Creating a Culture of Accountability

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Why is Accountability Important?

Accountability: “The obligation of an individual or organization to account for its activities, accept responsibility for them, and to disclose the results in a transparent manner.”In his December 8, 2016, online Forbes article “Why Accountability Is Critical For Achieving Winning Results,” Brent Gleeson writes “…accountability is probably the single most important element fueling truly successful organizations.” While Mr. Gleeson is referring to accountability in terms of the private sector, his observation is particularly applicable to law enforcement.Police departments operate in a highly discretionary, minimally supervised, procedure and protocol dependent environment. Discretionary decisions, to act or not to act, can have tremendous impact on citizens, the officer, the community and the department.  Discretionary decisions are made on a daily basis, they generally attract very little attention and usually are based on good intentions and have good results; however, the misuse of discretion does occur and has terrible consequences. While the high profile arrest of a dangerous felon may be the headline of the day, a discretionary enforcement action that gives the appearance of bias can linger in the media for months, destroying reputations and careers in the process.  Routine and mundane internal review processes and protocols can be so cumbersome and appear so insignificant that they “fall through the cracks”. Generally, those failings attract little departmental attention and seem to have little impact, until the day they are vital in the defense of a departmental action, are the critical link that would have provided an early indication of misconduct, policy failure or personal crisis, or are needed to demonstrate the department’s attentiveness to issues of public concern  When the misapplication of discretion, misconduct, or incidents of high public interest occur we often discover a history, both individually and organizationally, of overlooked indicators, that if recognized and acted upon, may have prevented or mitigated the impact of the conduct or incident. Police agencies are often characterized as intentionally ignoring or refusing to see the value of establishing accountability systems that could identify and possibly prevent misconduct, policy failure and threats to officer wellness; however, the more accurate reason for the lack of accountability is the overwhelming nature of law enforcement. All too often the demands of the day take precedence over less immediate issues and the volume of available information makes recognition and analysis very difficult. Agency size and workload make little difference; the smaller the agency the more tasks the chief and command staff are responsible for, in large agencies the volume of information and limited interaction between senior staff and operational personnel complicate the lines of communication. In each case, for different reasons, things “fall through the cracks” and accountability suffers.When an organization consistently pays attention to discretionary decisions and the procedure and protocol review process, those decisions and reviews are more in line with department values and policies.  Transparency and public confidence increase when the department can clearly demonstrate that conduct is monitored and reviewed. The challenge for the law enforcement executive is how, within the many and varied demands of their position, to establish a workable process that creates a culture of accountability.

How To Acess Accountability in your organization

A Comprehensive Review Of All Policies Should Be Conducted With The Following In Mind:

  • Do the policies clearly define expectations and requirements both operationally and in terms of the internal review process?
  • Are policies relevant, necessary and current?  Unenforced, unnecessary policies or those that are outdated, detract from the value of needed and vital policy.
  • Do policies reflect the mission, values and vision of the department? Policy should, in all cases, be consistent with the desired culture of the department.

For Internal Review Processes Consider The Following:

  • Is the process needed and relevant?  Unnecessary work detracts from the importance of vital reviews.
  • Is the review process workflow clearly defined and are the expectations for each level of review explicitly delineated?
  • Is there a standardized format (form) that guides the review?  If not, consider the development a standardized format.
  • Are time limits or time parameters established by policy and enforced?  The required timely completion of a review process emphasizes its importance, reduces the chance of a repeat of policy/performance failure and reinforces proper conduct.

Audit The Discretionary Decisions Made by Department Personnel:

  • What are most frequently occurring discretionary situations/decisions officers face/make?
  • Are the decisions made consistent with the policies, mission, vision and values of the department?
  • Have those decisions resulted in citizen complaints and/or civil actions?
  • Is there a shift, unit, day of week/hour of day, or supervisory correlation between discretionary decisions and complaints or civil actions?
  • Does department training address those situations where officers are required to make discretionary decisions?
Consider the availability and use of technological solutions designed to enhance the efficiency and effectiveness of the internal review process and the identification and analysis of discretionary activity and decisions. 

Proactive Is The Word For 21st Century Protecting & Serving

Police Office Training Wellness

Zach Quaintance, staff writer for Government Technology magazine recently wrote an article titled “SXSW 2019: Can Artificial Intelligence Spot Stressed Cops?

In the article, Mr. Quaintance is quoted as saying “Imagine a future in which tech — likely powered by artificial intelligence or natural language processing — gauges when an officer has undergone too many emotionally taxing calls. That same product would alert supervisors to the officer’s plight, advising them to take the stressed individual out of the field until they’d recovered.”

