Intelligent Capture für die digitale Transformation: my intelligent capture paper for @ABBYY_Software, now in German

A little over a year ago, I wrote a paper on intelligent capture for digital transformation, sponsored by ABBYY, and gave a keynote at their conference on the same topic. The original English version is on their site here, and if you read German (or want to pass it along to German-speaking colleagues), you can find the German version here. As usual, this paper is not about ABBYY’s products, but about how intelligent capture is the on-ramp for any type of automated processes and hence required for digital transformation. From the abstract:

Data capture from paper or electronic documents is an essential step for most business processes, and often is the initiator for customer-facing business processes. Capture has traditionally required human effort – data entry workers transcribing information from paper documents, or copying and pasting text from electronic documents – to expose information for downstream processing. These manual capture methods are inefficient and error-prone, but more importantly, they hinder customer engagement and self-service by placing an unnecessary barrier between customers and the processes that serve them.

Intelligent capture – including recognition, document classification, data extraction and text analytics – replaces manual capture with fully-automated conversion of documents to business-ready data. This streamlines the essential link between customers and your business, enhancing the customer journey and enabling digital transformation of customer-facing processes.

Or, in German:

Die Erfassung von Daten aus papierbasierten oder elektronischen Dokumenten steht als
zentraler Schritt am Anfang zahlreicher kundenorientierter Geschäftsprozesse. Dies ist üblicherweise
mit großem manuellen Aufwand verbunden – Mitarbeiter übertragen und kopieren
per Hand Daten und Texte, um sie so nachgelagerten Systemen und Prozessen zur Verfügung
zu stellen. Diese manuelle Vorgehensweise ist jedoch nicht nur ineffizient und fehleranfällig,
sie bremst auch den Kundendialog aus und verhindert Self-Service-Szenarien durch unnötige
Barrieren zwischen Kunden und Dienstleistern. Intelligent-Capture-Lösungen – mit Texterkennung,
Dokumentenklassifizierung, Datenextraktion und Textanalyse – ersetzen die manuelle
Datenerfassung. Dokumente werden vollautomatisch in geschäftlich nutzbare Daten umgewandelt.
So können Unternehmen die Beziehung zu ihren Kunden stärken, das Benutzererlebnis
steigern und die digitale Transformation kundenorientierter Prozesse vorantreiben.

Recently, I was interviewed by KVD, a major European professional association for customer service professionals. Although most of their publication is in German, the interview was in English, and you can find it on their site here.

ITESOFT | W4 Secure Capture and Process Automation digital business platform

It’s been three years since I looked at ITESOFT | W4’s BPMN+ product, which was prior to W4’s acquisition by ITESOFT. At that time, I had just seen W4 for the first time at bpmNEXT 2014, and had this to say about it:

For the last demo of this session, Jean-Loup Comeliau of W4 on their BPMN+ product, which provides model-driven development using BPMN 2, UML 2, CMIS and other standards to generate web-based process applications without generating code: the engine interprets and executes the models directly. The BPMN modeling is pretty standard compared to other process modeling tools, but they also allow UML modeling of the data objects within the process model; I see this in more complete stack tools such as TIBCO’s, but this is less common from the smaller BPM vendors. Resources can be assigned to user tasks using various rules, and user interface forms are generated based on the activities and data models, and can be modified if required. The entire application is deployed as a web application. The data-centricity is key, since if the models change, the interface and application will automatically update to match. There is definitely a strong message here on the role of standards, and how we need more than just BPMN if we’re going to have fully model-driven application development.

A couple of weeks ago, I spoke with Laurent Hénault and François Bonnet (the latter whom I met when he demoed at bpmNEXT in 2015 and 2016) about what’s happened in their product since then. From their company beginnings over 30 years ago in document capture and workflow, they have expanded their platform capabilities and relabelled it as digital process automation since it goes beyond BPM technology, a trend I’m seeing with many other BPM vendors. It’s not clear how many of their 650+ customers are using many of the capabilities of the new platform versus just their traditional imaging and workflow functions, but they seem to be expanding on the original capabilities rather than replacing them, which will make transitioning customers easier.

