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Creating Generational Legacies

Wednesday, June 26, 2019

The Evolution Of Management from Industrialisation to Industry 4.0

Michael Bolton eloquently writes about the necessary change in management styles of the Industrial Age to the knowledge exonomy to Insustry 4.0 
From the command and control - where Henry Ford would day that a customer can have any car that he wants - as long as it’s black -

 to 1950 - 2000 era of Consumerism - where industries created homogenous products en made

To 2000- now - where it’s all about the customer in a hyperconnected personalised  world - Management styles and organisational structures are changing accordingly, with leaders as stewards and guides vs command and control .

As Christine Mcdougall shared at the June19 #BBG EnterpriseForum - the organisational structure is mimicking the “cell” where the membrane is the domain of the leader!




Hope you enjoy the article 




Some would argue that in business the power has shifted to the customer. What role if any does the humble project have to play in helping organisations adapt to the ever-changing yet customer-centric world we now live in?

Henry Ford was an indomitable entrepreneur who understood how to create markets before there were any. As a captain of industry and a business magnate, the founder of the Ford Motor Company became a driving force behind what became the assembly line technique of mass production.

He understood that mechanising processes, ensuring that it was linear in nature, incremental in each step, and component-driven could produce a high-end product with consistent look and feel, as well as quality. He also understood that it was possible to build a market for his motor car and set about doing so.

Many organisations used Henry Ford’s so-called ‘blueprint’ to develop organisational structures, leveraging his knowledge to mass produce a homogenous product (or products) of quality, using well-defined and end-to-end processes and structures to develop their own assembly lines with minimal human effort.

As he once said:
“Any customer can have a car painted in any colour that he wants so long as it is black.” – Henry Ford, 1909). 
Basically the producer dictated the outcome for the customer.

While Ford may have provided the blueprint that so many organisations have followed, we are rapidly moving into a very different era on the customer journey. Ever-changing needs fuelled by technology and high expectations for innovation has shifted power away from the corporation of Henry Ford’s era to the consumer. But is it changing the way our organisations are structured and managed?

And what role does the humble project play in keeping organisations ahead of the curve?

Reliable, Repeatable, Measurable, and Certain: Our Structural Consistency

For more than a century, global organisations have relied on manufacturing processes that were organised into reliable, measurable, repeatable and certain processes that delivered consistency. Manufacturing organisation naturally extended to other organisational structures that sought centralised control and consistency as well.

The organisational chart appeared pretty quickly, visually depicting a command-and-control type of approach to governance and quality control, with those higher up the tree given more authority.

What characterised much of the early 20th century was customer demand exceeding supply, enabling organisations to define how the products looked, felt, were experienced, and what attributes customers could have access too – or in Ford’s immortal words: Any colour so long as it’s black.

Agility by a Different Name

Following World War II, a different kind of structural evolution started to take shape and shifted organisations toward a more decentralised model, where decision-making was delegated to smaller, more autonomous units instead of central control.

Smaller organisations were able to gain an advantage over larger ones in the post-industrial economy, as they were quicker to respond to change and were more dynamic in how they did so. It enabled them to react to customer demands as they changed.

The boom of the 1950s shifted a lot of manufacturing and business. Leveraging armed forces operating models that had been successful in the war smoothed the way for organisations to break into smaller, focused units made up of specific skills and goals – (think platoons, squads, or units). 

Over the next fifty years, consumerism became the norm as organisations created largely homogenous product lines that customers had to choose from what they were offered, to a large extent.

2000’s -  the Consumer has the power 

But in the 2000s, the worm well and truly turned from organisations dictating to some extent what the customer could buy to the customers defining what the organisation will provide.

A Hyperconnected, Personalised World

We are in very different times to those of our parents and grandparents. We are now living in a hyper-connected, personalised world characterised by tech-savvy, on-demand services with near-instant gratification that is expected by customers to define their experience, however that may look.

Today’s market disrupters are taking on industries that have been founded in traditional structures and previously dominated by a few who either didn’t move fast enough to personalise their brand (either unable or unwilling).

But it’s not just about products; it’s about platforms, technology, and understanding the mind of the consumer. Uber is a classic example of identifying the needs of its users and building the service around those needs.

Disrupters Driving Increased Project Activity

But what does this mean for the consumer and the organisation, not only in how the assembly line now supports personalised demand but also in how an organisation must shape itself to deliver to customer needs, especially in service industries? Organisations now have to come up with strategies and tactics that enable them to appeal to individuals who have grown up expecting immediacy and instant gratification.

Global organisations are moving away – by force and by disruption – from the traditional static and siloed hierarchies and a steady state of BAU with line managers rewarded for keeping the lights on. There is a definite shift in play as more organisations seek to become more dynamic and adopt greater agility, both in how they work as an organisation and in how they meet their customer’s needs and demands.