At Altovista Technology, we have great news, the future has already arrived. Altovista Technology’s Arx Alert artificial intelligence platform provides Law Enforcement agencies a comprehensive way to investigate, report on, resolve and predict incidents – all in one centralized, cloud-based solution.

Police officers are held to a higher standard – they are expected to protect the public, not put it at risk. Police “actions should reflect a standard of professionalism and skill that ensures equal protection and equal treatment under the law,” as the COPS report on Risk Management in Law Enforcement makes clear.

That can be a high bar to meet, especially when you consider the extraordinary demands placed upon police officers. In the normal course of their job, officers can be exposed to gruesome accidents and crime scenes, child and domestic partner abuse and other horrors that can lead to post-traumatic stress. Police officers also endure the normal stressors of family life and extreme ones like divorce, loss of a parent or financial difficulties. Any of these factors can have a negative effect on an officer’s physical, emotional and psychological well-being, job performance and decision-making ability. The combination of stressed-out police officers and the high-risk critical tasks that they undertake on a daily basis creates possibilities for missteps and lawsuits. In addition, with the proliferation of video and social media, chances are good that someone will notice.

So, what is an agency to do?

When the Detroit Police Department was working to make the changes mandated by the consent decree, it turned to our founding entrepreneurs for help. Dr. Jay Harrison and Bo Cheng digitized Detroit PD’s records, connected them and developed a system that would enable the agency to identify, manage, mitigate and avoid future incidents of officer misconduct through actionable follow-up.

In the first five years after Harrison and Cheng created the software, DPD saw a 62 percent reduction in lawsuits, a 36 percent reduction in citizen complaints and a 64 percent reduction in fatal shootings. It also started saving over $5 million annually in lawsuit payouts.

Realizing that police departments of all sizes could benefit from the solution that transformed DPD, Harrison, Cheng and their partners founded Altovista Technology.

Altovista Technology’s software, Arx Alert, is cloud-based risk management software that helps agencies proactively monitor and identify risks before they become lawsuits. Using artificial intelligence, Arx Alert identifies when an officer has been exposed to or is exhibiting the potential for risk, then guides supervisors through an intervention process to proactively correct the issue. Arx Alert integrates multiple data sources (including data that is already digital and data that is stored on paper documents) that the agency is already keeping in the normal course of operations, saving supervisors the work of having to manually comb through disconnected databases.

The software searches across records management systems, computer-aided dispatch systems, training records, personnel records, and other data sources for factors like citizen complaints, excessive overtime, vehicle pursuits or collisions, officer-involved shootings and civil rights violations.

A supervisor can easily log in to a cloud-based customized dashboard to see all officers who report to him or her and any risk potentials are flagged. The dashboard provides a single, holistic view of individual officer activity and can be used to identify agency trends.

Cheng, Altovista Technology’s President says “Overtime, intake violations and vehicular incidents are prevalent in all police departments. These cause lawsuits and cost money just like the more newsworthy issues like improper use of force.”

The power to turn data into smart, timely, effective, trusted, actionable information is here. Right now, Arx Alert is being used to do some incredibly smart and good things, like creating safer and healthier police forces, which in turn creates safer and healthier communities. Proactive is the word for 21st century protecting and serving. Law enforcement agencies and the communities they serve need no longer rely on things like hope or luck.

Not on this watch.

An all-in-one risk management software solution powered by Artificial Intelligence automatically brings antiquated and potentially ineffective processes into this digital age to create meaningful, clear, accurate, real-time data that produces positive and effective action and outcomes. This isn’t just smart technology.

Arx Alert is an opportunity, one that allows law enforcement to get back to being the force for good it has always been.

Read more about the Detroit Police Department’s success using Arx Alert.

How the City of Detroit Saved Millions of Dollars With Arx Alert

City Of Detroit

Problem: $124 Million in Lawsuit Payouts

From 1987 to 2000, the City of Detroit paid over $124 million in police misconduct lawsuits, averaging almost $10 million per year. In 2000, then-Mayor Dennis Archer requested the probe after police were involved in 47 fatal shootings between 1995 and 2000, including six of unarmed suspects. Between 1994 and 2000, 19 witnesses died while being detained by the Detroit Police Department (DPD). After federal review, on July 18, 2003 the DPD, the City of Detroit and the United States Department of Justice entered into two consent decrees. The first consent decree deals with the Use of Force, Arrest and Witness Detention.