31 ITESOFT W4 platform as part of enterprise architectureThe new platform, Secure Capture and Process Automation (SCPA), provides capabilities for capture, business automation (process, content and decisions), analytics and collaborative modeling, and adds some nice extras in the area of document recognition, fraud detection and computer-aided process design. Using the three technology pillars of omni-channel capture, process automation, and document fraud detection, they offer several solutions including eContract for paperless customer purchase contracts, including automatic fraud detection on documents uploaded by the customer; and the cloud-based Streamline for Invoices for automated invoice processing.

Their eContract solution provides online forms with e-signature, document capture, creation of an eIDAS-compliant contract and other services required to complete a complex purchase contract bundled into a single digital case. The example shown was an online used car purchase with the car loan offered as part of the contract process: by bundling all components of the contract and the loan into a single online transaction, they were able to double the purchase close rate. Their document fraud detection comes into play here, using graphometric handwriting analysis and content verification to detect if a document uploaded by a potential customer has been falsified or modified. Many different types of documents can be analyzed for potential fraud based on content: government ID, tax forms, pay slips, bank information, and public utility invoices may contain information in multiple formats (e.g., plain text plus encoded barcode); other documents such as medical records often contain publicly-available information such as the practitioner’s registration ID. They have a paper available for more information on combatting incoming document fraud.

07 ITESOFT W4 Verifiable documentsTheir invoice processing solution also relies heavily on understanding certain types of documents: 650,000 different supplier invoice types are recognized, and they maintain a shared supplier database in their cloud capture environment to allow these formats to be added and modified for use by all of their invoice processing customers. There’s also a learning environment to capture new invoice types as they occur. Keep in mind that the heavy lifting in invoice processing is all around interpreting the vendor invoice: once you have that sorted out, the rest of the process of interacting with the A/P system is straightforward, and the payment of most invoices that relate to a purchase order can be fully automated. Streamline for Invoices won the Accounts Payable/Invoicing product of the year at the 2017 Document Manager Awards.

After a discussion of their solutions and some case studies, we dug into a more technical demo. A few highlights:

  • 09 ITESOFT W4 Web Modeler - concurrent updates of modelThe Web Modeler provides a fully BPMN-compliant collaborative process modeling environment, with synchronous model changes and (persistent) discussion thread between users. This is a standalone business analyst tool, and the model must be exported as a BPMN file for import to the engine for execution, so there’s no round-tripping. A cool feature is the ability to scroll back through the history of changes to the model by dragging a timeline slider: each changed snapshot is shown with the specific author.
  • Once the business analyst’s process model has been imported into the BPMN+ Composer tool, the full application can be designed: data model, full process model, low code forms-based user experience, and custom code (if required). This allows a more complex BPMN model to be integrated into a low code application – something that isn’t allowed by many of the low code platforms that provide only simple linear flows – as well as developer code for “beyond the norm” integration such as external portals.
  • Supervisor dashboards provide human task monitoring, including task assignment rules and skills matrix that can be changed in real time, and performance statistics.

The applications developed with their tools generally fall into the case management category, although they are document/data based rather than CMMN. Like many BPM vendors, they are finding that there is not the same level of customer demand for CMMN as there was for BPMN, and data-driven case management paradigms are often more understandable to business people.

They’ve OEM’d some of the components (the capture OCR, which is from ABBYY, and the web modeler from another French company) but put them together into a seamless offering. The platform is built on a standard Java stack; some of the components can be scaled independently and containerized (using Microsoft Azure), allowing customers to choose which data should exist on which private and public cloud infrastructure.

