If there’s one thing the pandemic has taught IT leaders, it’s that their business continuity plans were not as hardened as they thought.

And while no one can fault CIOs for not having anticipated the full extent of the COVID-19’s impact on business, now that they have experienced such an event, many CIOs are getting strategic about planning for future unknown scenarios that may come to pass.

Business continuity plans (BCPs) center in large part around possible known scenarios, such as a major disruption caused by a fire, flood, or malicious attack by cybercriminals. They outline procedures an organization must follow in the face of such disasters, but when the exact fallout of a business existential event cannot be fully anticipated, establishing an organization capable of riding through such a scenario may be just as — if not more important than — having explicit plans in place to marshal a response.

This topic was explored recently during a session at the MIT Sloan CIO Symposium. CIOs who participated in the session further fleshed out in subsequent interviews what they wish they had done differently before and during the pandemic, as well as the technologies and IT strategies they believe will be beneficial in weathering unknowns in the coming years.

Following is a roundup of the common themes these IT leaders see as essential to ensuring future organizational resilience, as gleaned from their experiences throughout the pandemic. Consider it a continuity strategy that goes beyond the traditional BCP, focusing just as much on agility and flexibility and on positioning their organizations as a place where people want to work.

Toward a more proactive IT

“No one had a playbook for COVID but taking time to integrate the lessons learned and exercise your plans will be worthwhile to prepare you for the next unknown,” says Mona Bates, CIO of Collins Aerospace.

The Charlotte, N.C.-based aerospace and defense company has utilized lessons learned from the pandemic to establish a foundational focus on being proactive rather than reactive, especially when it comes to cybersecurity, Bates says.

Mona Bates, CIO, Collins Aerospace

Collins Aerospace

“We are taking proactive approaches to monitoring and measuring our critical [digital transformation] systems’ performance,’’ Bates says. This includes predicting system failure and performance trends, as well as monitoring the user experience and data-driven processes for continuous improvement across digital services and self-service, she says.

“From an architecture perspective, we reevaluated the ways in which we develop and bring to the business our support and applications, enhancing the business value and cost savings.” For example, Collins Aerospace is now taking a cloud-first approach and embracing the agile framework to design, develop, and deliver products faster, she says.

Now is the time to rethink business continuity plans, Bates adds. “Security and compliance [within] the enterprise is the ongoing, enduring work we’re doing to plan ahead,” she says. “It’s something that keeps me up at night.”

The good news is IT has good frameworks, practices, and talent in place, she says. But Bates still constantly asks herself whether the IT organization knows and understands its full architecture and whether they are doing enough tabletop exercises to be able to confidently respond and adjust.

Pushing what-if scenarios another step deeper

Adriana Karaboutis, group chief information and digital officer, National Grid

National Grid

Given the nature of its business as a multinational electricity and gas utility company, National Grid is doubling down on business continuity and crisis management in the wake of COVID-19. Adriana Karaboutis, group chief information and digital officer at National Grid, says it’s of paramount importance for IT leaders to think deeply about the future and conduct what-ifs simulations.

It is expected that utility officials will think about what will happen if there is an event that brings the phone network down. But it’s not enough to say, “we’ll use wireless,’’ she says. “What if that goes down? We have to keep thinking about what-ifs and things you didn’t imagine, so what we are doing within my organization is doubling down on the what-ifs because did anyone expect a pandemic for real? No. So now we have to assume they’re real and let’s play them through with different scenarios.”

IT spends a lot of time building resiliency, security, safety, and measuring into its scenario planning, she says.

Change management as an organizational skill

Of course, you can never imagine all the things you need to account for in scenarios. That’s why it’s important to build muscle and plan for how to manage a crisis, says Karaboutis, who adds that this was among the top lessons she learned as an IT leader throughout the pandemic.

“We all think we’re good at it and whether something like a political or geopolitical [event] or weather hits, we want to be leaders,” she says, “but change management is such an overused phrase and so underappreciated. Change management internally is a skill’’ that includes technologies, processes, and the way in which people work.