The second decree concerns the Conditions of Confinement in our holding facilities. The Consent Decree was also very costly, where a monitored was paid upwards of $2.3 million per year. Within the Consent Decree, the DOJ mandated for Detroit to implement a Risk Management Database. This was a top priority for the City of Detroit, but very difficult for the city to implement on its own

The risk management database needed to be a new computerized relational database, integrating and retrieving data necessary for supervision and management of the police department as detailed in sections 79-99 of the Consent Decree. The purpose of the system was to acquire and evaluate the performance of DPD officers across all ranks, units and shifts, to manage risk and liability, and to promote civil rights and best police practices. The system was also required to gather and integrate with over 36 datasets such as canine bites, civil lawsuits, use of force reports, hold policy, and etc.

This was difficult to integrate into a system due to the nature of DPD’s paper-based records management. In 2009, DPD was no further along in their process of implementing the risk management system. By this time, the city paid over $13.8 million in monitoring fees. DPD’s internal IT staff had created a temporary system called the Interim Management Awareness System (IMAS) until the Management Awareness System (MAS) could be developed. The IMAS was primarily an Access database that required manual entry of data captured from over 2,500 police officers. This created inefficiencies, inaccuracies, and delays in identifying risk within the police department. The City of Detroit and DPD needed help. Without an effective solution, the city would continue to pay millions on monitoring fees.

The City of Detroit and DPD needed help. Without an effective solution, the city would continue to pay millions on monitoring fees.

Solution: Integrated Risk Management System

For MAS to be successful, we needed address DPD’s three primary areas of concern for an effective risk management system. The first is to create a system that met the compliance of the Consent Decree, the second is to create a system that is accurate in identifying risk, and the third is to have an organization of 2,500 officers adopt the technology efficiently and effectively. We embarked on this process in 2009.

In order to meet the compliance of the Consent Decree, the system needed to identify risk factors from 36 datasets in near real-time. The, then current, process with IMAS was arduous and inaccurate since it relied on human intervention to replicate data. Data replication was required because critical datasets such as use of force was captured in paper form. For our risk management software to function effectively, we needed to first digitize the police departments paper-based records into an electronic database.

Working the police department, we created a flexible digital forms solution that converted existing paper forms into digital computer entry. This saved officers time, increased accuracy in data capture, and allows us to develop the risk management system.

Once the paper-based records were transitioned to digital records, we were able to begin the data integration into the risk management system, including DPD’s existing digital-based systems such as the Crisnet police reports and human resource time keeping system. With digital data now available to DPD, we needed to ensure risk management was accurate in identifying risk. This was challenging because we needed to create a system that did not exist to meet the unique needs of DPD.

We benchmarked major cities across the nation and the best practice, at that time, of risk management was quarterly reviews and outdated methods of fixed rules or thresholds for analysis. The challenge with this is a potential for false positives or not enough risk positives. For example, a member of the gang squad in a police department may shoot a canine at a higher rate than a patrol officer on traffic duty. If we set a fixed threshold across the department for canine shootings, it will not be able to encompass the unique attributes that determine risk accuracy. To address this issue, we needed to create a flexible rule set that learned the uniqueness of the police department. We deployed an early version of an Artificial Intelligence (A.I.) rules engine that identified risk and adjusted based on the changing dynamics in the police department, reducing false positives.

We needed to ensure that the 2,500 officers would adopt MAS and the risk management worked to ensure accountability. With the many systems the police department was using, we established a philosophy to simplify, eliminate, and automate where possible, without creating additional work for the officers. A change from paper-based to digital records keeping created natural barriers for adoption.

Our approach to removing the barrier was to design the digital forms that are familiar to the officers, reducing training time and increased adoption. In addition, we automated many of the workflows that saved officers time from traditional paperwork. The Consent Decree also required accountability in the risk management process and a change in culture. We needed to also ensure command staff adoption of MAS.

Our approach to managing culture change was to leverage data and automated workflow for accountability. For example, when risk is identified, supervisors needed to intervene within 48 hours. Previously, this would have been difficult to enforce. We embedded compliance policy that would alert a sergeant if the supervisor did not intervene within the appropriate time frame. Each level of the organization was held accountable, including alerting the Mayor if the Chief of Police did not comply with certain policies. We also designed additional “public safety apps” bridge gaps in data collection and processes so the officers did not have to go outside of MAS to perform necessary functions. This allowed officers and command staff to stay in the MAS application as much as possible.

In 2011, the deployment and adoption of MAS at DPD met the compliance of the Consent Decree, reduced false-positives, and increased user adoption. This fundamentally transformed a police department and helped DPD leapfrog into data-drive risk management.

Results: Reduced Lawsuits, Reduced Citizen Complaints, Reduced Payouts

As a result of deploying MAS, DPD experienced a decline in citizens complaints, use of force, and lawsuit payouts. Since the implementation of MAS, DPD has seen a 36% average decline in citizen complaints. Use of force within the first year of deploying MAS, saw a 17.5% decline in use of force across all applicable categories. By the time DPD entered into a Consent Decree transition agreement, use of force was reduced by 22.5% across the spectrum. In a recent 2017 article published by the Detroit News, MAS reduced lawsuits filed against the city by 62%, compared to the previous year. Lawsuit payouts was $4.9 million compared to $10 million in years before the Consent Decree; this represents a $5.1 million save.