ITESOFT | W4 SCPA 2017-12 briefing

28 ITESOFT W4 timeline demoThey also showed some of the features that they demoed at the 2017 bpmNEXT (which I unfortunately missed): process guidance and correction that goes beyond just BPMN validation to attempt to add data elements, missing tasks, missing pathways and more; a GANTT-type timeline model of a process (which I’ve seen in BPLogix for years, but is sadly absent in many products) to show expected completion times and bottlenecks, and the same visualization directly in a live instance that auto-updates as tasks are completed within the instance. I’m not sure if these features are fully available in the commercial product, but they show some interesting views on providing automated assistance to process modeling.


OpenText Enterprise World keynote with @markbarrenechea

I’m at OpenText Enterprise World 2017  in Toronto; there is very little motivating me to attend the endless stream of conferences in Vegas, but this one is in my backyard. There have been a couple of days of partner summit and customer training, but this is the first day of the general conference.

We kicked off with a keynote hosted by OpenText CEO/CTO Mark Barrenechea, who presented some ideas on his own and invited others to the stage to chat or present as well. He talked about world-changing concepts that we may see start to have a significant impact over the next decade:

  • Robotics
  • Internet of things
  • Internet of money (virtual and alternative currencies)
  • Artificial intelligence
  • Mobile eating the world
  • New business models
  • Living to 150
  • IQ of 1000, where human intelligence and capabilities will be augmented by machines

He positions OpenText as a leading provider of enterprise information management technologies for digital transformation, leveraging the rapid convergence of connectivity, automation and computing power. My issue with OpenText is that they have grown primarily through acquisitions – a LOT of acquisitions – and the product portfolio is vast and overlapping. OpenText Cloud is a fundamental platform, which makes a lot of sense for them with the amount of B2B integration that their tools support, as well as the push to private, hybrid and public cloud by many organizations. They see documents (whether human or machine created) as fundamental business artifacts and therfore content management is a primary capability, but there are a few different products that fall into their ECM category and I’m not sure of the degree of overlap, for example, with the recently-acquired Documentum and some of their other ECM assets. Application development is also a key category for them, with a few different products including their Appworks low-code environment. The story gets a bit simpler with their information network for inter-enterprise connectivity, new acquisition Covisint for managing IoT messages and actions, and newly-released Magellan for analytics.

He interviewed two customers on their business and use of OpenText products:

  • Kristijan Jarc, VP of Digital at KUKA, a robotics company serving a variety of vertical industries, from welding in automotive manufacturing to medical applications. Jarc’s team develops digital strategies and solutions that help their internal teams build better products, often related to how data collected from the robots is used for analytics and preventative maintenance, and they’re using OpenText technology to capture and store that data.
  • Sarah Shortreed, CIO of Bruce Power, which runs a farm of 8 CANDU reactors that generate 30% of Ontario’s electrical power. They’re in the process of refurbishing the plant, some parts of which are 40 years old, which is allowing more data to be collected from more of their assets in realtime. They have much tighter security restrictions than most organizations, and much longer planning cycles, making enterprise information management a critical capability.

Barrenechea hosted three other OpenText people to give demos (I forgot to note the names, but if anyone can add them in a comment, I’ll update this post); I’ve just put in a couple of notes for each trying to capture the essence of the demo and the technologies that they were showcasing:

  • Magellan analytics for a car-share company: targeted marketing, demand and utilization, and proactive maintenance via different algorithms. Automated clustering, trend derivation within a selected dataset to determine the target market for a campaign. Allow data scientists to open notebooks and directly program in Python, R, Scala to create own algorithms by calling Magellen APIs. Use linear regression on historical usage data and weather forecasts to forecast demand. IoT streaming diagnostics from vehicles to predict likelihood of breakdown and take appropriate automated actions to remove cars from service and schedule maintenance.
  • People Center app built on Appworks. Integrated with HRIs including SAP, SuccessFactors, Workday, Oracle for core HR transactions; People Center adds the unstructured data including documents to create the entire employee file. Manage recruitment and onboarding processes. Magellan analytics to match resumes to open positions using proximity-based matching. Identify employees at risk of leaving using logistic regression.
  • KUKA iiwa robot sending IoT data to cloud for viewing through dashboard, analytics to identify possible problems. Field service tech accesses manuals and reference materials via content platform. Case management foldering to collect and view documents related to a maintenance incident. Collaborative chat within maintenance case to allow product specialist to assist field tech. Future AI application: automatically find and rank related cases and highlight relevant information.