“If I could give any advice, it would be study it, learn it, understand the cycles,’’ Karaboutis says of change management. “I’d make it a more formal discipline and [incorporate] capabilities that many companies don’t embrace.”

To do this, IT must also “build dexterity and bring in diversity of thought and experience to your teams.” CIOs must also stay on top of tech cycles, the news, and the business of their business, Karaboutis says.

“The best anticipators of change will be successful in the next unknown that comes to us,” she says.

Accelerating the transformation timetable

With so many organizations having to accelerate digital initiatives to survive the pandemic, IT leaders are also stressing the need to ensure their organizations are primed for continual transformation as a means for navigating future unknowns.

Used vehicle retailer CarMax, for example, was on a path to enable customers to fully buy and sell cars online with the goal of “empowering customers to do everything on their own,” says Shamim Mohammad, executive vice president and chief information and technology officer. In early 2020, the company had rolled out an omnichannel experience to half of the country, Mohammad says.

Shamim Mohammad, EVP & CITO, CarMax

CarMax

What went well for CarMax’s IT group when the pandemic hit was a focus on agility and nimbleness and preparing the company for rapid change, he says. What didn’t work well was focusing too heavily on “culture and adapting and mindset. We could have done a better job getting farther along in [our transformation] journey,” Mohammad says. But this has “challenged us to move quicker.”

During the session at the symposium, Mohammad said IT’s plan was to “refocus on building agility and resiliency. Then we’ll be fine. Unknowns don’t have to always be bad.”

To do this, Mohammad is hiring more engineers and investing more in technologies such as data science and AI to automate and increase the pace at which teams are innovating. More legacy systems are being moved to the cloud at an accelerated pace “because cloud gives you a lot more agility than on-premises [systems].”

This will empower CarMax’s associates and customers and give them “the option and flexibility to do the work they’d like to do where they can add the most value,’’ he says, adding that, when IT teams are empowered for transformation, unknowns can become opportunities.

“As the unknowns become more known and we can see more clearly what’s happening, our teams can really adapt and respond and create the type of experiences customers are expecting,’’ he says. “We can really take advantage of that market-changing or industry- or society-changing opportunities.”

Mohammad credits CarMax IT’s shift from being a traditional project-based organization to a product-based one as key to facilitating the company’s ability to adapt to change, he says.

Before, there were large numbers of tech professionals who worked individually. Now there are cross-functional and small, mission-driven teams that understand the company goals and customer needs and are empowered to test and learn to understand changing customer behaviors, Mohammad says.

Improving the people part of business continuity

IT leaders have also been rethinking the people part of business continuity in the wake of a pandemic that exposed several holes in their plans.

Due to the unprecedented nature of the pandemic, like many other companies, Collins Aerospace, for example, did not have a plan for almost 75% of the organization to work from home, says Bates.

“Our digital organization was running very lean when it came to spare computer hardware and peripherals,’’ she says. “We had to quickly shift our asset and hardware management practices to put hardware in the hands of employees quickly to enable their safety and productivity.” Today, the company is partnering and planning differently with key suppliers, Bates says.

Technology-wise, National Grid’s IT group was prepared to keep its 23,000 employees connected and productive during the pandemic with laptops, video, and other collaboration tools, Karaboutis says, but the group CIDO is looking to go further.

Now, “we’re setting the bar really high and knowing the persona for each [employee]’’ to have a deeper knowledge of each individual’s needs, she says. For example, IT learned about people’s struggles during the pandemic, whether it was employees who were experiencing loneliness because they had no one at home — or those with three kids who now had to be home-tutored and they had no space for an office and needed headsets as opposed to just a laptop with a camera and microphone.

“Knowing those personas and being even more prepared is something I would say we could have done better” during the pandemic, Karaboutis says.

Building in better automation

For many organizations, automation and AI have proved key technologies for navigating the workplace and marketplace disruptions brought about by the pandemic, and many CIOs see both as strategic tools for making their organizations better positioned to deal with future unknowns.

