Digital transformation has revolutionized businesses across every industry. However, implementing new technologies to boost efficiency, agility and customer experience is rife with obstacles. This comprehensive 2600+ word guide examines some pervasive challenges companies face when digitally transforming, along with expert recommendations to tackle them.
The Widening Digital Skills Gap
One of the top roadblocks for digital transformation is talent shortage across critical emerging skills like cloud, analytics, AI/ML, cybersecurity and more.
As per Gartner, demand for IT skills and digital capabilities will increase by 125% through 2024, yet supply is failing to keep pace. Organizations are struggling to recruit professionals with both technical and business expertise. More concerning data points on the widening divide include:
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A LinkedIn study found 63% of companies believe talent shortage is the biggest barrier in leveraging new technologies. Moreover, 67% stated current skills gaps are preventing innovation.
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Deloitte estimates a growing 4.3 million worker deficit across data analytics, engineering and related fields by 2030.
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Burning Glass research shows demand for data science skills has grown over 650% since 2012 while hiring has only risen by 256%.
Specific Skill Shortages Hindering Transformation
Below are some roles that organizations consistently find challenging to hire and retain which impedes their modernization efforts:
1. Data Translators
While more teams gain access to rich data for decision making, extracting actionable insights requires statistical, business and communication excellence. However, professionals adept at turning analysis into measurable impact and storytelling findings to diverse stakeholders remain scarce.
2. AI/ML Engineers
As artificial intelligence and machine learning adoption surges across functions, demand for specialized roles like data engineers, model builders, and machine learning operations (MLOps) engineers outstrips supply. Competition and compensation for this talent is intensifying across major hubs like Silicon Valley.
3. Analytics Leadership
Recruiting analytics execs who can align data initiatives to strategic goals, spearhead organizational data literacy efforts, and tightly govern analytics to uphold data quality and privacy is an uphill climb. With the CDO role now mainstream, marquee enterprises often source talent from FAANG firms.
4. Hybrid Architects
Technology generalists who can connect legacy on-prem and cloud environments are pivotal when migrating apps or building with a cloud-first mentality. But their jack of all trades skillsets take years to hone across infrastructures.
Why Recruiting Stalls Transformation
This deficit stems from the exponential speed of technological shifts while planning, talent policies and education institutions fail to keep pace. Some root causes include:
- Lack of linkage between HR hiring plans and digital transformation roadmaps required capabilities
- Leadership reluctance towards remote hiring which expands talent access considerably
- Below market compensation and benefits for high demand digital roles
- Scarce investment in reskilling programs for existing employees
- Risk aversion in hiring candidates without exact skill match who can learn on the job
- Limited talent pipelines and hiring from the same traditional degree programs
Ultimately this crisis cripples organizations’ ability to adopt and benefit from sophisticated data-driven solutions to elevate operations, analytics and customer experience.
Strategies to Bridge the Divide
Smart approaches to building a capable digital workforce include:
1. Assess Existing Team Strengths
Catalog current skills across business and technology teams to identify key gaps measured against transformation requirements. Leverage capability maturity models for an honest self-assessment.
2. Map Roadmaps to Hiring Plans
Detail multiyear technology adoption plans spanning needs across infrastructure, data, analytics, apps and translate requisite role needs into 18-24 month recruitment targets.
3. Offer Upskilling Programs
From online platforms like Coursera, Udacity to coding bootcamps and internal training, enable employees to learn high demand skills like cloud engineering, data science.
4. Hire for Potential Fit
Widen talent pipelines by removing exact skill match requirements. Assess candidates’ ability to learn quickly and demonstrate cultural fit. Prioritize aptitude tests over formal credentials.
5. Boost Retention
Beyond competitive pay, retain top digital talent through exposure to cutting-edge projects, continuous learning budgets, leadership career paths and flexibility.
Overcoming Change Resistance
Once temporary crisis driven solutions, digital tools now require major behavioral shifts as mainstay productivity platforms. Yet few organizations invest adequately in adoption.
As per Prosci research, across sectors, a typical organization faces 60% resistance towards change efforts. Select causes behind the inertia include:
- Lack of sustained communication on transformation roadmap
- Perceived threats of job loss due to perceived automation by AI/ML
- Lack of input, involvement during tool selection stages
- Insufficient training and post go-live support
This inertia slows the pace of technology adoption, lowers ROI on new software investments and directly affects customer experience.