Businesses are attempting to shift towards a proposition that supports creating and sustaining value in an ever-changing market and this also requires the business agility that high levels of targeted project activity deliver.

Sustainability is the Key – No Matter What Your Project

Whilst new, optimal organisational structures continue to shape up and roll out into organisations, we feel it is imperative that an organisation considers the critical elements that will enable a business to not only successfully deliver projects to keep ahead of the consumer curve but remain sustainable through this and into the next era

If we asked our old friend Henry Ford he might have already given us the answer:
 “If everyone is moving forward together, then success takes care of itself” 
Management has to Evolve as Much as Business Structure Does

So what is changing then? Management techniques are evolving to support organisations that want to meet and manage consumer and market-changing expectations. For example:

Collaborative leadership: Collaborative leadership is focused on the leadership skills that exist across functional and organisational boundaries, ensuring that people can move forward together, where everyone can engage with anyone to deliver on a shared vision. Elon Musk is a proponent of the lack non-hierarchical communications, but it may not work for everyone, particularly where an organisation has not built the kind of structural scaffolding that enables flat hierarchies in management.

Organisational Agility; In addition to the drive toward a more collaborative leadership is the idea of organisational agility – the ability to bend, flex, scale, change, and do so cohesively. A key to achieving this agility is the increasing use of projects to get business outcomes and the fail fast ethos of delivery methodologies like Agile.

Customer Expectations and the Ability to be Agile

Personalisation is a vital part of marketing and selling to today’s customers, as new generations of consumers make very different decisions about how they buy and why. Personalisation is a significant part of the experience they have as consumers and it will continue to drive how organisations adapt to meet their expectations.

This is not something that Henry Ford had to grapple with. He had a handle over his customers and build his business accordingly. Most organisations these days face very different business conditions.

Our perspective is that he would have grasped quickly the concept of business agility and invested heavily in a collaborative but decentralised management structure that empowered the business through projects to keep pace with changing consumer demand.

Michael Bolton is a co-founder of Quay Consulting, a leading project management consultancy based in Sydney, Australia. He is a contributor to the Quay Bulletin and co-author of Trends in Project Management.

The Flawed Logic at the Heart of the Automation Fantasy


A thought provoking white paper on Automation and digital learning by Michelle Shevin Dec 19, 2018 · 14minute read 






“Tech doesn’t solve for trust, accountability, or labor — it shifts responsibility away from systems and onto individuals.”




Across the private, public, and non-profit sectors, a common recipe is being applied to growing stores of data: interoperability → integration → optimization → automation.

Promising to usher in an era of “smart cities,” “efficient services,” and “unlimited leisure,” automation is the fantasy driving the current revolution across business and bureaucracy.

Overwhelmed by the massive amount of information (personally identifiable and otherwise) generated by your operations in the digital age? Not to fear, the Age of Automation is here.

One Stack to Solve Them All

Automation promises (cheap) compliance. It worships at the altar of efficiency. It paints your wicked problems as debuggable and your complex systems as a set of linear causal relationships just waiting to be disentangled. It does not distinguish between the types of problems and processes faced by private vs. public institutions. It will not only mine your data for diamonds, but also cut and polish the stones. Put simply, it will “change the world.”

Organizations are not just mobilizing their own data. The best insights come from analyzing massive swaths of data from different sources. This is why public sector agencies are pooling data across services, and why consumer companies are gobbling up their customers’ personal information. As cited by the New York Times, American companies spent close to $20 billion in 2018 on acquiring and processing consumer data. 

The promised logic of that spend goes something like this:

In step 1, 

interoperability, data is made machine readable and digestible. Nigh gone are the days of manually digitizing PDFs. A growing stack of tools including scanners, computer vision, and natural language processing algorithms is getting better at munching up even the messiest data substrates and regurgitating extracted and compiled data-cud, ripe for analysis. With graph analytics, even the most disparate data sets can be layered for mining.

In step 2, 

integration, data from separate systems is joined up and made accessible through interfaces, dashboards, and databases. Longitudinal researchers, rejoice! Silos are spanned. Graphs are analyzed. Previously unseen relationships are modeled and visualized. Trends are heralded, their strength and directionality dissected and served up as so much “insight.”

In step 3, 

optimization, algorithms are layered onto the stack that promise to do things like “recommend,” “personalize,” and “predict” much better than any mere human can or ever could. In lieu of complicated stakeholder engagement with its messy debates about values, these algorithms take their cues from the logic of our past decisions and dominant narratives — from capitalism and neoliberal institutionalism. They drive toward efficiency. They drive toward growth. If the predecessor systems that generated their historical data inputs were sustainable, equitable, or fair, the algorithms might be too. If not, onward— speed the collapse.