CarMax’s Mohammad is one such IT leader. Mohammad’s plans for AI include automating more capabilities that humans don’t need to be involved with. For example, when global supply chain issues arose during the pandemic and demand for cars skyrocketed, within a few weeks, the company rolled out an AI-based capability through its omnichannel experience called Instant Offer, which gives customers the ability to quickly offer a car for sale without having to talk to anyone, by using the CarMax website or mobile app.

Customers answer a few questions and are given an offer within minutes without any human involvement, Mohammad says, adding that this will help ensure CarMax staff are free to tackle whatever comes next. “If my team can focus on where they can have the most value then I think they’ll be much more open, much more able to change things happening.”

Taking stock of AI

Still, further reliance on AI can also bring about greater risk of the very business existential unknowns for which IT leaders are now bracing their organizations.

While many IT leaders say that cybersecurity keeps them up at night, privacy, risk, compliance, and ethics should be responsibilities that also worry them, Karaboutis says.

As she sees it, AI and machine learning are critical for an intelligent, connected utility, but “there has to be an envelope of ethics, compliance, and security, otherwise, anything good can turn out poorly.”

Even with the constructs and guardrails regulators and policymakers have put in place, organizations need “more belts and suspenders and policies that are commensurate with the data we’re trying to pull together,” Karaboutis says.

For example, smart meters have become somewhat mainstream. Reading them at someone’s home can tell a field worker “whether the toaster or hairdryer is running because all [devices] have a different electrical pull” and a fingerprint, Karaboutis says. But individuals may not want their utility knowing this information and their privacy has to be respected.

“You have to give consent to the ethical portion of this,’’ she says. “That’s why we as technologists as we continue to really leverage for good, frontier technologies like AI, ML, blockchain, and others, we also need to have a view of ethics, responsibility, citizenship, responsible charters and make sure we’re living within the auspices of policy and creating policy as well.”

This requires thinking “360-degrees around the good and the potential risk for harm [with] technologies that are emerging,” she says. Otherwise, organizations open themselves up to potential fallout down the line.

The most daunting challenge: Talent

Industry-wide, IT leaders say there remains a high attrition trend among IT professionals — and not enough people entering the workforce to fill the gaps. The CIOs we talked to all agree that a big part of planning for future unknowns requires talent.

“We are focusing on pleasing the innovator innovating,’’ says Mohammad. “The talent shortage is the biggest uncertainty we all have to face.”

Similarly, the other big challenge at CarMax is making sure the company culture continues to be a place where people will want to work. “That is something we cannot take for granted and we need to focus more and more on that,’’ Mohammad says.

“Without exceptional talent, digital transformation cannot happen and readiness to tackle unknowns will be hindered,’’ says Bates. “We are focused on creative new ways to attract, develop, retain, and engage our employees to remain a preferred employer of choice and a place where people can work, grow, and belong.”

There is no one-size approach to work that will fit all needs, she notes. A hybrid work environment is here to stay at Collins Aerospace, which has defined three personas for employees based on their roles: remote, hybrid, and on-site. Managers work with their employees to decide the best persona fit.

The power, Bates says, is with the employee. So Collins Aerospace is “keenly focused on employee engagement in this new normal, ensuring our employees have a tie to our purpose and mission as a company and fully understand the impact they make on the mission,” she says.

Lowering the barrier to entry will help with the dearth of staff, Bates adds. “Going forward, we have to think differently about how we attract people and take the opportunity to develop them where there are gaps. AI could be a powerful technology to complement humans.” This will require learning how to work in a human-machine world to supplement the workforce, she says.

As they plan for the next unknowns, the silver lining is the culture change brought about by the pandemic and the fact that companies now know people can work from anywhere, anytime, and be productive and safe, Bates says.

“While we learned a lot and it was hard on many of us there’s always the nuggets. Let’s learn from them and apply them to whatever the next unknown is,’’ she said during the CIO consortium. “Know where your critical assets are — not just products, but people — and how you create more resiliency around them” in meaningful ways to keep businesses going.