The keynote ended with Barrenechea interviewing Wayne Gretzky, which was a delightful conversation although unrelated to any of the technology topics. However, Gretzky did talk about the importance of teamwork, and how working with people who are better than you at something makes you better at what you do. You could also see analogies in business when he talked about changes in the sport of hockey: globalization, expanding markets, and competition is getting bigger and meaner. As a guy who spent a lot of the early part of his hockey career as the smallest guy on the ice, he learned how to hone his intelligence about the game to be a winner in spite of the more traditional strengths of his competitors: a good lesson for all of us.

Smart City initiative with @TorontoComms at BigDataTO

Winding down the second day of Big Data Toronto, Stewart Bond of IDC Canada interviewed Michael Kolm, newly-appointed Chief Transformation Officer at the city of Toronto, on the Smart City initiative. This initiative is in part about using “smart” technology – by which he appears to mean well-designed, consumer-facing applications – as well as good mobile infrastructure to support an ecosystem of startup and other small businesses for creating new technology solutions. He gave an example from the city’s transportation department, where historical data is used to analyze traffic patterns, allowing for optimization of traffic flow and predictive modeling for future traffic needs due to new development. This includes input in projects such as the King Street Pilot Study that is going into effect later this year, that will restrict private vehicle traffic on a stretch of King in order to optimize streetcar and pedestrian flows. In general, the city has no plan to monetize data, but prefer to use city-owned data (which is, of course, owned by the public) to foster growth through Open Data initiatives.

There were some questions about how the city will deal with autonomous vehicles, short-term (e.g., AirBnB) rentals and other areas where advancing technology is colliding with public policies. Kolm also spoke about how the city needs to work with the startup/small business community for bringing innovation into municipal government services, and also how our extensive network of public libraries are an untapped potential channel for civic engagement. For more on digital transformation in the city of Toronto, check out my posts on the TechnicityTO conference from a few months back.

I was going to follow this session with the one on intelligent buildings and connected communities by someone from Tridel, which likely would have made an interesting complement to this presentation, but unfortunately the speaker had to cancel at the last minute. That gives me a free hour to crouch in a hallway by an electrical outlet to charge my phone. Winking smile

AIIM breakfast meeting on Feb 16: digital transformation and intelligent capture

AIIM TorontoI’m speaking at the AIIM breakfast meeting in Toronto on February 16, with an updated version of the presentation that I gave at the ABBYY conference in November on digital transformation and intelligent capture. ABBYY is generously sponsoring this meeting and will give a brief presentation/demo on their intelligent capture and text analytics products after my presentation.

Here’s the description of my talk:

This presentation will look at how digital transformation is increasing the value of capture and text analytics, recognizing that these technologies provide an “on ramp” to the intelligent, automated processes that underlie digital transformation. Using examples from financial services and retail companies, we will examine the key attributes of this digital transformation. We will review step-by-step, the role of intelligent capture in digital transformation, showing how a customer-facing financial services process is changed by intelligent capture technologies. We will finish with a discussion of the challenges of introducing intelligent capture technologies as part of a digital transformation initiative.

You can register to attend here, and there’s a discount if you’re an AIIM member.

You can read about last month’s meeting here, which featured Jason Bero of Microsoft talking about SharePoint and related Microsoft technologies that are used for classification, preservation, protection and disposal of information assets.

