5 Reasons to invest in Digital Documents

invest in digital documentsThis document highlights five major reasons to invest in an enterprise platform like Encanvas that supports the lifecycle of digital documents.

Remastering the document for a digital age

Documents have always been useful to businesses. They are easy to create and use, perform countless roles—by making information easier to capture, process, distribute, share, and store—and, perhaps most importantly, they are a familiar concept that people understand.

Read our article on digital documents and innovation

Intelligent digital documents

The use of intelligent digital documents is on the rise, responding to the demands of digital business. This new digital file construct—that combines document data with design and logic rules whilst still remaining largely autonomous in its use—is breathing new life to the role of documents in businesses.

Digital documents are a form of what Gartner calls a composable application. (Interestingly, composable applications come #5 in Gartner’s top 2022 priorities.)

They are built from business-centric modular components and make it easier to use and reuse data and code, accelerating the time to market for new information solutions and releasing enterprise value.

According to the Gartner report “Adopt a Composable DXP Strategy to Future-Proof Your Tech Stack,” 60% of mainstream organizations will use the composable business model as a strategic objective by 2023.

While digital documents are considered to be essential in the democratization of IT, their autonomy of use is not without rules or governance. Indeed, IT teams have greater control and governance over digital documents than they enjoy with the self-authored apps of citizen developers. But, what this autonomous use does bring is an insane level of versatility in the range of information publishing, management, and processing use cases digital documents can deliver across your business.

Read about intelligent digital documents

Reasons to invest in digital documents

1. Drive business agility

Demands for agility come from the recognition that markets and business models are changing progressively faster. To see change as an opportunity, not a business threat requires an organization to see the need for agility as a constant. This agilization of the enterprise covers all areas including decision-making culture, supply chain, resourcing, people, and not least systems and processes.

The Nordics arm of Deloitte’s took the time in 2021 to conduct detailed research into the importance of business agility to leaders and found that 67 percent of respondents saw business agility as having a high priority across their organization.

Composable technology, like digital documents, cascades access to information—and information sharing and processing tooling—across the enterprise, allowing departments and individuals to craft better ways to analyze data and get things done without calling on IT every time a spreadsheet isn’t the answer.

According to the Gartner report “Adopt a Composable DXP Strategy to Future-Proof Your Tech Stack,” 60% of mainstream organizations will see the composable business model as a strategic objective by 2023.

2. Deliver innovations faster, at lower IT costs, while de-skilling access to information services

Tech talent is hard to find, and the competition is so fierce, leading to a 14% upshift in operating costs in some US states.  Meanwhile, in the UK, the Department for Digital, Culture, Media and Sport (DCMS)  report on the tech skills gap suggests that data analysis is the fastest growing skills cluster in tech and is set to expand by 33% in the next five years.

Applications developments are high-risk and costly. Everyone knows it. Still, the move to make tech solutions—such as mobile apps—an integral part of the customer value offered by digital businesses means every IT function today has a long tail of app dev demands.

Thankfully, digital documents aren’t quite the same as apps. They are more autonomous. They are truly codeless. And, they combine with cloud-native digital cloud spaces and digital data fabrics to allow IT, teams, to retain control over their tech stack, even while providing business stakeholders with the information solutions they need. That’s good news when there’s a global shortage of tech talent.

3. Maximize the value of data

Watch any video of Bezos talking about business, Amazon’s growth, or his own life lessons, and within seconds he will inevitably talk about customer-centricity and the value Amazon derives from data. Extracting value from data—not just gathering it—is critical to any digital business. And it’s in this second phase of ‘harvesting value from data’ that digital documents bring real value.

The challenge most companies face when it comes to data value is threefold:

  1. Executives don’t take data value (or quality) seriously enough as a contributor to business success, and often adopt slack KPI recording of performance in this capability.
  2. The data management and governance across an enterprise—compromised as it is so often by systems and departmental silos—is not ‘composable’ by the business decision-makers that need it.
  3. Executives and information workers lack the autonomy of action—or information management tooling—to maximize data value and use.

Digital documents allow executives and information workers to fully leverage the data at their disposal to answer new questions as they emerge. Additionally, digital documents can capture further enrichment data associated with a subject—by cross-fertilizing with third-party data or adding custom data fields—that brings more value to data.

4. Cascade digital innovations like AI and graph technology to the edge of the enterprise

Since the birth of enterprise computing, the focus on data processing and its use has seesawed between centralized and distributed systems.