Business Continuity, IT Leadership

1.

What is business analytics?

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Research firm Gartner defines business analytics as “solutions used to build analysis models and simulations to create scenarios, understand realities, and predict future states.”

While quantitative analysis, operational analysis, and data visualizations are key components of business analytics, the goal is to use the insights gained to shape business decisions. The discipline is a key facet of the business analyst role.

Wake Forest University School of Business notes that key business analytics activities include:

Identifying new patterns and relationships with data miningUsing quantitative and statistical analysis to design business modelsConducting A/B and multivariable testing based on findingsForecasting future business needs, performance, and industry trends with predictive modelingCommunicating findings to colleagues, management, and customers

2.

What are the benefits of business analytics?

Business analytics can help you improve operational efficiency, better understand your customers, project future outcomes, glean insights to aid in decision-making, measure performance, drive growth, discover hidden trends, generate leads, and scale your business in the right direction, according to digital skills training company Simplilearn.

3.

What is the difference between business analytics and data analytics?

Business analytics is a subset of data analytics. Data analytics is used across disciplines to find trends and solve problems using data mining, data cleansing, data transformation, data modeling, and more. Business analytics also involves data mining, statistical analysis, predictive modeling, and the like, but is focused on driving better business decisions.

4.

What is the difference between business analytics and business intelligence?

Business analytics and business intelligence (BI) serve similar purposes and are often used as interchangeable terms, but BI can be considered a subset of business analytics. BI focuses on descriptive analytics, data collection, data storage, knowledge management, and data analysis to evaluate past business data and better understand currently known information. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward. It uses data mining, data modeling, and machine learning to answer “why” something happened and predict what might happen in the future.

Business analytics techniques

According to Harvard Business School Online, there are three primary types of business analytics:

Descriptive analytics: What is happening in your business right now? Descriptive analytics uses historical and current data to describe the organization’s present state by identifying trends and patterns. This is the purview of BI.Predictive analytics: What is likely to happen in the future? Predictive analytics is the use of techniques such as statistical modeling, forecasting, and machine learning to make predictions about future outcomes.Prescriptive analytics: What do we need to do? Prescriptive analytics is the application of testing and other techniques to recommend specific solutions that will deliver desired business outcomes.

Simplilearn adds a fourth technique:

Diagnostic analytics: Why is it happening? Diagnostic analytics uses analytics techniques to discover the factors or reasons for past or current performance.

Examples of business analytics

San Jose Sharks build fan engagement

Starting in 2019, the San Jose Sharks began integrating its operational data, marketing systems, and ticket sales with front-end, fan-facing experiences and promotions to enable the NHL hockey team to capture and quantify the needs and preferences of its fan segments: season ticket holders, occasional visitors, and newcomers. It uses the insights to power targeted marketing campaigns based on actual purchasing behavior and experience data. When implementing the system, Neda Tabatabaie, vice president of business analytics and technology for the San Jose Sharks, said she anticipated a 12% increase in ticket revenue, a 20% projected reduction in season ticket holder churn, and a 7% increase in campaign effectiveness (measured in click-throughs).

GSK finds inventory reduction opportunities

As part of a program designed to accelerate its use of enterprise data and analytics, pharmaceutical titan GlaxoSmithKline (GSK) designed a set of analytics tools focused on inventory reduction opportunities across the company’s supply chain. The suite of tools included a digital value stream map, safety stock optimizer, inventory corridor report, and planning cockpit.

Shankar Jegasothy, director of supply chain analytics at GSK, says the tools helped GSK gain better visibility into its end-to-end supply chain and then use predictive and prescriptive analytics to guide decisions around inventory and planning.

Kaiser Permanente streamlines operations

Healthcare consortium Kaiser Permanente uses analytics to reduce patient waiting times and the amount of time hospital leaders spend manually preparing data for operational activities.

In 2018, the consortium’s IT function launched Operations Watch List (OWL), a mobile app that provides a comprehensive, near real-time view of key hospital quality, safety, and throughput metrics (including hospital census, bed demand and availability, and patient discharges).