TechnicityTO 2016: Challenges, Opportunities and Change Agents

The day at Technicity 2016 finished up with two panels: the first on challenges and opportunities, and the second on digital change agents.

The challenges and opportunities panel, moderated by Jim Love of IT World Canada, was more of a fireside chat with Rob Meikle, CIO at City of Toronto, and Mike Williams, GM of Economic Development and Culture, both of whom we heard from in the introduction this morning. Williams noted that they moved from an environment of few policies and fewer investements under the previous administration to a more structured and forward-thinking environment under Mayor John Tory, and that this introduced a number of IT challenges; although the City can’t really fail in the way that a business can fail, it can be ineffective at serving its constituents. Meikle added that they have a $12B operating budget and $33B in capital investments, so we’re not talking about small numbers: even at those levels, there needs to be a fair amount of justification that a solution will solve a civic problem rather than just buying more stuff. This is not just a challenge for the City, but for the vendors that provide those solutions.

There are a number of pillars to technological advancement that the City is striving to establish:

  • be technologically advanced and efficient in their internal operations
  • understand and address digital divides that exist amongst residents
  • create an infrastructure of talent and services that can draw investment and business to the City

This last point becomes a bit controversial at times, when there is a lack of understanding of why City officials need to travel to promote the City’s capabilities, or support private industry through incubators. Digital technology is how we will survive and thrive in the future, so promoting technology initiatives has widespread benefits.

There was a discussion about talent: both people who work for the City, and bringing in businesses that draw private-sector talent. Our now-vibrant downtown core is attractive for tech companies and their employees, fueled by our attendance at our universities. The City still has challenges with procurement to bring in external services and solutions: Williams admitted that their processes need improvement, and are hampered by cumbersome procurement rules. Democracy is messy, and it slows things down that could probably be done a lot faster in a less free state: a reasonable trade. 🙂

The last session of the day looked at examples of digital change agents in Toronto, moderated by Fawn Annan of IT World Canada, and featuring Inspector Shawna Coxon of the Toronto Police Service, Pam Ryan from Service Development & Innovation at the Toronto Public Library, Kristina Verner, Director Intelligent Communities of Waterfront Toronto, and Sara Diamond, President of OCAD University. I’m a consumer and a supporter of City services such as these, and I love seeing the new ways that they’re using to include all residents and advance technology. Examples of initiatives include fiber broadband for all waterfront community residences regardless of income level; providing mobile information access to neighbourhood police officers to allow them to get out of their cars and better engage with the community; integrating arts and design education with STEM for projects such as transit and urban planning (STEAM is the new STEM); and digital innovation hubs at some library branches to provide community access to high-tech gadgets such as 3D printers.

There was a great discussion about what it takes to be a digital innovator in these contexts: it’s as much about people, culture and inclusion as it is about technology. There are always challenges in measuring success: metrics need to include the public’s opinion of these agencies and their digital initiatives, an assessment of the impact of innovation on participants, as well as more traditional factors such as number of constituents served.

That’s it for Technicity 2016, and kudos to IT World Canada and the City of Toronto for putting this day together. I’ve been to a couple of Technicity conferences in the past, and always enjoy them. Although I rarely do work for the public sector in my consulting business, I really enjoy seeing how digital transformation is occuring in that sector; I also like hearing how my great city is getting better.