In step 4, 

automation, new algorithms are given new responsibilities. Building onto a stack that already claims to better understand system dynamics and relationships, they now offer to reorganize accountability mechanisms and decision-making structures. They determine creditworthiness. They allocate healthcare benefits. They predicate access to public services — on previously orthogonal behaviors, or on one’s ability to prove their identity.

Alas. In the near term, at least, the promised land looks like trying to create a DHS digital account in Arkansas, and unfortunately it’s not pretty.


“The future is already here — just unevenly distributed”


From my current perch in philanthropy, I see the shift happening everywhere — at different speeds in different places, altering the very ground for the work that we want to do across sectors and regions — sometimes insidiously, always inexorably.

In the past, I’ve worked in the public sector (DoD’s Cebrowski Institute), the private sector (syndicated research on technology futures), and in cross-sector consulting (developing innovation ecosystems for prize incentive competitions). In a relatively short time, I’ve come full circle from tech engagement enthusiast (at the age of 24, I described myself in a job application as a “wearables evangelist”) to cautious skeptic of technology’s capacity to intervene positively in human systems.

Last year, I was in a meeting on Sand Hill Rd., beating my drum about centering ethics and equity in the development of automated public sector systems, when a funder and data integration enthusiast asked very seriously, 

“Why do you keep bringing that up — like, what could go wrong?”

At this point, from my perspective, it’s less about what could go wrong and more about what already has. 

There’s something rotten at the center of the automation fantasy.

Automation goes by many names (“artificial intelligence,” “algorithmic decision-making,” etc.) but likes to hide its true nature. 

Here are a few of the many faces it wears.

Garbage in, Garbage out.

And most of it is garbage.

Sure, “big data” has revealed correlations and relationships that enable monetization, value creation, and improved service delivery (perhaps less than you’d think). But that’s largely in spite of data quality and veracity, not because of it.


To cite one of many misnomers, what we’re building is not actually artificial intelligence, it’s (flawed) human intelligence at the scale of industrial societal machinery — yes, the man behind the curtain is still twisting at the knobs of civilization. And yes, it is indeed a white man wearing cargo shorts with socks & sandals in Palo Alto.


Planning often disguises itself as prediction.

At scale, algorithms create the future they forecast.

When machines make an accurate prediction, it’s a triumph of status quo, not of foresight.

More often, as with humans, they make self-fulfilling prophesies. They’ll serve up more of the same, faster this time, more accurately, and with less of your input needed. For recommending what to watch next on Netflix, this is really great. I do not aspire to stop liking sci-fi films with a strong female lead. (In case it hasn’t penetrated your filter bubble, don’t sleep on instant camp classic The Pyramid.)

But when it comes to public sector service delivery and systems that have real impact on families and livelihoods, it’s a different story. Why would we intentionally model future decision-making on past patterns, which we know to have been systematically biased, unfair, inequitable, discriminatory, and in many cases ideologically irresponsible, if not dangerous? Sure, algorithms are pretty good at learning from past patterns to project future decisions. But in myriad systems, that’s the last thing we should want them to do.

Friction is the engine of stability — and of progress.

Healthy systems thrive at the edge of chaos.

Automation arrives under a banner of “progress,” but reveals itself an agent of stagnation.


Friction — struggle — is theorized to be the driving force in biological evolution, tool use and technology development, a thriving immune system, and more. And yet in automation’s recipe book, it’s first on the list of ingredient subsitutions.

Sick of having to do your own research? Algorithms will mine vast stores of information so you don’t have to. Sick of waiting in line? Algorithms can optimize your arrival time. Sick of composing responses as part of basic human communication? Algorithms can suggest a response that’s uncannily just so you.

But what’s at stake in this rush to lubricate our every (trans)action? What might be lost when we no longer have to wait, suffer boredom, struggle, think about it, or even try?

Optimization and influence are subtle forms of control.

Borrowing from ad-tech business models, automation’s end-game in a capitalist society is not just selling more stuff, but actually designing human behavior.

The data-mining infrastructure undergirding automation is the same that supports Surveillance Capitalism, and it wants to blunt our agency, rob us of our sanctuary, and erase our unpredictability. 

As Shoshana Zuboff puts it, 

“Forget the cliche that if it’s free you are the product — you are not the product, but merely the free source of raw material from which products are made for sale and purchase…You are not the product, you are the abandoned carcass.”


