Problem Solving and Decision Making

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problem and problem solving pdf

  • Linda Drake Gobbo 3  

Part of the book series: Advances in Group Decision and Negotiation ((AGDN,volume 3))

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Problem solving and decision making in multicultural work teams are the last of the skill areas to be covered in this book. This topic will be discussed from the cultural, individual, and organizational levels of multicultural team development, building on the frameworks that have been presented in previous chapters. Many theorists consider problem solving and decision making as synonymous-all decisions are made in response to a problem or opportunity. Simply stated, if problem solving is the process used to find a solution to the problem, challenge, or opportunity. However, how one solves problems can be quite varied. An individual can use analytical tools based on logic, deduction, or induction, or intuition based on an understanding of principles, or creative thinking. Problem-solving abilities and approaches may vary considerably, actually using different paradigms or frameworks. In this chapter one approach, with the steps and methods to do problem solving in work teams, will be presented.

There are six steps to the problem-solving model described and demonstrated in this chapter. Several of those steps within the model are used for decisionmaking, and are covered as well. How a team makes the decision, and who on the team makes it are important elements and will also be discussed. As prior chapters have noted, membership of multicultural teams varies greatly. The procedures each member follows, the different value orientations guiding their behavior (Smith et al. 2002), the nature of the tasks they must complete, and the communication tools they employ (face-to-face and/or technology-based) all impact how they approach problem solving and decision making. When done effectively, problem solving, which includes decision making, moves through all the steps described here equally, engaging the knowledge and skills of all team members.

This chapter will first present theoretical frameworks for problem solving, then define the steps that comprise problem solving and decision making within them. This will be followed by a discussion of the cultural variations, and impact of individual styles and societal assumptions on decision-making. Shared mental models and consensus are offered as methods to equalize participation in team decision making, and an overview of other methods provided. The last section will look at ways to coordinate the stages of team development with the variety of problemsolving and decision-making techniques in order to maximize a team’s effectiveness.

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Gobbo, L.D. (2008). Problem Solving and Decision Making. In: Halverson, C.B., Tirmizi, S.A. (eds) Effective Multicultural Teams: Theory and Practice. Advances in Group Decision and Negotiation, vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6957-4_9

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Opinion: Competent caring and problem solving go hand in hand

The world's leaders could learn some important lessons from the dedicated staff at Miles Hospital in Damariscotta.

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Caring is the key to happiness, success and respect alike. The capacity to care is a universal human potential that must be developed and nurtured as part of our spiritual, intellectual, ethical substance. Failing that, we remain – in my father’s words to me, back under Hitler’s rule – “lightweight for a grownup size.” Indeed, just like flotsam rises after a ship has sunk, lightweights around me have kept rising to the top as institutions and societies compromised their values and started sinking. Naïve believers often mistake such rises for “success,” even inspiration.

As the home stretch of this year’s elections unfolds, we hear calls for saving democracy and honest politics, even as we sometimes wonder whether a world order based on such honesty is even possible. Actually, there are working models of honest, caring, democratic collaborations, ready to be adopted and upscaled.  My family and I found such a model in Damariscotta’s Miles Hospital when my wife, in pain, checked in at their emergency room in the middle of the night. Her diagnosis: appendicitis. During surgery the appendix was found to have burst, prolonging the post-operation recovery.

ABOUT THE AUTHOR

Paul F. Kando is a resident of Damariscotta.

Post-operative care was an exemplary combination of science, skill and care, delivered by a multiracial, multiethnic nursing staff – from north, south, Canada, Haiti, Colombia, the Philippines and more. They kept track of vital signs and healing progress, keeping the doctors informed. And they cheerfully kept their patient as comfortable as possible. Beth was released from the hospital eight days after her surgery.

What we experienced is also a great model of successful problem solving, one that I, as an engineer, can sum up as the keys to creative competency. They are:

(1) Conduct research. Peruse prior medical-scientific findings, diagnostic tests, monitoring patient progress. Research is the only reliable way to discover reality – e.g., the appendicitis diagnosis and the results of patient monitoring – the only things that matter. From private lives to unfolding world history, everything is a series of real occurrences.

(2) Truth – e.g., the information shared by members of the medical team – is simply information that describes reality. Misinformation, propaganda, beliefs, denials, lies, and so on, are but damaging distractions from truth and reality, with potentially dire consequences. Advertisement

(3) Questioning and critical evaluation – how members of the medical team decide the appropriate treatment and medications, for example – are the only way to ascertain the truth, and the validity of information from any source.