In its first year, OWL reduced patient wait time for admission to the emergency department by an average of 27 minutes per patient. Surveys also showed hospital managers reduced the amount of time they spent manually preparing data for operational activities by an average of 323 minutes per month.

Business analytics tools

Business analytics professionals need to be fluent in a variety of tools and programming languages. According to the Harvard Business Analytics program, the top tools for business analytics professionals are:

SQL: SQL is the lingua franca of data analysis. Business analytics professionals use SQL queries to extract and analyze data from transactions databases and to develop visualizations.Statistical languages: Business analytics professionals frequently use R for statistical analysis and Python for general programming.Statistical software: Business analytics professionals frequently use software including SPSS, SAS, Sage, Mathematica, and Excel to manage and analyze data.

Business analytics dashboard components

According to analytics platform company OmniSci, the main components of a typical business analytics dashboard include:

Data aggregation: Before it can be analyzed, data must be gathered, organized, and filtered.Data mining: Data mining sorts through large datasets using databases, statistics, and machine learning to identify trends and establish relationships.Association and sequence identification: Predictable actions that are performed in association with other actions or sequentially must be identified.Text mining: Text mining is used to explore and organize large, unstructured datasets for qualitative and quantitative analysis.Forecasting: Forecasting analyzes historical data from a specific period to make informed estimates predictive of future events or behaviors.Predictive analytics: Predictive business analytics use a variety of statistical techniques to create predictive models that extract information from datasets, identify patterns, and provide a predictive score for an array of organizational outcomes.Optimization: Once trends have been identified and predictions made, simulation techniques can be used to test best-case scenarios.Data visualization: Data visualization provides visual representations of charts and graphs for easy and quick data analysis.

Business analytics salaries

Here are some of the most popular job titles related to business analytics and the average salary for each position, according to data from PayScale:

Analytics manager: $71K-$132KBusiness analyst: $48K-$84KBusiness analyst, IT: $51K-$100KBusiness intelligence analyst: $52K-$98KData analyst: $46K-$88KMarket research analyst: $42K-$77KQuantitative analyst: $61K-$131KResearch analyst, operations: $47K-$115KSenior business analyst: $65K-$117KStatistician: $56K-$120KAnalytics

Cairn Oil & Gas is a major oil and gas exploration and production company in India. It currently contributes 25% to India’s domestic crude production (about 28.4 MMT) and is aiming to account for 50% of the total output. The company plans to spend ₹3,16,09 crores (₹31.6 billion) over the next three years to boost its production.

The oil and gas industry currently confronts three major challenges: huge price fluctuation with volatile commodity prices, capital-intensive processes and long lead times, and managing production decline.

Sandeep Gupta, chief digital and information officer at Cairn Oil & Gas, is using state-of-the-art technologies to overcome these challenges and achieve business goals. “We have adopted a value-focused approach to deploying technological solutions. We partner with multiple OEMs and service integrators to deploy highly scalable projects across the value chain,” he says.

Reducing operational costs with drones, AI, and edge computing

Sandeep Gupta, chief digital and information officer, Cairn Oil & Gas

istock

The oil and gas industry is facing huge price fluctuation due to volatile commodity prices and geopolitical conditions. In such a scenario, it becomes crucial for the business to manage costs.

Sustained oil production depends on uninterrupted power supply. However, managing transmission lines is a high-cost, resource-intensive task. For Cairn, it meant managing 250km of power lines spread across 3,111 square kilometers. They supply power to the company’s Mangala, Bhagyam, and Aishwarya oil fields and its Rageshwari gas fields in Rajasthan.

To reduce operational costs, the company decided to use drones. The images captured by the drones are run through an AI image-recognition system. The system analyses potential damage to power lines, predicts possible failure points, and suggests preventive measures, thereby driving data-driven decision-making instead of operator-based judgment.