In “Algorithm and Blues: The Tyranny of the Coming Smart Tech Utopia,” Brett Frischman describes some of the ideology at the heart of “smart tech” and automation:

“Supposedly, smart phones, grids, cars, homes, clothing and so on will make our lives easier, better, happier. These claims are rooted deeply in a smart-tech utopian vision that builds from prior techno-utopian visions such as cyber-utopianism as well as from economic-utopian visions such as the Coasean idea of friction-free, perfectly efficient markets and the Taylorist vision of scientifically managed, perfectly productive workers. 

In our modern digital networked world these visions creep well beyond their original contexts of idealized internet, markets and workplaces. Smart-tech can manage much more of our lives.”

There is no magic in machine learning.

Only ones and zeroes, graphs and correlations.

There’s no magic in machine learning, just a cascading flow of abdicated decisionmaking (and thus accountability). Sure, the power imbalances inherent in a world where some humans make decisions on behalf of other humans (to say nothing of nonhumans) is plenty problematic, but are we really so sure glorified mathematical equations are going to do a better job?

Speaking with the New York Times, grandfather of computer programming Donald Knuth recently admitted,

“I am worried that algorithms are getting too prominent in the world. It started out that computer scientists were worried nobody was listening to us. Now I’m worried that too many people are listening.”


It’s clear that many decision makers have already bought into the fantasy that machines are better suited to make choices than we are. Code is being put in charge of important systems and decisions, in many cases without even a thought to processes for redress or adjudication. Who can afford a protracted legal battle to seek recourse after a buggy algorithm denies their healthcare? Ironically, only those whose income precludes them needing access to public services at all.

Who wins — and who loses — in an automated world?

Automation promises to usher in wholly new forms of inequality.

Increasingly, access to services that put an explicitly human face on the automation of service delivery is sold at a premium. 

And in an automated world, privacy and sanctuary are privileges you pay for.


“Better never means better for everyone. It always means worse for some.” — Margaret Atwood

For a preview of who plans on winning the long game, take a peek at some of automation’s most vocal proponents: + 

The Inter-American Development Bank (IDB) is promoting the use of predictive analytics in the public sector, part of an ongoing fetish also known as “data for development.” 

+ For IBM, data is the new oil. For enterprise software companies, automation is what’s for dinner, and the public sector is a massive emerging market. 

+ As we heard from Facebook’s Mark Zuckerberg when (weakly) challenged by Congress on almost any problem with the platform that now mediates global information consumption (initially designed to reduce the friction associated with checking out freshman girls): algorithms will fix it. 

+ Big consulting firms like Accenture stand to gain from what they call their “technology vision.” This week, McKinsey is under fire for aiding and legitimizing authoritarian governments.


Fundamentally, there are trade-offs implicit in an automated future. We are sold a bill of goods based on the assumed value of efficiency, but make invisible trade-offs in equity. We are promised freedom from friction, but end up losing serendipity. Our systems optimize resource allocation, but only by rendering us contantly surveilled and increasingly responsible for managing our interactions with the system. We look forward to a future where drudgery is machine-borne, but struggle to imagine holding on to human dignity and meaningful lives. We are seduced by the logic of straightforward measurement and evaluation, but forget that not everything that matters can be measured.

Structural inequality sits squarely in automation’s analytical blindspot.

Overreliance on data analysis functionally prioritizes the types of correlations that linear algebra is good at spotting — but not those arising from complex system dynamics.

By now, biased algorithms are a well known problem. Because they are reliant on past data, they are subject to codifying bad patterns, based on bad data collection, inequitable historical distribution of services (and thus oversurveillance of low-income and minority populations), and pre-baked assumptions. We can see the evidence of this bias in the racist and sexist outcomes of automation efforts across sectors.

But with all of the focus on introducing fairness, accountability, and transparency in machine learning, we are still failing to see the forest for the trees. Specifically, attempts to correct for bias in algorithms typically fail to account for structural inequalities. Because it is steeped in and born out of historical data, automation knows only how to deepen the grooves of existing patterns, valuing only those variables that have been isolated for measurement and then made meaningful through their relation to other metrics.

But it is precisely the structural ecosystem in which automation is being deployed that we’ll need to problematize and address if we want to harvest the promise of analytical tools. Legitimately resistant to statistical analysis, the water in which we swim — a rich stew full of narratives of dominance, ideologies of growth and consumption, fundamental false dichotomies, rampant othering, ubiquitous misinformation, and ecological fatalism — is something we can glimpse the edges of but scarcely transcend.

With automation, transcendence is not on offer. 

Optimization, yes. Mitigation, maybe. 

Solutions, in name only. Instead, the fantasy of automation carries the ethos of exceptionalism and the the arrogant allure of the “end of history.” The fantasy of automation suggests deploying analytics to lock in the structures of the status quo. It’s a particular view of “progress.” Things could be so much better, it suggests, as long as the high-level distribution of power and resources stays pretty much the same.

