digitaltransformation – Page 4

Obligatory futurist keynote at AIIM18 with @MikeWalsh

We’re at the final day of the AIIM 2018 conference, and the morning keynote is with Mike Walsh, talking about business transformation and what you need to think about as you’re moving forward. He noted that businesses don’t need to worry about millenials, they need to worry about 8-year-olds: these days 90% of all 2-year-olds (in the US) know how to use a smart device, making them the truly born-digital generation. What will they expect from the companies of the future?

Machine learning allows us to customize experiences for every user and every consumer, based on analysis of content and data. Consumers will expect organizations to predict their needs, before they could even voice it themselves. In order to do that, organizations need to become algorithmic businesses: be business machines rather than have business models. Voice interaction is becoming ubiquitous, with smart devices listening to us most (all) of the time and using that to gather more data on us. Face recognition will become your de facto password, which is great if you’re unlocking your iPhone X, but maybe not so great if you don’t like public surveillance that can track your every move. Apps are becoming nagging persuaders, telling us to move more, drink more water, or attend this morning’s keynote. Like migratory birds that can sense magnetic north, we are living in a soup of smart data that guides us. Those persuasive recommendations become better at predicting our needs, and more personalized.

Although he started by saying that we don’t need to worry about millenials, 20 minutes into his presentation Walsh is admonishing us to let the youngest members of our team “do stuff rather than just get coffee”. It’s been a while since I worked in a regular office, but do people still have younger people get coffee for them?

He pointed out that rigid processes are not good, but that we need to be performance-driven rather than process-driven: making good decisions in ambiguous conditions in order to solve new problems for customers. Find people who are energized by unknowns to drive your innovation — this advice is definitely more important than considering the age of the person involved. Bring people together in the physical realm (no more work from home) if you want the ideas to spark. Take a look at your corporate culture, and gather data about how your own teams work in order to understand how employees use information and work with each other. If possible, use data and AI as the input when designing new products for customers. He recommended a next action of quantifying what high performance looks like in your organization, then work with high performers to understand how they work and collaborate.

He discussed the myth of the simple relationship between automation and employment, and how automating a task does not, in general, put people out of work, but just changes what their job is. People working together with the automation make for more streamlined (automated) standard processes with the people focused on the things that they’re best at: handling exceptions, building relationships, making complex decision, and innovating through the lens of combining human complexity with computational thinking.

In summary, the new AI era means that digital leaders need to make data a strategic focus, get smart about decisions, and design work rather than doing it. Review decisions made in your organization, and decide which are best made using human insight, and which are better to automate — either way, these could become a competitive differentiator.

Automation and digital transformation in the North Carolina Courts

Elizabether Croom, Morgan Naleimaile and Gaynelle Knight from the North Carolina Courts led a breakout session on Thursday afternoon at AIIM 2018 on what they’ve done to move into the digital age. NC has a population of over 10 million, and the judiciary adminstration is integrated throughout the state across all levels, serving 6,800 staff, 5,400 volunteers and 32,000 law enforcement officers as well as integrating and sharing information with other departments and agencies. New paper filings taking up 4.3 miles of shelving each year, yet the move to electronic storage has to be done carefully to protect the sensitivity of the information contained within these documents. For the most part, the court records are public records unless they are for certain types of cases (e.g., juveniles), but PII such as social security numbers must be redacted in some of these documents: this just wasn’t happening, especially when documents are scanned outside the normal course of content management. The practical obscurity (and security) of paper documents was moving into the accessible environment of electronic files.

They built their first version of an enterprise information management systems, including infrastructure, taxonomy, metadata, automated capture and manual redaction. This storage-centric phase wasn’t enough: they also needed to address paper file destruction (due to space restrictions), document integrity and trustworthiness, automated redaction of PII, appropriate access to files, and findability. In moving along this journey, they started looking at declaring their digital files as records, and how that tied in with the state archives’ requirements, existing retention schedules and the logic for managing retention of records. There’s a great deal of manual quality control currently required for having the scanned documents be approved as an official record that can replace the paper version, which didn’t sit well with the clerks who were doing their own scanning. It appears as if an incredible amount of effort is being focused on properly interpreting the retention schedule logic and trigger sources: fundamentally, the business rules that underlie the management of records.

Moving beyond scanning, they also have to consider intake of e-filed documents — digitally-created documents that are sent into the court system in electronic form — and the judicial branch case management applications, which need to consume any of the documents and have them readily available. They have some real success stories here: there’s an eCourts domestic violence protection order (DVPO) process where a victim can go directly to a DV advocate’s office and all filings (including a video affidavit) and the issue of the order are done electronically while the victim remains in the safety of the advocate’s office.

They have a lot of plans moving forward to address their going-forward records capture strategy as well as addressing some of the retention issues that might be resolved by back-scanning of microfilmed documents, where documents with different retention periods may be on the same roll of film. Interestingly, they wouldn’t say what their content management technology is, although it does sound like they’re assessing the feasibility of moving to a cloud solution.

AIIM18 keynote with @jmancini77: it’s all about digital transformation

I haven’t been to the AIIM conference since the early to mid 90s; I stopped when I started to focus more on process than content (and it was very content-centric then), then stayed away when the conference was sold off, then started looking at it again when it reinvented itself a few years ago. These days, you can’t talk about content without process, so there’s a lot of content-oriented process here as well as AI, governance and a lot of other related topics.

I arrived yesterday just in time for a couple of late-afternoon sessions: one presentation on digital workplaces by Stephen Ludlow of OpenText that hit a number of topics that I’ve been working on with clients lately, then a roundtable on AI and content hosted by Carl Hillier of ABBYY. This morning, I attended the keynote where John Mancini discussed digital transformation and a report released today by AIIM. He put a lot of emphasis on AI and machine learning technologies; specifically, how they can help us to change our business models and accelerate transformation.

We’re in a different business and technology environment these days, and a recent survey by AIIM shows that a lot of people think that their business is being (or about to be) disrupted, and digital transformation is and important part of dealing with that. However, very few of them are more than a bit of the way towards their 2020 goals for transformation. In other words, people get that this is important, but just aren’t able to change as fast as is required. Mancini attributed this in part to the escalating complexity and chaos that we see in information management, where — like Alice — we are running hard just to stay in place. Given the increasing transparency of organizations’ operations, either voluntarily or through online customer opinions, staying in the same place isn’t good enough. One contributor to this is the number of content management systems that the average organization has (hint: it’s more than one) plus all of the other places where data and content reside, forcing workers to have to scramble around looking for information. Most companies don’t want to have a single monolithic source of content, but do want a federated way to find things when they need it: in part, this fits in with the relabelling of enterprise content management (ECM) as “Content Services” (Gartner’s term) or “Intelligent Information Managment” (AIIM’s term), although I feel that’s a bit of unnecessary hand-waving that just distracts from the real issues of how companies deal with their content.

He went through some other key findings from their report on what technologies that companies are looking at, and what priority that they’re giving them; looks like it’s worth a read. He wrapped up with a few of his own opinions, including the challenge that we need to consider content AND data, not content OR data: the distinction between structure and unstructured information is breaking down, in part because of the nature of natively-digital content and in part because of AI technologies that quickly turn what we think of as content into data.

There’s a full slate of sessions today, stay tuned.

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.

The 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.

Their 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:

The 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.

They 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

I’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.