Lawsuit payouts was $4.9 million compared to $10 million in years before the Consent Decree; this represents a $5.1 million save.

In addition to the reduction in tangible risk categories, DPD also had access to their complete digital dataset, enabling additional benefits such as running time keeping reports from a single system as compared with multiple systems. MAS held supervisors accountable and ensured that proper intervention was performed and any remediation was completed. The risk management system worked.

Next Generation: Scalability for All Size Agencies with Arx Alert

Police departments of all sizes across the nation face risk. Although suburban police departments may not have the same levels of risk that Detroit had, the risks still exists. Categorically, the risks that departments face are use of force, citizen complaints, vehicular-incidents, overtime, intake, and lawsuits. In many cases, smaller police departments might have higher risks due to a lack of updated best-practice policies, outdated systems, and siloed systems purchased in different decades.

A system like MAS could benefit these smaller agencies, but the architecture and support required would not meet their financial budget. We needed to develop a new cloud-based platform that provided the benefits of a multi-million dollar risk management system only major cities can afford, at a fraction of the cost. In addition, we need to provide a new modern A.I. engine that was able to adapt to agencies of all sizes. Our solution is Arx Alert.

Arx Alert is a cloud-based risk management platform that is accessible and affordable to agencies of all sizes. We are able to provide the benefits of major city solution such as digitization of paper-based forms, A.I. risk identification, A.I. assisted remediation, and built-in business intelligence at a fraction of the cost. Whether you have 25 officers or 2,500 officers, Arx Alert is able to meet the unique needs of the agency within budget, saving money, reducing risks, and improving image.  


Real Time Law Enforcement Administration

Arx Alert Featuring Chief Charles Craft.jpg

Operating in Real Time

We have become accustomed to living in a world that operates in real time. Retailers, box offices, delivery services, restaurant reservations, in-car GPS and television news all provide us with information that is accurate to the moment and updated as conditions change. You think of it, and there’s an online service or application that provides you with the information you seek on a 24/7 basis. As well as being a convenience, real time technology allows users to identify situations that require immediate action and make decisions without delay. This point was demonstrated to me during a recent car trip when my GPS alerted me to a developing severe traffic congestion situation, which allowed me the opportunity to re-route.

Real time technology allows users to identify situations that require immediate action and make decisions without delay.

As real time experiences have become the standard by which we operate, we’ve also developed the expectation that all product and service providers respond to inquiries, demands and changes in the same fashion. If the data is available, the public expects an immediate and accurate response. This technology benefits more than just the consumer. It also allows producers, retailers and service providers the ability to avoid costly and reputation damaging errors.

Operationally, law enforcement has recognized the need for and benefit of real time response to service demands and has embraced the technology necessary to enhance response capabilities. For example, CompStat and Data-Driven Policing philosophies utilize technology to analyze data in real time and provide law enforcement managers with the information needed to allocate and direct resources. There are many other examples of technology utilized by law enforcement to facilitate real time response to data as it is processed. While the primary beneficiary of real time response are the citizens we serve, law enforcement agencies also benefit in terms of reduced cost, improved officer safety and enhanced public perception.

Identifying and Mitigating Risk in a Real Time Standard

The administrative side of law enforcement has been much slower to identify and implement technologies that would bring the management of internal processes and personnel into real time. As a police chief, much of my time was dedicated to identifying and mitigating risk. All too often I found myself in a reactive mode; I was searching for information necessary to respond to some incident or conduct that had already occurred. The search for that information took me to multiple files and databases. I’m sure that all police executives have performed such exhausting research and experienced the disappointment in finding that based on past performance, the incident or conduct was predictable and may have been avoided had intervention and remediation occurred.

In an era where law enforcement activity is live streamed and scrutinized at an unprecedented level, police executives must leverage technology to enhance their administrative capabilities.

Given the demands placed on law enforcement leaders, it is reasonable to argue human beings cannot, in a timely fashion, correlate, analyze and formulate a response to the vast amount of data gathered. However, workload and human capabilities mean very little in terms of civil liability. The legal concept of “known or should have known” requires that police chiefs and law enforcement executives have systems in place for identifying and mitigating risk in a real time standard. In an era where law enforcement activity is live streamed and scrutinized at an unprecedented level, police executives must leverage technology to enhance their administrative capabilities. Failure to do so will expose the executive and their agency to increased liability and a loss of public confidence.