What’s more, employees today report unprecedented levels of burnout – a recent study found the share of U.S. workers quitting their jobs reached 3% in 2021, the highest in over 2 decades. This compounds hesitance towards learning new processes atop crisis-fueled digital overload.
Tactics for Driving Buy-In
Smart leaders use strategies from change management disciplines like Prosci’s ADKAR model focusing on;
Awareness – of need for change and transformation objectives
Desire – to participate and support based on WIFM (what’s in it for me)
Knowledge – through training in new skills, behaviors
Ability – via technology, resources and coaching
Reinforcement – to sustain engagement via incentives, culture
Proven approaches spanning ADKAR elements include:
- Early involvement – workshops, design sessions to co-create solutions
- Clear links between priorities and better employee experience
- Proof points on efficiency gains, career growth opportunities
- Peer success stories from early adopter business units
- Hands-on support during and after technology launch
Leaders must compellingly convey how new tools elevate work rather than replace jobs. With empathy, co-creation and capability building, they can overcome inertia.
Mitigating Emerging Cyber Threats
As digital transformation accelerates cloud adoption, connected sensors and remote operations, it multiplies potential attack surfaces and vulnerabilities drastically.
Yet per IBM, just 26% of organizations feel fully prepared cyber risks accompanying transformation. And underinvestment leaves them exposed – Verizon’s survey found over 85% of breaches involved human error or system glitches, not sophisticated attacks.
Costs of incidents are rising sharply as well:
- Another study by Tenable saw a 542% annual increase in ransomware globally from 2019 to 2022. Victims incurred around $170K in recovery costs.
- Malicious email attacks grew 149% YoY from 2020-21. Total damages from business email compromise scams reached $43 billion since 2016 per FBI data.
- Overall, the average cost of a corporate data breach now exceeds $4.35 million globally as per IBM’s Cost of a Data Breach report.
A reactive, siloed view of cyber risk and reliance on legacy defenses lead to repeated failures. Developing resilience requires rethinking foundational security architecture and culture.
Core Elements of a Modern Cybersecurity Framework
Leading analysts Gartner have defined a strategic model securing the digitally transformed business spanning:
1. IAM – Enforcing least-privilege access via strong identity and access controls and auditing across heterogeneous environments from mainframes to multi-cloud prevents 90% of attacks.
2. Data Security – As volumes of sensitive data surge, adopting adequate discovery, classification, encryption and analytics controls grows critical to lower exposure.
3. Privileged Access Management (PAM) – Attaining deep visibility into administrator activities, extensive key management and control over privileged access prevents costly insider risks.
4. Microsegmentation – Fine-grained network isolation of workloads limits lateral attacker movement which causes 95% of breaches as per Gartner.
5. XDR – Extended detection and response solutions enhance threat visibility via advanced ML and managed services to quickly identify incidents, limiting dwell time.
6. Simulation – Running continuous attack simulations to find overlooked holes across apps, endpoints and cloud infrastructure is essential for proactive defense.
7. Compliance – Given rising enforcement and steep fines by regulators globally around privacy and standards like ISO 27001, achieving and sustaining compliance is compulsory.
8. Secure Architecture – Adopting zero trust and a SASE framework that treats internal and external threats alike while enabling universal secure access fundamentally upgrades posture.
9. Security Culture – Through global security education addressing leading breach causes like phishing and strong accountability, organization behavior transformation reduces risk exposure tremendously.
10. Managed Services – Third party security operations centers (SOCs) and critical capability partners offset inhouse resourcing constraints and skill gaps cost effectively while hardening defenses.
Steps to Reign in Runaway Costs
For companies spending upwards of $100 million on transformation like insurer AXA over 2 years, or attempting to consolidate decades of legacy siloed infrastructure, the price tag of modernizing is invariably steep.
Typical problem areas increasing costs include:
1. Uncoordinated Buying
Siloed software evaluations and purchases across business units lead to high app redundancy, integration complexity and licensing costs at scale.
2. Maintenance of Legacy Systems
Maintaining legacy platforms being slowly phased out in favor of modern cloud apps leads to significant overhead during transition periods.
3. Multi-Platform Integrations
Getting data, functions and experiences to flow across legacy on-prem data centers to cloud to IoT and edge networks demands heavy custom engineering efforts.