This pendulum has been about leveling up cost, availability, and control over IT. That is to say, finding the ideal state between these three core considerations has never been easy.

The general shift over the past few years—thanks in part to cloud computing and big data—has been a move to large-scale centralized processing. But centralized economies and the assumed advantages in data and systems governance served up by cloud computing result in less autonomy and access for information workers to harness and adapt technology to serve business needs at the edge of the enterprise.

5. Rebalance the relationship between IT and THE BUSINESS

The overriding reason digital documents are facing a high pace of adoption within enterprise technical teams comes down to their ability to apply a new and practical balance between business demands and IT priorities.

Since the digital economy landed—and started to place unreasonable demands on IT teams whose resources were already overstretched by business continuity, compliance, and renewal challenges—there has been an unquenchable demand from front-line enterprise departments for more applications. This is hardly surprising; the consumerization of IT made it plain to many businesspeople that the quality of the software they were being served up and asked to live with was far behind the curve of what companies like Google and Facebook were serving up to consumers for free. Information workers of the 1990s were frazzled by having to work late nights with spreadsheets, while fully aware that their databases were perfectly capable of achieving more in less time, and with less hassle.

Digital documents offer digital workers empowerment; that much is reasonably obvious: They don’t have to go to the IT department door with a begging bowl for new applications to work with data. What is less obvious, is how game-changing digital documents are for IT teams. While digital documents are convenient and accessible to the mass of workers in a digital business, for IT professionals with skills, there are no limits to the possibilities to innovate, whilst throwing a veil of robust IT protocols across the enterprise to improve control, data security, applications governance, replication, and scaling safeguards, etc.

Above all, digital documents form a thoughtfully designed balance between the needs of the business, and the needs of IT; one that favors both parties.

3 Technologies Transforming Digital Marketing

3 Technologies Transforming Digital Marketing

In the post-pandemic era, companies are seeking new methods of targeting and connecting to consumers through digital marketing. According to McKinsey, B2B companies are seeing digital interactions as two to three times more important to their customers than traditional sales interactions. Supporting this claim, in the latest round of industry analyst reports, the majority of responding companies are saying that 90% of their sales have moved online. In this article, we highlight three technologies that are helping to transform digital marketing to serve the digitization of the industry.

1. Data-Driven Digital Marketing

Whilst commerce has gone digital, it has not removed the need to understand what matters most to customers. One of the more effective ways of doing this is to capture customer feedback.  Even a decade ago, getting good research data from customers wasn’t easy.  In the digital age, it’s almost impossible for brands to get research surveys completed.  To listen to customers in the 21st century means tapping into their online interactions and profiling their buying behaviors.  It’s about harvesting data from multiple data points to build a picture of what makes buyers tick.

Combining traditional data analysis and visualization tools with big data and machine learning enables companies to build effective data analysis platforms to gain more accurate and real-time understanding of their customers and site visitors.

According to [Wikipedia]—’..big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.’


Machine learning (‘ML’) on the other hand is about writing computer algorithms that improve automatically through experience and by the use of data.  ML technologies have become more affordable and democratized over the past decade, so the number of IT people with ML skills has mushroomed, bringing this technology within reach of companies of all sizes.

Using these digital marketing mechanisms to harvest and rationalize data, marketers are uniquely able to interpret the needs of their target segments and design strategies that help to improve customer experience and satisfaction touching every conversational channel.

For instance, Twitter applies machine learning technology to identify and evaluate tweets in real time and rank them using various metrics to display tweets that have the potential to drive the most active engagement.

2. Automating Digital Marketing with Chatbots

The state of the ‘customer service’ art over the last decade was the human customer service agent. What we’ve seen in recent years has been the proliferation of self-service vehicles for customers, like chat and voice bots.  Today, there are over 300,000 Facebook chatbots and 367% of people on a mobile phone would rather have access to a chatbot to answer emergency questions.

For instance, Twitter applies machine learning technology to identify and evaluate tweets in real time and rank them using various metrics to display tweets that have the potential to drive the most active engagement.

A chat bot is any form of computer program that simulates a natural human conversation. Chatbots allow customers to self-serve their answers quickly. The real fascination these days lies in smart AI chatbots that can understand the intent of enquirers, not just blindly look to capture common phrases in chat text that result in the wrong answers to questions being presented (what practitioners call ‘false positives’).