Looking at algorithms that promise to revolutionize healthcare, Shannon Mattern writes:

What’s more, the blind faith that ubiquitous data collection will lead to “discoveries that benefit everyone” deserves skepticism. Large-scale empirical studies can reinforce health disparities, especially when demographic analyses are not grounded in specific hypotheses or theoretical frameworks. Ethicist Celia Fisher argues that studies like the Human Project need to clearly define “what class, race, and culture mean, taking into account how these definitions are continuously shaped and redefined by social and political forces,” and how certain groups have been marginalized, even pathologized, in medical discourse and practice. 

Researchers who draw conclusions based on observed correlations — untheorized and not historicized — run the risk, she says, of “attributing health problems to genetic or cultural dispositions in marginalized groups rather than to policies that sustain systemic political and institutional health inequities.” — Shannon Mattern, “Databodies in Codespace”

Automation shifts the burden of accountability away from systems and onto people.

The myth of unlimited leisure time through automation already rings false.

In an automated world, processes have been redesigned not to improve user experience, but to increase profit margins and/or reduce human capital expenditures.

But as Karen Levy’s research on trucking shows, automation doesn’t replace humans as much as it invades them. Like a violent ex-partner, it surveils, encroaches, polices, and manipulates, while requiring intimate access to the body and demanding increasing access to the mind.

Without intervention, those already at the margins will be further marginalized. And when automation is deployed in service of the status quo, value is extracted and/or invisible labor required from every person who interacts with automated systems.

The patient is now coordinator and advocate of her own care. The consumer is actively consumed in the ongoing cycle of consumption. The citizen is now arbiter of her own truth and curator of her own meaning. Across sectors, the invisible (and unpaid) labor now necessary to navigate the systems in which we are inextricably implicated, reveal us — the individual — increasingly responsible and increasingly commoditized in the acts of consumption, citizenship, and the pursuit of health and wellbeing.

No such thing as neutral technology.

In the fractal hierarchy of automation technology, invisible values are embedded everywhere you look.

There are values — moral values — in every design choice, every implementation process, every organizational culture change, and in every impact on end-user decision-making.

The framing of automation as a “technical fix” or inevitable application of technology obscures the age-old philosophical and moral underpinnings of the machine learning algorithms implicit in the automation stack, too often running on auto-pilot in lieu of having hard and inclusive conversations about values that resist quantification and measurement.

When it comes to automation technology, we should never assume neutrality, let alone positive progress. 

This is especially important when it comes to data integration and automation in the public sector. The same technical infrastructure built to support government transparency can be easily deployed for social control. The same analytics layers that promise to make criminal justice systems more just can also be used to fill private prisons with marginalized citizens. And the same surveillance mechanisms that promise to improve public safety can be mobilized to restrict citizens’ access to services.

China is promoting its social credit system, literally based on the government’s phrase “once untrustworthy, always restricted,” as a way to improve citizen trust in government. Chinese officials met with counterparts in at least 36 countries last year specifically to share their approach to “new media or information management” (read: digital control). 

In Mexico, where already just 2% of citizens believe they are living in a full democracy, transparency speeds ahead of accountability, leaving in its wake not just truth, but also cynicism and disengagement. In Brazil, a renowned and expansive public integrated data system built to automate social service delivery is being connected to private sector employment data, just as a hardliner takes office who has waxed romantic about military dictatorship. 

In Kenya, the government has set out to catalogue each citizen’s genome and earlobe geometry. And in the United States, public integrated data systems are being built that will soon touch the majority of citizens.

To be clear, many of the dedicated civil servants who operate our public services rightly welcome data integration; even getting access to real-time data dashboards from within one’s own agency is still a compelling prospect in many districts. But there is a useful distinction to be made between data being used to improve outcomes through research versus data being used for individual case management, predictive analytics, decision-support, and automated service delivery. I’m worried that tech companies are selling the public sector on a vision of automation whose tools embed values of capitalism, not sustainability; efficiency, not equity; status quo, not justice. And to note, no matter how many best practices are followed in design and implementation (as they have been in the integrated data system in Allegheny County, PA), there are at least two sides to every story of automation.

In every place you look, the fantasy of automation is finding purchase and fertile ground to plant its seeds. In spite of the blaring hype coming from enterprise tech companies, it most often does so quietly, insidiously, and strategically.

Impacted communities are left unaware until first contact with a buggy process or infuriating user experience. University IRBs are a thing quietly longed for, and yet long forgotten in the rush to ship. Systems are lifted wholesale from one context, white-labeled, and airdropped into another. Sold by the promise of modernization and progress, our leaders commit to procuring commercial off-the-shelf societal control.