4. Agile Scope Creep
As agile projects progress towards workable prototypes through successive sprints, evolving specifications and discoveries around technical debt frequently necessitate bigger budgets.
Per McKinsey, large transformation programs exceed initial budgets by 200 to 300% on average. With legacy complexity, inadequate discovery of constraints and poor vendor planning, overruns snowball.
Achieving Financial Visibility and Control
Steps to reign in costs include:
1. Audit Existing Investments
Group-wide app and technical asset inventory including integration and support costs, compliance risks, redundancies and efficiencies guides rationalization.
2. Align Roadmaps to Capabilities
Anchor transformation blueprints to evolving operational capabilities needed vs trend-driven software buying that worsens sprawl.
3. Leverage Pilots
Test new technologies via small controlled launches focused on user experience and metrics vs extensive upfront builds. Favor experimentation.
4. Evaluate Beyond Cost
Audit vendor ecosystem capabilities beyond go-live implementation costs – their integration ecosystem, operational analytics and automation functionality prove pivotal long term.
5. Tracking Utilization Rates
Post deployment, consistently monitor usage metrics across user cohorts to spot gaps needing support vs low adoption platforms needing shutdown.
6. Plan Margins for Unforeseen Events
Account for sizeable contingency funds or insurance to address unplanned needs in large programs – ranging from cyberattacks to new regulation needing compliance spends.
Enabling Enterprise Agility
Beyond technology upgrades, adapting operating and business models to rapidly shifting customer needs relies on organization-wide agility. This allows faster responses to market dynamics through decentralization.
Industry leaders like ING Bank use 8000+ agile scrums while Spotify leverages autonomous squads across engineering, analytics and design to test and release experiential features regularly.
But agile transitions prove intensely challenging – per McKinsey just 30% succeed. Obstacles like culture rigidity and lack of sustained leadership commitment derail progress.
Let’s examine some common hurdles:
1. Misaligned KPIs
When project success and individual career growth stay pegged to waterfall mechanisms like utilization rates rather than value delivered, agile stalls.
2. Legacy Processes
Approval-driven governance stopping teams from flexing budgets or priorities to capitalize on experimental findings counter agility.
3. Spotty Leadership Vision
Agile needs leaders passionate about empowering self-driving teams versus chasing short term profits. Lack of coaching support also impedes team autonomy.
4. Piecemeal Training Investment
While organizations budget for short Scrum master classes, engraining product-centric mindsets across thousands of employees via coaching requires serious resources.
5. Minimal Technology Modernization
Clunky legacy platforms prevent accessing real-time data at scale critical for data-driven decisions and rapid response. Technical debt must be overcome.
6. Cultural Debt Accumulation
If promotion policies retain STRICT upward mobility, controlled risk appetite and siloed thinking – core barriers to innovation surface. Values matter more than practices.
Steps to Drive Successful Agility
With meticulous planning, leadership realignment and change management practices, enterprises can break decades old shackles.
1. Executive Commitment
Weekly coaching and planning participation by C-suite sets the tone for transparency, removing departmental barriers and fast decisions.
2. Knowledge Transfer
Through weekly newsletters, internal social campaigns and evangelist testimonials, continually educate on agile benefits from productivity to employee experience and convey global progress.
3. New Role Mandates
In signing off on agile charter, leaders endorse fluid team structures, upgraded collaboration tools and decision rights around experiments to help teams self-organize.
4. Aligned Incentives
Tie bonus pools and stock options to customer centric KPIs – like net promoter scores to fuel accountability to users vs shareholders alone.
5. Distributed Authority
Guide teams to tap cross functional expertise needed to solve complex challenges without bureaucracy through flatter hierarchy and collective decision models based on merit.
6. Culture Measurement
Continually gauge values alignment via anonymous surveys and staff interviews to address gaps – between professed leadership vision and ground reality which erodes staff trust.
The strategies above help organizations successfully tackle common digital transformation obstacles and future proof operations. But every company’s challenges manifest uniquely based on maturity, size, industry norms and legacy landscape.
Defining a long term transformation roadmap – both technology capability development and change management – anchored to strategic objectives while also moving in agile sprints is key. This allows holistic tracking of progress and tradeoffs.
Partnering with specialized Transformation Office consulting firms can provide invaluable program governance, capability benchmarking and project leadership through complex modernization journeys.
To discuss how to elevate your organization to the next level while mitigating risk, please get in touch.