Chat and voice bots allow companies to go beyond the traditional “one to one” form of customer service with their digital marketing.   Rather, they act upon consumers’ request with speed and accuracy. Another major benefit for organizations looking to serve an always-on buying audience is that chat and voice bots don’t need to rest. They don’t take holidays.  They never go on strike.  Furthermore, resources can be easily scaled to serve peaks in demand.

Chat and voice bots improve customer experience by providing personalized and customized experience across multiple channels. For instance, they can detect user emotions or offer different language options that customers feel comfortable with.  Furthermore, chatbots are proficient in capturing what matters to customers and offer deep insights into buying trends, behaviors, preferences, likes, dislikes, etc.

Voice-based communication solutions are gradually transitioning chatbot use cases to voice bots.  In future, don’t be surprised if your customer service needs are being served up by Siri or Alexa.  Firms can leverage these intelligent voicebots to fully understand consumers’ needs and maximize every voice interaction with relevant and practical care.  Voice applications have more potential to shape brand tone of voice and personality to deepen the emotional connection made with customers and prospects.  

3. Rise of Personalization in Digital Marketing

Digital advertizing has grown to become one of the most important forms of digital marketing and Statista shows that digital advertizing spending worldwide amounted to 378.16 billion U.S. dollars in 2020, increasing significantly compared to the previous years.

The popularity of digital advertizing is unsurprising. Facebook and Google Ad platforms are already using machine learning and data analysis to analyze customer trends and behaviours.  These extend into themes such as interests and demographics to better understand and target different customer segments.

Such techniques allow companies to detect the best and most suitable customers for their products, increasing sales revenue. What’s more, AI enables marketers to personalize their message to customers on an individual level to increase experience and satisfaction.

Business Team

As Meghan Keaney Anderson once said, “don’t push people to where you want to be; meet them where they are.”

The algorithms work by predicting customer behavior based on their past browsing or shopping history. What is changing over this period is the fact that online advertising has gone more and more personal, from mass media advertising to personal targeting. This will help the company generate richer data about their target segments and bring a profound two-way impact.

The Takeaway

These modern digital marketing tools—big data, AI, personalized digital marketing—are transforming the field of digital marketing by equipping companies with deep insights into their customer audiences. Businesses would be wise to invest more in AI to be well-positioned to benefit from the shift in consumer behaviour and advancement in technology. It is important to note that companies have to be the first mover of the technology. As Steward Brand once said,“once a new technology rolls over you, if you’re not part of the steamroller, you’re part of the road”.

Experience codeless enterprise application software

Task Automation or Digital Transformation?

Task Automation or Digital Transformation?

Is it progress if a cannibal uses a fork? Stanislaw Jerzy LecIs

Task automation: Are SaaS and RPA tools distracting you from true progress in your digital transformation?

Task automation is a critical aspect of digital transformation

It’s a funny thing. When leadership teams get wrapped up in software app selection discussions, the PURPOSE of technology can get so easily lost. It’s as if, the more technology options and possibilities come into the foreground, the more they become the SUBJECT, not a CONTRIBUTION to the desired outcome.

Particularly when enterprises are considering a digital transformation, this technology ‘target fixation’ is a real issue.

Leaders have to be technology aware these days – DIGITAL TRANSFORMATION is too big for the CTO alone.

Businesses today live on data and their relationships with customers and suppliers exist as data flows through a software conduit. The technology organizations use defines them to their customers. It also makes a huge impact on profitability (i.e. how efficiently an organization translates its customer value into shareholder returns).

I am always surprised by how many experienced sales and marketing leaders say they are awash with software apps and robotic solutions for task automation. Each of these tools had been selected for doing a particular task or job really well – and I’m sure they do – but the unintended consequential impact of using all of these tools was a paucity of technology that did little more than distract from their core agenda.

The world of business computing has shifted from a discussion around best-of-breed apps to solve particular needs, to looking more holistically at business models and how enterprises can maximize customer experience and shareholder returns with a single, unifying platform.

How to tackle task automation

There are several ways leadership teams can tackle the automation and ‘digitalization’ of their enterprise.

One option is to start from the ground-roots, looking at the task-related problems of work activities and lever in new tech-tools like Robotic Process Automation (RPA) to make improvements one task at a time. The challenges this ground-up approach fosters include a lack of control afforded to IT and compliance teams over data, the increased risk of silos of data and activities being created, and the probability that any step-change in workflow design (or new tools and mechanisms) could obviate the need for these low-level tasks completely! There is a big risk that internal (and external) sponsors of technology tools will FIND more and more task automation opportunities to justify the time and spend on solutions, distorting how resources are being used to achieve departmental ends not enterprise level outcomes.