TechnicityTO 2016: Open data driving business opportunities

Our afternoon at Technicity 2016 started with a panel on open data, moderated by Andrew Eppich, managing director of Equinix Canada, and featuring Nosa Eno-Brown, manager of Open Government Office at Ontario’s Treasury Board Secretariat, Lan Nguyen, deputy CIO at City of Toronto, and Bianca Wylie of the Open Data Institute Toronto. Nguyen started out talking about how data is a key asset to the city: they have a ton of it gathered from over 800 systems, and are actively working at establishing data governance and how it can best be used. The city wants to have a platform for consuming this data that will allow it to be properly managed (e.g., from a privacy standpoint) while making it available to the appropriate entities. Eno-Brown followed with a description of the province’s initiatives in open data, which includes a full catalog of their data sets including both open and closed data sets. Many of the provincial agencies such as the LCBO are also releasing their data sets as part of this initiative, and there’s a need to ensure that standards are used regarding the availability and format of the data in order to enable its consumption. Wylie covered more about open data initiatives in general: the data needs to be free to access, machine-consumable (typically not in PDF, for example), and free to use and distribute as part of public applications. I use a few apps that use City of Toronto open data, including the one that tells me when my streetcar is arriving; we would definitely not have apps like this if we waited for the City to build them, and open data allows them to evolve in the private sector. Even though those apps don’t generate direct revenue for the City, success of the private businesses that build them does result in indirect benefits: tax revenue, reduction in calls/inquiries to government offices, and a more vibrant digital ecosystem.

Although data privacy and security are important, these are often used as excuses for not sharing data when an entity benefits unduly by keeping it private: the MLS comes to mind with the recent fight to open up real estate listings and sale data. Nguyen repeated the City’s plan to build a platform for sharing open data in a more standard fashion, but didn’t directly address the issue of opening up data that is currently held as private. Eno-Brown more directly addressed the protectionist attitude of many public servants towards their data, and how that is changing as more information becomes available through a variety of online sources: if you can Google it and find it online, what’s the sense in not releasing the data set in a standard format? They perform risk assessments before releasing data sets, which can result in some data cleansing and redaction, but they are focused on finding a way to release the data if all feasible. Interestingly, many of the consumers of Ontario’s open data are government of Ontario employees: it’s the best way for them to find the data that they need to do their daily work. Wylie addressed the people and cultural issues of releasing open data, and how understanding what people are trying to do with the data can facilitate its release. Open data for business and open data for government are not two different things: they should be covered under the same initiatives, and private-public partnerships leveraged where possible to make the process more effective and less costly. She also pointed out that shared data — that is, within and between government agencies — still has a long ways to go, and should be prioritized over open data where it can help serve constituents better.

The issue of analytics came up near the end of the panel: Nguyen noted that it’s not just the data, but what insights can be derived from the data in order to drive actions and policies. Personally, I believe that this is well-served by opening up the raw data to the public, where it will be analyzed far more thoroughly than the City is likely to do themselves. I agree with her premise that open data should be used to drive socioeconomic innovation, which supports my idea that many of the apps and analysis are likely to emerge from outside the government, but likely only if more complete raw data are released rather than pre-aggregated data.

TechnicityTO 2016: IoT and Digital Transformation

I missed a couple of sessions, but made it back to Technicity in time for a panel on IoT moderated by Michael Ball of AGF Investments, featuring Zahra Rajani, VP Digital Experience at Jackman Reinvents, Ryan Lanyon, Autonomous Vehicle Working Group at City of Toronto, and Alex Miller, President of Esri Canada. The title of the panel is Drones, Driverless Cars and IoT, with a focus is on how intelligent devices are interacting with citizens in the context of a smart city. I used to work in remote sensing and geographic information systems (GIS), and having the head of Esri Canada talk about how GIS acts as a smart fabric on which these devices live is particularly interesting to me. Miller talked about how there needs to be a framework and processes for enabling smarter communities, from observation and measurement, data integation and management, visualization and mapping, analysis and modeling, planning and design, and decision-making, all the way to action. The vision is a self-aware community, where smart devices that are built into infrastructure and buildings can feed back into an integrated view that can inform and decide.

Lanyon talked about autonomous cars in the City of Toronto, from the standpoint of the required technology, public opinion, and cultural changes away from individual car ownership. Rajani followed with a brief on potential digital experiences that brands create for consumers, then we circled back to the other two participants about how the city can explore private-public sensor data sharing, whether for cars or retail stores or drones. They also discussed issues of drones in the city: not just regulations and safety, but the issue of sharing space both on and above the ground in a dense downtown core. A golf cart-sized pizza delivery robot is fine for the suburbs with few pedestrians, but just won’t work on Bay Street at rush hour.