“Algorithms such as convolutional neural networks were trained on images captured when the overhead powerlines are running in their ideal condition. The algorithm then compares the subsequent images that are taken at an interval of six months when any anomalies are captured. An observation is then put into portal for the maintenance team to take corrective and preventive action,” says Gupta.

This is a service-based contract between Cairn and the maintenance provider where the monitoring is carried out on biannual basis for 220kV power lines and annually for 500kV power lines.

“Since the implementation of drone-based inspection, the mean time between failure has increased from 92 to 182 days. This has reduced oil loss to 2,277 barrels per year, leading to cost savings worth approximately ₹12 crores [₹120 million]. As it enables employees to carry out maintenance activities in an effective manner, a small team can work more efficiently, and the manpower required reduces,” Gupta says.

The remote location of operations coupled with a massive volume of data (Cairn generates about 300GB data per day) that is generated make the oil and gas industry ideal for the use of edge-based devices for computing.

With smart edge devices, critical parameters are stored and processed at remote locations. The devices are installed in the field which send data via MQTT protocol where cellular network connectivity is available. They store data up to 250GB on the Microsoft Azure cloud and perform analytics using machine-learning algorithms, as well as provide intelligent alarms.

Without these devices, the data generated would be transported to faraway data centres, clogging the network bandwidth. “Edge computing helps reduce our IT infrastructure cost as lower bandwidth is sufficient to handle the large volume of data. These devices deployed are tracking critical operational parameters such as pressure, temperature, emissions, and flow rate. The opportunity cost of not having edge computing would result in requiring a higher bandwidth of network, which would amount to around 2X of the current network cost,” says Gupta. “This also has an implication on the health and safety risk of our personnel and equipment.”

Reducing lead times through a cloud-first strategy

The oil exploration process has a lead time of around three to five years and requires huge capital commitment. Out of these three to five years, a significant amount of time is taken up by petrotechnical experts (geologists, geophysicists, petroleum engineers, and reservoir engineers) in simulating models that require massive computational power.

Petrotechnical workflow entails evaluation of subsurface reservoir characteristics to identify the location for drilling the wells. These workflows are carried out by petrotechnical experts via multiple suites of software applications that can help identify the location and trajectory of wells to be drilled.

“Capital allocation and planning for future exploration has become riskier due to long lead times. To achieve our goals, increasing computing capabilities are essential. For this, we have adopted and executed a cloud-first strategy,” says Gupta. Thus, Cairn has completely migrated the workloads for petrotechnical workflows to the cloud. “This migration has removed the constraints of on-premises computational capabilities. As a result, there is almost 30% reduction in time to first oil,” he says.

Managing decline in production through predictive analytics

Cairn has considerable volume, variety, and velocity of data coming from different sources across production, exploration, and administration. “Using this data, we have deployed multiple large-scale projects, including predictive analytics, model predictive control, and reservoir management, which have been scaled across multiple sites,” says Gupta. Model predictive control (MPC) is a technology where the equipment is monitored for various operating parameters and is then operated in a particular range to get maximum efficiency, while maintaining the constraints in the system.

At the heart of this lies Disha, a business intelligence initiative that uses dashboards driving critical actionable insights. “The philosophy for developing Disha was to make the right data available to the right people at the right time. We wanted to remove file-based data sharing and reporting as significant time goes in creating these reports. We connected data from various sources such as SAP HANA, Historian, Microsoft SharePoint, Petrel, LIMS, and Microsoft Azure cloud onto a single Microsoft PowerBI ecosystem where customized reports can be created,” says Gupta.

Disha was developed in a hybrid mode with an in-house team and an analytics provider over the course of three years. It offers more than 200 customized dashboards, including a well-monitoring dashboard, a production-optimisation dashboard, a CEO and CCO dashboard, and a rig-scheduling dashboard.