I want to emphasize that none of this condemns data integration, graph analytics, or machine learning. These are valuable tools in a kit that must also include social science and stakeholder engagement. But the context in which these tools are deployed sets up path dependence. The fantasy that drives the purchasing and purposing of these tools merits careful scrutiny. The business models they support, the embedded values they encode, the degree of person-centeredness they reflect, the way they subtly shift responsibility between stakeholders, and the structural inequities they threaten to lock in — matter deeply. And the current context in which automation tools are sold and deployed is deeply flawed.

Commitments to community engagement, person-centered design methodologies and implementation approaches, rigorous and ongoing ethical review, default inclusion of social scientists and artists in development processes, algorithmic auditing, and the explicit and inclusive discussion of what values get embedded in tools (particularly ripe for revisiting: the unspoken social compacts between citizens and commercial/legal governance mechanisms) could go a long way toward ensuring automation isn’t flavored by authoritarianism, but not if we stay asleep at the wheel of this self-driving car.


Something is rotten at the center of the dream, and we urgently need to wake up — before we automate the broken promises of our past into the very fabric of our future.

Tuesday, June 18, 2019

The need for IT to create connectivity in organisations




With the advent of 5G , Internet  of Things (IOT) , the ability to access data faster , quicker and smarter - productivity improvements and customer experience should abound ..... however larger corporates will need to relook at their current IT systems to take advantage of these amazing advancements 

This pain and opportunity is highlighted In a report by Mulesoft , :- https://www.mulesoft.com/sites/default/files/resource-assets/MuleSoft%20Reports%20-%20Connectivity%20Benchmark%20Report%202019.pdf

Here is my summary 



Very few (36% ) of IT leaders say that their organization offers a completely connected customer experience. 

More than half (53%) respondents report having over 800 (which will grow significantly ) applications in use but only 29% are connected or integrated 

As a result 97% undertaking or plan to undertake digital transformation initiatives to increase productivity and customer service. 

It’s all about (or should be about) the customer experience - and these are some issues that need to be solved to protect, analyze, and enhance their experiences:-

  • it security (57%), 
  • big data/analytics (55%), 
  • IoT (49%), and 
  • AI/machine learning (36%)

Silo’s,  lack of connectivity , integration and collaboration are the big issues -(the big pain that needs the pain killer) 

83% report data silos create business challenges in their organization.

Both from a cultural or an IT perspective 

People find it difficult Integrating and connecting their applications across the enterprise

More than half (53%) respondents report having 800 or more applications in use but only 29% are connected or integrated 

The majority of IT decision makers (59%) find it difficult to introduce new applications or technologies or make changes to existing applications because of their legacy IT infrastructure.

But they acknowledge that they need to

How are they going to solve this pain?

It seems to be all about leveraging APIs,hire more talent, reusing existing assets and Outsourcing - using agile software development and deployment 

Why use agile and leveraging API’s? 

  • increased productivity (53%), 
  • greater agility (46%), 
  • and increased innovation (40%).

About Mulesoft

Mulesoft is part of Salesforce - has about 1600 clients and builds application networks to unlock data to increase productivity, revenue channels  and customer experience 


Saturday, June 15, 2019

Diversity and Inclusion leads to Innovation and Growth - and Victoria is up there - leading the charge!

When it comes to Diversity, Inclusion  and Innovation - Melbourne is up there, and the Kelly Hutchison’s of the world are the drivers of this change - She is driving this change by leading the charge with the Victorian State Governmebt initiative - “the Digital Innovation Festival “

Women Entrepreneur Cities Index listed the top 50 cities globally for women entrepreneurs and found Melbourne ranked 17th place for its ability to foster women entrepreneurship.

We are looking forward to adding value through our #bbglinkedinforum which we plan to launch in July 2019.




Digital inclusion is one of the three themes of the annual Digital Innovation Festival.  #DIFvic actively encourages underrepresented voices and diverse stories from across the Victoria to be part of the festival. Read more about how our vibrant tech ecosystem is championing diversity. 

Diversity of ideas and people are at the heart of innovation. Including different voices and perspectives in the development process, can deliver surprising results. Diversity and inclusion are increasingly becoming differentiators in business as consumers become aware of who makes and manages the tech they use in their daily lives. Yet the tech sector that creates ground-breaking solutions does not always represent the society which uses them.

To fully realise technologies' transformative potential, everyone needs to be a part of shaping the digital economy. In order to create an inclusive tech ecosystem, organisations and individuals need to be engaged. At the macro level diversity means that all sectors have a seat at the table: business, entrepreneurs, not-for-profit and government. At the micro level individual groups need to be represented and collaborate to create positive change.  

