will make it through unscathed.

Want to experience the power of artificial intelligence for your IT support team? Try Ayehu NG absolutely free for 30 full days. Click here to download your free trial.

The 7 Secrets of Effective Digital Transformation

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If you’ve ever read the book The 7 Habits of Highly Effective People by Stephen Covey, you’re familiar with the concept of “beginning with the end in mind.” Putting that into context in terms of digital transformation means organizations must determine what their goals are before they begin adopting a ton of shiny new technologies. Unfortunately, many otherwise intelligent business leaders make the mistake of focusing so much on technological innovation that they miss the mark altogether.

This is not to say that technology isn’t a key driver of digital transformation. The problem often lies in a misunderstanding of what digital transformation actually is. According to a recent report by Altimeter, despite the fact that a growing number of enterprises are investing in innovative technologies, the majority of them are still lacking in terms of meeting customer expectations due in large part to a lack of digital literacy. The report also concludes that the main obstacles to achieving the solidarity and collaboration necessary for true, effective and lasting digital change are ego, politics and fear.

When an organization begins with a tech-first approach, it risks missing the point about what digital transformation is truly all about. In many instances, company leaders – CIOs in particular – fall into the trap of attempting to build new technology atop an old and crumbling legacy foundation. There’s an erroneous belief that all it takes to keep up with disruption is continuously adopting the latest and greatest apps and programs. New tech is great, but it must be adopted as a component of the digital transformation process, rather than its fundamental basis.

To demystify the whole digital transformation concept and improve your chances of success, here are a few expert tips to keep in mind.

The human element should be front and center.

Yes, the term is “digital” transformation, but in reality, it’s more about human transformation than anything else. That’s really what’s at the heart of any successful change. Technology is essential, yes, but it’s equally, if not more important that your people are all on the same page and moving together at the right speed. One of the biggest challenges to transforming a business is bringing its workforce up to speed, in particular, getting them current with the skills needed to facilitate change.

Experts unilaterally agree that the key to achieving true digital transformation is having a team of individuals who are curious, motivated by and passionate about the mission. Only then can you successfully usher in the innovative technologies you need to move forward.

A great example of this is Pitney Bowes. Several years ago, the company began initiating a shift to align itself with the changing world of tech. Specifically, they focused on evolving in 10 key areas such as machine learning, analytics, mobile, SaaS and APIs. But while leadership recognized the critical need for a strong technical strategy, they also prioritized the development and implementation of a solid people strategy as well.

The company organized curriculum for each of the 10 key areas of disruption and every one of the 1,200 employees was tasked with immersing themselves in one of those 10 topic areas for a period of one full year. The results have been beneficial to both sides – the company, by enhancing its workforce, and the employees, who have enriched their skills and improved their personal value proposition. Additionally, with staffers becoming subject matter experts in their chosen topics and subsequently collaborating together, many new and valuable relationships have been forged. This is advantageous to everyone involved.

Take the time to really understand your customers.

Ask any business leader what they believe the biggest driver of digital transformation is and they’ll probably cite the evolving behaviors and preferences of their clientele. Yet, according to the Altimeter report, a remarkable few (less than half) actually bother to truly understand their digital customers.

The few that are actually getting it right have done so by taking an outside-in approach. In other words, they take the time to determine what’s missing or broken that can solve a need and then focus their efforts on doing just that, tying in key performance indicators (KPIs) and ROI to demonstrate success. Rather than looking at internal processes, these innovators examine the customer experience first to identify opportunities to add value.

The key takeaway? If you aren’t meeting what your customers want or need, your efforts to achieve digital transformation will inevitably fall short and you will risk being left behind. The best technology, the best policies and procedures, the best laid plans – none of that will matter if the end result doesn’t make the lives of your clientele easier. That’s the end result that should be your focus from day one.

Establish new teams.

Spearheading digital transformation shouldn’t be a side project. If you want it done right, you need to have a team of individuals who are 100% dedicated to the cause. Teams should be made up of various people with different strengths and diverse backgrounds. For instance, you might have a project manager, a lead developer and someone who is focused on the customer experience. You could then supplement this with members from other roles, such as QA, development, ops and finance.

When an idea for a new initiative arises, the team’s job should be bringing it to fruition – at least to some degree – as quickly as possible. It’s not about achieving perfection right away. Digital transformation involves evolution, which means your team should be ready to go through a cycle of development – try things out, assess how they work and then adapt and improve accordingly. This agile methodology may require a paradigm shift, which is why it’s so important to have a dedicated team.

Cultivate collaboration as you deploy technology.

As mentioned, digital transformation isn’t entirely about technology. Yes, technology is a critical component, but it takes people to really achieve successful change, and that requires ongoing collaboration. Trailblazing ideas, sharing best practices, building a community – these things drive innovation and continuous improvement.

Use Pitney Bowes as an example once again. While they were designing their curricula around their 10 targeted technology areas, leadership also hosted global innovation roundtables to enhance collaboration efforts. As a result, they were able to identify cases in which there were common problems with their integration, delivery and operational practices. This enabled a fast and effective resolution across the board. Furthermore, because of the improved collaboration, workers acknowledged feeling much more engaged, as opposed to being just another “cog in the wheel.”

Don’t give in to the resistance.

It’s human nature to fear change, and that fear often manifests itself as resistance amongst workers. Logically speaking, the larger the enterprise, the greater the push back is likely to be. If you want to successfully shift to a digital ecosystem, you simply cannot let the naysayers get you down.

That’s not to say you should steamroll over them and ignore their concern. It’s more about your approach. Over communication and clear articulation, not just about what is happening, but how and most importantly, why, is key. It’s also important to develop a group of early adopters and innovators – those who embrace the proposed changes, as they can become your champions.

At the end of the day, digital transformation is really about people transformation.

Think like a startup.

As organizations become larger, greater divides between various groups and departments begin to occur. This results in silos of information, which can hinder communication and the ability to collaborate effectively.

To avoid this, try to adopt more of a startup mentality – one that focuses on operating nimbly and making sure that projects are being carried out in the correct way. Be cognizant of any walls and barriers that exist and focus on eliminating those and encouraging unilateral communication across the board. Encourage teams, departments and divisions to work closely together with a goal of making strategic decisions more quickly and rolling out smaller changes faster.

Take a bottoms up approach.

According to the aforementioned Altimeter survey, only 40% of the companies polled say their digital transformation initiative is overseen by an executive-mandated steering committee. Getting buy-in from the C-suite is certainly important, but how you go about doing so can make all the difference in the world.

Many organizations have had tremendous success by flipping the typical top-down narrative to more of a bottoms up approach. In other words, they focus on obtaining buy-in from all levels of hierarchy within, bringing together a diverse group of workers to collaborate together to create a digital transformation strategy.

This provides the opportunity to go through checks and balances to determine what makes the most sense and is directionally appropriate. Only when every ‘I’ is dotted and every ‘T’ crossed is the strategy presented to the C-suite for approval.

Conclusion

Is technology an important part of digital transformation? Of course. But if that’s all you’re focused on, you will inevitably come up short. Instead, focus on the people and policies that matter most, get all your ducks in a row and start with the end in mind. Do so and your organization can be counted among the success stories.

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