How to tackle task automation

There are several ways leadership teams can tackle the task automation and ‘digitalization’ of their enterprise.

The Bottom Up Approach

 One option is to start from the ground-roots, looking at the task-related problems of work activities and lever in new tech-tools like Robotic Process Automation (RPA) to make improvements one task at a time.

The challenges this ground-up task automation approach fosters include a lack of control afforded to IT and compliance teams over data, the increased risk of silos of data and activities being created, and the probability that any step-change in workflow design (or new tools and mechanisms) could obviate the need for these low-level tasks completely!

There is a big risk that internal (and external) sponsors of technology tools will FIND more and more task automation opportunities to justify the time and spend on solutions, distorting how resources are being used to achieve departmental ends not enterprise level outcomes.

Digital transformation drives data re-use

Another task automation option is to explore your current use of hard-copy documents and any document workflows.

With document and business process management solutions, enterprises are able to turn their traditional paper-based workflows into a digital (superior) alternative, sometimes installing machine-to-machine processing and eradicating the need for humans to take on the role of ‘sub-processors’ or ‘glue-ware.’  

Getting task automation right 

How is your enterprise moving ahead with its digital transformation? And is it starting at the right level?

Unless organizations have established a digital transformation governance team, the probability is that task automation falls to departmental managers and portfolio holders that are rewarded on the performance of their silo.  Inevitably, when in search of quick-wins, the likely consequence of this lack of top-down control is that middle-managers will focus on plugging gaps and short-terms economies rather than step back and revisit the big picture.

Equipping teams and individuals with the SaaS apps they need (or like to use) might well be creating far too many rabbit holes for leadership teams to get lost in.  Re-visiting business model designs and then considering a digital orchestration using a unifying applications design and deployment platform may sound like a longer-term agenda but the alternatives may just turn task automation into a task itself.

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About Ian Tomlin

Ian Tomlin is a management consultant and strategist specializing in helping organizational leadership teams to grow by telling their story, designing and orchestrating their business models, and making conversation with customers and communities. He serves on the management team of Encanvas and works as a virtual CMO and board adviser for tech companies in Europe, America and Canada. He can be contacted via his LinkedIn profile or follow him on Twitter.

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Two-Speed IT Or Not, That Is The Question

It’s no secret that creating digital platforms and ecosystems demands a faster paced-IT capability.  But is moving to a two-speed IT model the best way to go?

IT leaders are challenged to keep innovating while over 60% of IT budgets remain focused on keeping the lights on.  Consumers and workers alike expect apps that ‘just work’. They expect IT innovators to rapidly source always-on, powerful, and instantly intuitive solutions to capture, access, manage, and share information.

To keep pace with the need for near-constant digital re-invention, a new kind of IT rapid DevOps team is needed and a ‘fail-fast’ prototyping approach that in itself requires a high-productivity applications platform to support it.

Management teams recognize that they can’t ignore the importance of digital technologies and their influence on markets and business models. Organizations have a stark choice; to embrace digital, or die.

Buy or Build

In this new digital market reality, enterprises are faced with the option to buy an existing digital platform and ecosystem to support their business model orchestration, or build their own. In most cases, the only way for organizations to achieve a competitive edge is to do the latter.  Recognition of this change makes IT an intrinsic core competency of any business, not a support department only there to keep the lights on.

McKinsey & Co. suggest companies with digital platforms enjoyed an annual boost in earnings before interest and taxes (EBIT) of 1.4 percent, compared with the 0.3 percent gains of non-players.  They go on to state that performance effects are cumulative, with EBIT improvements adding to early-year gains, so over a five- year period, platform players may capture an additional 10 percent in EBIT growth—a company’s 2 percent EBIT growth, for example, would increase to 2.2 percent in year five.

 ‘The right digital-platform strategy’, Insights Report, McKinsey & Co, May 2019

DevOps – The Right Approach?

Enterprises are creating DevOps teams to support and speed up their digital transformation, embracing digital innovation, enabling them to reduce operation costs.  Sometimes, these teams are carved out of existing in-house resources and continue to report to the IT department, but in other cases, Chief Digital Officer (CDO) roles are appointed to ensure a new culture is stitched into the design of this key enabling team.

Which Route? Two-Speed or Integrated?