Change is central to innovation and is essential to progress. The Victorian tech ecosystem is proactively addressing the issues of equity across a range of initiatives lead by LaunchVic, Victoria’s startup agency. Focusing on how we go about creating a diverse workforce and empowering underrepresented startup founders. They supported Change Catalyst to create a toolkit that offers best practices for making the tech industry more diverse and inclusive.

Encouraging allyship is another way to drive positive change. An ally is any person that actively promotes and aspires to advance the culture of inclusion through intentional, positive and conscious efforts that benefit people as a whole. According to Sheree Atcheson Award-winning Diversity and Inclusion Leader in her article in Forbes, everyone has the ability to be an ally as privilege is intersectional - white women can be actionable allies to people of colour, men can be allies to women, cis people can be allies to members of the LGBTQI+ community, able-bodied people can be allies to those with different abilities, economically privileged people can be allies to those who are not and so on.  

Gender in tech 

Diversity in the tech world has focused on gender, given the stats it’s not surprising. In Victoria, women are estimated to represent around 20 percent of the State's ICT industry and 30 percent of the workforce. Women continue to be underrepresented in ICT roles, significantly lower than in other professional occupations. Women comprised 28 percent of the national digital technology workforce; a figure that has remained unchanged since 2015 ACS: Australia’s Digital Pulse (2018)  

However, the 2017 Women Entrepreneur Cities Index listed the top 50 cities globally for women entrepreneurs and found Melbourne ranked 17th place for its ability to foster women entrepreneurship. Networks that support women in technology are thriving and the Melbourne chapter of the global Girls in Tech are back with their Catalyst Conference.

Geelong Youth Innovation Summit 2019 (Sat 11 May) and the girledworld WOW STEM Expo Summit 2019 program has been curated and designed just for Australian high school girls and early tertiary women, empowering, educating and equipping them to make informed decisions about their individual career pathways with the new World of Work front of mind.  

Supporting entrepreneurs from diverse backgrounds 

LaunchVic is Victoria’s startup agency and is committed to the development of a globally-connected, diverse and inclusive startup ecosystem. Their third funding round supported programs that improved access and participation in the Victorian startup ecosystem for first-generation migrants and refugees. Another program supported entrepreneurial programs for Aboriginal Victorians, including Barayamal is the world’s first indigenous accelerator is looking for 5 innovative Indigenous startups to give a funding total of $50,000.  See a list of the organisations who are delivering real benefits on the ground.  

Migrants and refugees are important contributors to successful startup ecosystems. They are known to have high-risk appetites, having started a new life in a new country – often with no capital, no credit history, no assets, and no security. The risk-taking that defines a migrant’s experience often continues as they embark on entrepreneurial journeys to establish themselves. 

According to Startup Victoria diversity is the key to success and diverse leadership yields better business performance. Australia is one of the most ethnically diverse countries in the world, and our startups should be the same. Here in Victoria, we want to challenge the norm and lead by embracing diversity in our startups - starting from the top.  

Startup Victoria Pitch Night: Diversity and Inclusion on Tue 28 May will focus on diversity and showcase both leaders and up-and-coming startups that are led by Women, Migrant and Aboriginal and Torres Strait Islander from any industries. Startup Victoria are proud to partner with LaunchVic to showcase 4 diverse startups, as they pitch to a panel of hand-picked, expert judges as well as our usual community of founders, startups, investors and more. They will also be pitching to win the amazing Startup Victoria Prize Package.

Championing the underrepresented in the digital economy 


Melbourne is proudly home to the #TechDiversity awards which raise the profile of those who are building inclusion in the digital economy: to share their stories of courage and commitment, and to amplify their achievements, and to inspire others to act. 

#TechDiversity supports the increased participation of underrepresented groups and embraces women, people with a disability, people who recognize themselves as LGBTQI, Indigenous Australians and Torres Strait Islanders, people of colour, older people, and those who may face discrimination around their religious beliefs. 

The 2019 #TechDiversity Awards are open for nominations launching at RMIT on 15 May. Nominations display outstanding expressions of leadership, behavior, commitment, and courage – key touchstones that embrace inclusion and drive diversity.

2018 winners include Grad Girls a 1-year program run by Vic ICT for Women for female university STEM students to discover and understand the pathways available when taking the next step in their career. If you are raising awareness and creating change through diversity initiatives or programs nominate by 30 June. Who knows, we may see you in the spotlight at the #TechDiversity Awards Gala Dinner on 12 September. Save the date!  

#TechDiversity is a great example of collaboration in action. It is an initiative spearheaded by a core committee of volunteers representing Mia Consulting Services, Method9, Nexec Leaders and MizTee. This core committee is supported by a wider team representing a number of industry groups and businesses – including the Australian Computer Society (ACS), Australian Information Industry Association Victoria (AIIA), Vic ICT for Women and the Victorian Government.

Who's in the spotlight?  

