Ukraine Urban Recovery: Of Mines and Metrics, 3 of 3
Brutal Catalyst: What Ukraine’s Cities Tell Us About Recovery From War, available at: https://www.amazon.com/dp/B0DJ8Q7BGJ
A continuation of discussions drawing on Brutal Catalyst: What Ukraine’s Cities Tell Us About Recovery From War, released October 8, 2024.
Ukraine urban recovery Blog 12: Of Mines and Metrics, 3 of 3 (A continuation of discussions drawing on Brutal Catalyst: What Ukraine’s Cities Tell Us about Recovery from War released by KeyPoint Press October 8, 2024; more info at www.ukrainecities.com)
Whether in terms of demining or other functions, the burden on metric designers tasked with tracking Ukrainian cities’ recovery is a heavy one. Reports will have to inform (and thus be comprehendible to) managers at multiple Ukrainian government echelons and organization types, funding nations’ representatives, private donors, NGOs, IGOs, and others. That implies considering these organizations’ perspectives during the metrics-creation process (as otherwise the metrics might provide information of little interest to one or more parties). The topic of Ukrainian corruption provides a prime example. The matter is not simply one of whether corruption is sufficiently constrained. Corruption of concern to one set of donors will be of little interest to others. Corruption metrics need to be dynamic as well, necessitating periodic revisiting by their designers. The corrupt are nothing if not adaptable. They quickly learn how to game existing countermeasures and metrics to their benefit. Designing agility into measures, therefore, makes adaptation easier for those seeking to contain corruption. Such agility also helps to avoid the jolting consequences of having to create and present entirely new metrics as conditions evolve. The source reporting Maersk’s initial metric misstep (of mistaking time spent per call as a legitimate measure) went on to observe, “often the problem stems from new regulations being introduced without thinking through the implications.” (Recall our earlier observation regarding the need to consider a metric’s second and higher-order effects, which can be positive or negative.) This highlights the value of what the military calls wargaming, a procedure that includes representatives from relevant parties presenting their perspectives in the service of determining a draft plan’s strengths and vulnerabilities. The name notwithstanding, it is a process with application to far more than military contingencies. A key component of wargaming is the sequence of action->reaction->counteraction. Assuming an adversarial situation is the game’s focus, one party initiates an action in support of its identified objectives. The players representing the opposition (and any other pertinent individuals or groups) identify possible reactions, the original initiator then considering options on how it would counter the reaction. The eventual outcome should be more robust and effective plans or procedures. To assume the adversary (corrupt parties in our example here) is other than smart, connected, and adaptive is self-defeating. Effectively wargaming possible courses of action in terms of dealing with corruption thus needs to go beyond today’s objectives to consider how goals will have to evolve in order to respond effectively or, preferably, stay a step ahead of corrupt individuals’ maneuvers. Yet dealing with corruption is but one facet of recovery from a disaster
Metrics are managers’ GPS. Leaders establish goals and plot a course for their accomplishment. Chances of success are slim if they don’t know whether they are on or off track. Successful recovery requires not just understanding how the uncountable (and everchanging) pieces of the whole fit together. It demands managers seek out and take advantage of available synergies. Synergy during recovery means more than merely the whole being greater than the sum of its parts. It comes to encompass timeliness, accurate scoping, minimizing waste, and resilience in the face of changing conditions.
One might not be able to predict the future – to determine exactly what will happen and where and when an occurrence will take place. But effective metrics can aid in forecasting the likelihood of possible outcomes: They can point to possible results and provide reasonable probability estimates each will come to be. (This discrimination between “prediction” and “forecasting” is my own.) This in turn provides a basis for calculating risk. Lucius Clay put education on the back burner early in his tenure as leader of US occupation forces in post-WWII Germany, assigning priority to food provision. The choice seemed the logical one…at first. But rarely are recovery decisions of an either-or nature. They are instead judgments regarding proportion. What percentage of resource A is best allocated to need 1 vice needs 2, 3, or otherwise?
Perfect understanding of how a recovery system’s parts create a whole and influence each other is management nirvana. It isn’t going to happen. Having a reasonable grasp is nonetheless essential to reduce the risk of failure. Successful recovery, like war waged well, demands a systems approach to orchestration. Consciously capitalizing on synergistic relationships constitutes systems management at rarely attained levels, levels artificial intelligence might in future years make regularly achievable. In the meantime, pursuit improves outcomes even when it falls short of perfection. That pursuit is inestimably aided by effective metrics.