It’s only an opinion, but my experience of two-speed team structures for digital transformation hasn’t been satisfactory. There’s a risk that some great people get left in the ‘slow-speed’ IT team that end up feeling disenfranchised. Also, the leadership of the two teams can end up squabbling. creating disruption and distractions that are at best unhelpful.  That said, if both teams accept that their roles are important, and the right personalities are placed in the right seats, perhaps it could work.

The Third Way

My preference is a third project structure. It’s what German companies call the ‘Organization Department’.  It’s a department responsible for managing change – a continuous improvement team that includes IT, analysts, legal, HR, marketing,and program management competencies in a single unifying team that sits within the body corporate led not by IT but the CEO. 

Why this structure?  Because agility in business these days is a process.  It has a life-cycle like any other process. Organizations must accept that change is not an intervention, it’s an always-on aspect of organizational performance.

Use Encanvas AppFabric to supercharge your Digital Transformation


88% of businesses say they are already under-going a digital transformation


On average middle-managers spend a quarter of their time searching for information... only to find that 50% of the data they find has no value


47% of job categories may be taken over by machines in the next two decades.


85% of businesses believe that cloud technology will transform their business or industry


On average over 60% of enterprise budget is spent on 'keeping the lights on' technology


40% of business managers cite a lack of urgency in the company as the biggest barrier to digital transformation


1. Altimeter Group Digital Transformation Survey
2. University of Oxford
3. Gartner (2112)
4. Gartner (2112)
5. Oxford Economics and SAP (2012)
6. MIT Sloan Mgmt. Review

 Tool Kits Matter

Without the right tool kit, it’s not sensible or practical to consider in-house development of the technology you’ll need to orchestrate your business model.  When businesses continue to use manual coding of apps, they inevitably fall foul of its inherent weaknesses.

Encanvas software, and similar tools like Mendix, ServiceNow, and OutSystems equip businesses with the ability to design, deploy and run their own self-authored apps.  Encanvas is specifically engineered to support the project process for orchestrating business models through a series of software developments modules.  This way, it removes the technology obstacles of creating enterprise-scale applications, such as coding, integrating, and testing new applications.

Live Wireframing Make Fail Fast Prototyping Affordable

a fundamental principle of rapid app development is that it’s best to start small with the minimum set of requirements and get something working so it starts delivering value.  The alternative to this is building a mammoth software requirements specification (SRS) document that conjures up so many ‘nice-to-have’ features that it becomes impossible to economically produce.  When creating a best-fit app module, involving stakeholders (ie Customers, Partners, Users) directly in the design process always works better.

Removing code and presenting WYSIWYG results in a workshop environment is the best way to do this.

A Live Wireframe is a fully functioning application prototype (pre-UAT) that proves the red-flag issues that the project team determines as being the biggest risks to project success.  The task of producing a Live-Wireframe is performed by having stakeholders work ‘across-the-desk’ with a business analyst who creates the resulting live-wireframe design in near-real-time.

As soon as line-of-business stakeholders get presented with a screen of code, they shy away from feeling they should contribute to the development process – it’s just too overwhelming.  With Live Wireframes, stakeholders get to see during the design workshop, the live system they’re going to be using in all of its glory.  Seeing instant results makes an enormous difference to project success, but it requires built-for-purpose development tools; a unifying design and deployment ecosystem that removes the need for IT to master a dozen different technology components before they can produce any outcome.

Two-Speed IT is unnecessary when enterprises create an Organization Department and install a culture of prototyping by employing Live Wireframes. This way digital platform design and management becomes an embedded capability of the enterprise, ensuring agility is seen as a constant (and is appropriately resourced).

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Ian Tomlin

Ian Tomlin


Ian Tomlin is a marketer, entrepreneur, business leader and management consultant. His passion is to help make great ideas happen. Relentlessly optimistic about the potential of technology for good, Ian’s 30+ year career has focused around the intersect of strategy, technology and marketing. He writes on subjects including enterprise computing and organizational design. He also works as a consultant and advisor to the executive teams of PrinSIX Technologies, Answer Pay and INTNT.AI, helping to rethink their marketing in order to tell their brand story.

Ian has founded a series of successful businesses including NDMC Ltd (2003), Encanvas (2006), and Newton Day Ltd (2019). He has written books, articles and guides on brand, digital transformation, enterprise applications, data science, workforce management, and organizational design. He can be reached via LinkedIn or Twitter.