The panel finished with a discussion on IoT for buildings, and the advantages of “sensorizing” our buildings. It goes back to being able to gather better data, whether it’s external local factors like pollution and traffic, internal measurements such as energy consumption, or visitor stats via beacons. There are various uses for the data collected, both by public and private sector organizations, but you can be sure that a lot of this ends up in those silos that Mark Fox referred to earlier today.

The morning finished with a keynote by John Tory, the mayor of Toronto. This week’s shuffling of City Council duties included designating Councillor Michelle Holland as Advocate for the Innovation Economy, since Tory feels that the city is not doing enough to enable innovation for the benefit of residents. Part of this is encouraging and supporting technology startups, but it’s also about bringing better technology to bear on digital constituent engagement. Just as I see with my private-sector clients, online customer experiences for many services are poor, internal processes are manual, and a lot of things only exist on paper. New digital services are starting to emerge at the city, but it’s a bit of a slow process and there’s a long road of innovation ahead. Toronto has made committments to innovation in technology as well as arts and culture, and is actively seeking to bring in new players and new investments. Tory sees the Kitchener-Waterloo technology corridor as a partner with the Toronto technology ecosystem, not a competitor: building a 21st century city requires bring the best tools and skills to bear on solving civic problems, and leveraging technology from Canadian companies brings benefits on both sides. We need to keep moving forward to turn Toronto into a genuinely smart city to better serve constituents and to save money at the same time, keeping us near or at the top of livable city rankings. He also promised that he will step down after a second term, if he gets it. 🙂

Breaking now for lunch, with afternoon sessions on open data and digital change agents.

By the way, I’m blogging using the WordPress Android app on a Nexus tablet today (aided by a Microsoft Universal Foldable Keyboard), which is great except it doesn’t have spell checking. I’ll review these posts later and fix typos.

Exploring City of Toronto’s Digital Transformation at TechnicityTO 2016

I’m attending the Technicity conference today in Toronto, which focuses on the digital transformation efforts in our city. I’m interested in this both as a technologist, since much of my work is related to digital transformation, and as a citizen who lives in the downtown area and makes use of a lot of city services.

After brief introductions by Fawn Annan, President and CMO of IT World Canada (the event sponsor), Mike Williams, GM of Economic Development and Culture with City of Toronto, and Rob Meikle, CIO at City of Toronto, we had an opening keynote from Mark Fox, professor of Urban Systems Engineering at University of Toronto, on how to use open city data to fix civic problems.

Fox characterized the issues facing digital transformation as potholes and sinkholes: the former are a bit more cosmetic and can be easily paved over, while the latter indicate that some infrastructure change is required. Cities are, he pointed out, not rocket science: they’re much more complex than rocket science. As systems, cities are complicated as well as complex, with many different subsystems and components spanning people, information and technology. He showed a number of standard smart city architectures put forward by both vendors and governments, and emphasized that data is at the heart of everything.

He covered several points about data:

  • Sparseness: the data that we collect is only a small subset of what we need, it’s often stored in silos and not easily accessed by other areas, and it’s frequently lost (or inaccessible) after a period of time. In other words, some of the sparseness is due to poor design, and some is due to poor data management hygiene.
  • Premature aggregation, wherein raw data is aggregated spatially, temporally and categorically when you think you know what people want from the data, removing their ability to do their own analysis on the raw data.
  • Interoperability and the ability to compare information between municipalities, even for something as simple as date fields and other attributes. Standards for these data sets need to be established and used by municipalities in order to allow meaningful data comparisons.
  •  Completeness of open data, that is, what data that a government chooses to make available, and whether it is available as raw data or in aggregate. This needs to be driven by what problems that the consumers of the open data are trying to solve.
  • Visualization, which is straightforward when you have a couple of data sets, but much more difficult when you are combining many data sets — his example was the City of Edmonton using 233 data sets to come up with crime and safety measures.
  • Governments often feel a sense of entitlement about their data, such that they choose to hold back more than they should, whereas they should be in the business of empowering citizens to use this data to solve civic problems.