“With data now easily and quickly accessible in an interactive format across the organisation, which was earlier restricted to a select few, the corrective actions for resource allocation are now based on the data,” Gupta says. “For instance, we leverage Disha to monitor the parameter and output of the electronic submersible pump, which handles oil and water. It helps us in tracking the gains achieved through MPC implementation. All this enables better decision-making and has helped to allocate resources in optimized manner, thus managing the decline in productivity.” Going forward, Cairn plans to partner with a few big analytics providers and build a single platform to help contextualize its data and deploy micro solutions, according to business needs. “This will be a low-code platform that will enable individual teams to build solutions on their own,” Gupta says. “The initiatives are oriented towards sustaining the production levels, while reducing time to first oil. Some of the initiatives include artificial lift system monitoring, well monitoring, and well-test validation,” says Gupta.

Artificial Intelligence, Digital Transformation

Companies and organizations are experiencing the first stage of a new digital support: GDPR management tools. We analyzed some of them.

As for all previous cases of new business compliance processes there is today a growing number of tools in the market addressing the all new European privacy law, the General Data Protection Regulation, which came into force on May 25, 2018. Our main conclusion: these privacy tools have design limitations.

Il problema

In alcuni casi l’approccio della soluzione è tecnologico -sistemi progettati come se fossero indipendenti o di natura statica- mentre in altri casi è funzionale, quindi tecnico in materia di compliance, ancora specifico.

Classifichiamo entrambi gli approcci come principalmente orientati al marketing; non per criticare la qualità di questi strumenti in quanto tali, ma il fatto che le soluzioni sono principalmente opportunità commerciali guidate dallo slancio per una domanda improvvisa, il cui mercato non è ancora esperto in materia. Questa pratica solleva problemi, anzi.

Parlando con gli esperti di GDPR emerge che alcuni imprenditori e dirigenti hanno adottato una visione che limita la conformità al GDPR a una gestione – burocratica – dei documenti o, peggio ancora, sembrano un’operazione one-shot che non richiede manutenzione. Il tutto nonostante i tanti e ripetuti avvertimenti e rischi di incorrere in enormi sanzioni amministrative.

Inoltre, ci è stato confidato che le aziende apparentemente preferiscono processi di business del mondo reale non corrispondenti rispetto alla presentazione di “processi ufficiali” e continuano con quelli abituali. Conclusione: il rischio e lo scopo dell’audit di conformità vengono dissipati nonostante si spenda tempo e denaro e allo stesso tempo con un costo di rischio elevato.

Ritorno al passato

Notiamo un notevole parallelo con gli anni ’90, quando la certificazione di qualità ISO era di moda. Non era raro trovare imprenditori che inseguivano in modo contingente una serie di certificati, senza tuttavia alcuna seria intenzione di cambiare la loro cultura aziendale.

Abbiamo lavorato con un bel po ‘di loro in quel momento e, purtroppo ma non a caso, nessuno di loro aveva illuminato il proprio futuro dopo tali scelte. (Nessuno di loro esiste più sul mercato, ma questo è solo un account personale.)

Tre decenni dopo, la qualità in generale, infine, sembra diffusa in molti ambienti aziendali e la mappatura e la reingegnerizzazione dei processi non sono più una novità. I vantaggi che ne derivano sono riconosciuti come parte della nostra cultura aziendale.

Un approccio innovativo: un’opportunità

Sottovalutare gli interventi necessari per soddisfare il GDPR o non sfruttare tutte le azioni necessarie durante questo processo, può portare le aziende a scegliere strumenti sbagliati che richiedono un serio impegno di conformità. Spesso questa strada porta anche all’impossibilità di collegarsi ad altre aree di competenza fondamentali come Legale e Operativo. Considerato tutto quanto sopra, solleviamo una domanda cruciale:

Perché le aziende e le organizzazioni dovrebbero mappare i propri processi solo ai fini del GDPR? Perché gli strumenti GDPR non partono dai processi gestiti?

Sono disponibili standard di scambio, come IDEFx, FFBD o BPMN 2.0 per la modellazione o standard universali come XML o Json, solo per fornire alcuni esempi. Allora, quanto è comune l’adozione di strumenti di mappatura dei processi?

Questa mancanza di integrazione delle migliori pratiche e degli investimenti precedenti porta a un costoso logoramento.