Successful aid delivery during recovery is inevitably multi-faceted. Measuring its effectiveness is a function of many variables. Among them: (1) What is delivered (Does it meet recipient needs?), (2) What form delivery takes (Are recipients—or aid providers for that matter—unnecessarily put at risk?), (3) Does the aid undermine economic recovery?, (4) Who receives the aid? (Does it go to individuals or groups actually in need?), and (5) When and where does delivery come (Does it arrive in a timely fashion where needs exist?). Dropping aid in a convenient location without arranging for follow-on transport might tick the “delivered” block for the lazy or scared when recipients are in a threatening location. Favoring recipients with marginal if any need because they reside in relatively safe locations is not unheard of. Such aid corruption allows providers to report favorable statistics and thereby garner further funding. The ability to provide guidance for delivery to those most in need and monitor whether appropriate whats, whos, whens, and wheres are on the receiving end remains a mark on the wall not always reached.
Our previous example of police training makes it clear that careful definition and monitoring of how users employ a metric is crucial to its value. The below example from Ukraine demonstrates how shortcomings in metric design, misleading reporting (deliberate or otherwise), and inattention to conditions on the ground can otherwise combine to misinform and lead to waste:
One food kit can support three people. Regardless of how many it was actually helping, it was being recorded as going to three people. Taking reporting shortcuts like that is pretty common in NGO work. Some INGOs [international nongovernmental organizations] were going to big cities and distributing aid to those who didn’t really need it [because it was easy. One mega-donor] adapted and demanded rural distribution as well, but not until mid-2023. Until then it was a wild west environment and they only cared about how much money was spent. (This quote is from an interviewee who asked to remain anonymous.)
To review, quality metrics focus on effects, avoid motivating negative behaviors, encourage positive behaviors, and provide sufficiently granulated results to support decision-making at all relevant echelons and across all pertinent organizations. Creation of ready-to-use metrics waiting “on the shelf” for immediate use once recovery operations begin would be a leap forward. These standing metrics would need adaptation to fit local or evolving conditions once a recovery undertaking began. More effective aid organizations already employ solid practices in this regard.
Rather than providers making assumptions, representatives gauge needs by requiring recipients to complete preliminary questionnaires with questions such as “Are your family members skipping meals?” Following up with the same question after aid delivery begins provides a basis for refining support. Managers can also adapt base aid levels when assisting elderly, special needs, or other exceptional recipients. Familiarity with an environment can spawn further efficiencies. Delivery of some aid via Ukraine’s Ukrposhta (National Postal System) might be feasible, for example, as Ukrposhta is well regarded in the country and a proven quantity. The organization has long distributed pension payments and has control mechanisms in place to reduce fraud, e.g., representatives require identification verification before making disbursements. Alternatively, cash cards or payments to mobile phones via apps allowing remote replenishment can be even quicker and cheaper when local conditions permit.
Metrics design is both art and science. It has its experts, but experts require assistance by those familiar with the activities for which measures are needed. Getting it right is tough. Our several examples over these three blog posts demonstrate that getting it wrong promises inefficiency, ineffectiveness, waste, and—potentially—far worse.
Last post’s trivia question: “There are 45 sets of brothers buried in the Normandy American Cemetery. Two of those brothers have the last name "Niland." Why might you know of them...but by a different name?”
Answer: The brothers underlying Tom Hanks’ mission in Saving Private Ryan were actually based on the Niland brothers, two of whom were killed in Normandy (and are those buried in the cemetery there), another who was thought dead in the Pacific but was actually a POW with the Japanese and returned after the war. The remaining brother (who was pulled out of combat due to the Sole Surviving Son policy), played by Matt Damon in the movie, was Fritz Niland. Spielberg changed the character's name to sound less German, thus Saving Private Ryan instead of Saving Private Niland.
Next question (bit of a trivia change of pace): As of mid-2024, how many of the Baseball Hall of Fame’s members were World War II veterans?
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Russell W. Glenn, Brutal Catalyst: What Ukraine’s Cities Tell Us About Recovery From War (Boulder, CO: KeyPoint Press, 2024). Available in hardback, paperback, and eBook at https://www.amazon.com/dp/B0DJ8Q7BGJ.
For media inquiries and review copies, email: editor@keypointpress.com
Discover more about the war in Ukraine and recovery at: www.ukrainecities.com
KeyPointPress: www.keypointpress.com