Events are a great way to explore ideas, learn new skills and build networks to challenge the status quo. Many high-profile conferences, events and taskforces lack gender balance, despite there often being no shortage of qualified women. It is estimated less than 15% of panelists in Australia are women. Less than 12% of experts cited in business newspapers are women. Such optics have consequences. There has been push back against #manels, all male speaker panels. The Panel Pledge seeks gender balance at every forum and the tech sector is responding.

Change Catalyst has created a guide to inclusive events and recommends creating programming that speaks to your local community and is oriented towards the topics and conversations that will best serve your audience. Look outside your normal circles to find diverse voices and no matter what your event programming, be sure to provide guidance to your speakers, presenters and facilitators to ensure that your content is created with an inclusive lens.  

Walking the talk, TechInclusion returns to Melbourne this year convening the tech industry to focus on solutions to diversity and inclusion. The theme this year is “Voices of Innovation” – featuring diverse, underrepresented voices building the innovative technologies and cultures of our future. Presented by Change Catalyst and LaunchVic it's an open invitation to learning new solutions, meet diverse people who care, be stretched in a safe environment, and gain new tools and strength to advocate for change. A highlight will be the interactive session focusing on allyship in tech.

This year's program features some great speakers including: Dr Manisha Amin, CEO at Centre for Inclusive Design; Aiman Hamdouna, Founder & Ceo At Hatch Quarter Pty Ltd; Gian Wild, CEO, Founder at Accessibilityoz and Michelle Sheppard, Transgender Community Liaison Officer at Fitted for Work and more.   

If knowledge is power, then Melbourne Knowledge Week is your personal charger. MKW is packed full of interesting talks and events to help grow your mind and feed your curiosity. So make sure you check out what's on between 20 - 26 May around the city. 

DIF2019 Digital Inclusion program 

The DIF Team recommend all Event Partners read the Creating Inclusive Events Guide and consider how to make diversity and inclusion as part of how they approach their own DIF2019 event. All events are encouraged to make all efforts to achieve a gender-balanced program and consider other dimensions of age and international and local experience.  

The DIF Team actively seeks underrepresented voices and diverse stories from across the Victorian tech ecosystem. We work with event partners to identify speakers from diverse backgrounds and the DIF Hub program has an open EOI for speakers. If you’re interested to be a speaker please make sure you register or if have an event that focuses on diversity or inclusion sign up and post it to the DIFvic Online Events Hub.  

This year’s DIF Hub program will have dedicated Women Changing Tech Day and Digital Diversity Day to showcase the amazing people and solutions that are making a difference. Check out the program and spend some time outside of your comfort zone, open your mind to possibilities and step up and make a change for good.  

The DIFvic Online Events Hub digital inclusion events across the state from tech help and coding for kids in libraries, Meetup groups for female entrepreneurs and more are added weekly. You can sign up and create your account, for event alerts to receive a #DIFlist of digital inclusion events to your inbox.

Change Catalyst Reminder: Diversity and Inclusion is a journey, we’re all learning. It’s okay to make mistakes in the process. Listen and learn from the community and continue to improve. Congratulations on taking the first step!

About Kelly Hutchinson 

Kelly is a  self-confessed digital changemaker and ideas hacker. Results-oriented, she constantly envision ways to create shared value and see cross-sector collaboration as the key. 
As an international expert, Kelly harnesses  open innovation approaches to deliver positive change for business and communities. 

Teaching innovation and change management through practical case studies is how Kelly balances research and practice. 

She has ridden the entrepreneurship rollercoaster, working in her Melbourne-based family business and running two tech startups in Cambodia. Currently, Kelly works with the Victorian State Government delivering the Digital Innovation Festival which allows her to champion digital inclusion and emerging technology for the benefit of all.

Thursday, June 13, 2019

Preparing Australia’s workforce for the digital future




Swinburne University of Technology Centre for the New Workforce just released their #futureofwork research report titled Peak Human Potential. One of the most striking, although perhaps not surprising, findings is that those workers in industries that have been digitally disrupted have the most accurate read on the skills needed for the future while those in industries not yet disrupted still value old, outdated models of expertise. The danger lies ahead when those older industries become digitally disrupted and those workers are caught flat footed. New systems of education and learning, new models of integrated work and learning are needed ASAP. 


Link below 


https://bit.ly/2Zgdlaz

Immigration driving Innovation and Growth of the economy



Great Insight from my innovation Guru, Heather Mcgowan 

“In Mary Meeker latest internet report 2019 (all 333 pages) she highlights what Chris Shipley and I have been saying for years. 

#immigration drives our #economy. 60% of our most highly valued technology companies were started by a first or second generation immigrant. #futureofwork #entrepreneurship”