Smart cities can’t be managed in a strict sense, Fox believes, but rather it’s a matter of managing complexity and uncertainty. We need to understand the behaviours that we want the system (i.e., the smart city) to exhibit, and work towards achieving those. This is more than just sensing the environment, but also understanding limits and constraints, plus knowing when deviations are significant and who needs to know about the deviations. These systems need to be responsive and goal-oriented, flexibly responding to events based on desired outcomes rather than a predefined process (or, as I would say, unstructured rather than structured processes): this requires situational understanding, flexibility, shared knowledge and empowerment of the participants. Systems also need to be introspective, that is, compare their performance to goals and find new ways to achieve goals more effectively and predict outcomes. Finally, cities (and their systems) need to be held accountable for actions, which requires that activities need to be auditable to determine responsibility, and the underlying basis for decisions be known, so that a digital ombudsman can provide oversight.

Great talk, and very aligned with what I see in the private sector too: although the terminology is a bit different, the principles, technologies and challenges are the same.

Next, we heard from Hussam Ayyad, director of startup services at Ryerson University’s DMZ — a business incubator for tech startups — on Canadian FinTech startups. The DMZ has incubated more than 260 startups that have raised more than $206M in funding over their six years in existence, making them the #1 university business incubator in North America, and #3 in the world. They’re also ranked most supportive of FinTech startups, which makes sense considering their geographic proximity to Toronto’s financial district. Toronto is already a great place for startups, and this definitely provides a step up for the hot FinTech market by providing coaching, customer links, capital and community.

Unfortunately, I had to duck out partway through Ayyad’s presentation for a customer meeting, but plan to return for more of Technicity this afternoon.

Intelligent Capture enables Digital Transformation at #ABBYYSummit16

IMG_0672I’ve been in beautiful San Diego for the past couple of days at the ABBYY Technology Summit, where I gave the keynote yesterday on why intelligent capture (including recognition technologies and content analytics) is a necessary onramp to digital transformation. I started my career in imaging and workflow over 25 years ago – what we would now call capture, ECM and BPM – and I’ve seen over and over again that if you don’t extract good data up front as quickly as possible, then you just can’t do a lot to transform those downstream processes. You can see my slides at Slideshare as usual:

I’m finishing up a white paper for ABBYY on the same topic, and will post a link here when it’s up on their site. Here’s the introduction (although it will probably change slightly before final publication):

Data capture from paper or electronic documents is an essential step for most business processes, and often is the initiator for customer-facing business processes. Capture has traditionally required human effort – data entry workers transcribing information from paper documents, or copying and pasting text from electronic documents – to expose information for downstream processing. These manual capture methods are inefficient and error-prone, but more importantly, they hinder customer engagement and self-service by placing an unnecessary barrier between customers and the processes that serve them.

Intelligent capture – including recognition, document classification, data extraction and text analytics – replaces manual capture with fully-automated conversion of documents to business-ready data. This streamlines the essential link between customers and your business, enhancing the customer journey and enabling digital transformation of customer-facing processes.

I chilled out a bit after my presentation, then decided to attend one presentation that looked really interesting. It was, but was an advance preview of a product that’s embargoed until it comes out next year, so you’ll have to wait for my comments on it. Winking smile

A well-run event with a lot of interesting content, attended primarily by partners who build solutions based on ABBYY products, as well as many of ABBYY’s team from Russia (where a significant amount of their development is done) and other locations. It’s nice to attend a 200-person conference for a change, where – just like Cheers – everybody knows your name.