(4) Respect must be earned by individuals, officials and institutions alike. They earn it by being truthful and caring about the needs of others. Mutual respect is what makes professional collaborations, like those at Miles, possible. Liars, narcissists, hiders behind assorted uniforms may demand, but cannot earn respect.

(5) Equality and mutual respect are the only basis on which diverse people can peacefully and productively work together. We humans are, without exception, equals as members of small minorities within Earth’s great population – of one diaspora among many that may or may not earn the acceptance and respect of the others as citizens of this diverse, multicultural world. This diverse equality is both a comforting fact and a challenge.

I have found the above five key principles applicable to all problems I have been challenged to address. The same simple principles are key to addressing climate change, the Gaza fiasco and this 2024 election season. They define and demonstrate what’s possible. So, the Miles Hospital medical team has much to teach leaders, public servants and citizens alike on both the national and international levels – to act with care, and only on the basis of reality and truth; and to avoid falsehoods, power games and demagoguery. Because only real things matter, i.e., only the facts, uncontaminated by falsehoods, power games and manipulated beliefs.

Sick climate? Ailing country? Warmongering? Demagoguery? Endangered democracy?

What and who could stop us from being diverse, committed caregivers for this country working together?

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Nice’s 1cx could be a game-changer for solving knotty customer problems.

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Imagine that one of your customers is experiencing a problem with a product or service that they have purchased from your company. Wanting to find a fast and easy solution to their problem, they land on your website, but after searching your FAQs and interacting with your chatbot, they realise they won’t be able to find the answer to their problem. It’s a little too complex.

They then decide to call your contact center to seek help. Once they get through to an agent and explain their issue, the agent quickly realises that the customer’s problem is quite complex and not something that they themselves will be able to help with. It will require the assistance of one of their colleagues in the back office. However, rather than asking them to call another team or placing them in another queue, they remember that they helped a customer with a similar issue last week and, in particular, how one of their colleagues in the back office team had been a great help.

Asking the customer to bear with them for a moment, the agent checks their system to see if that colleague is available and quickly messages them to see if they can help. Their colleague quickly responds saying that they can help, and the agent proceeds to loop their colleague into the conversation. Introducing their colleague to the customer and explaining the situation, the agent then takes a back seat in the conversation whilst their colleague helps the customer. This takes a few minutes, so while they wait for the issue to be resolved, the agent catches up with some administrative tasks and answers a few emails from other customers.

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Customer support agent

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Solving the Overlap Query Problem in PostgreSQL

Lee Asher

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problem and problem solving pdf

Range queries are a very common task in SQL: selecting dates, numbers, or even text values that fall within some specified range. For instance: all loan applications for the month of March, or all sales transactions between $50 and $500. SQL developers are generally adept at writing such queries and indexing them to ensure they perform well.

But when the requirements are changed slightly — to compare two ranges of values to find where they overlap — it’s suddenly a whole new ballgame. These so-called “overlap queries” are trickier than they appear.

Overlap Queries

The most common overlap queries involve temporal (date and time) ranges, known as intervals . For example, imagine a query for patients at a hospital. If you wish to find all patients initially admitted during the month of August, that’s a simple range query. But if you wish to find all patients whose duration of stay — another date interval — lies at least partially in the interval of August, that’s an overlap query. While writing such queries isn’t hard, writing them to perform well can be difficult. Let’s see why.

A Use Case Scenario

Let’s examine an actual problem involving an overlap query. The database for a large museum tracks the time all visiting patrons enter and leave the building. It also maintains the times of all outages in its video security system. After a rash of minor thefts, the head of security has asked for a list of all patrons who were present during one or more security outages. Clearly, we have one datetime range, the length of a patron’s stay, which must be compared with another, the interval denoting a security outage. The goal is to find all overlapping instances.

The Database.

A table of patrons contains an initial and final timestamp indicating the duration of the visit and an id indicating the associated patron. And an outages table similarly defines the start and end timestamps of each outage. For simplicity, we include no other columns.

TABLE patrons ( patron_id  INT  generated always as identity NOT NULL, enter      Timestamp(0) NOT NULL, leave      Timestamp(0) NOT NULL ; TABLE outages ( location_id INT generated always as identity NOT NULL, start_time  Timestamp(0) NOT NULL, end_time   Timestamp(0) NOT NULL ;

To test performance on a large dataset, we’ll populate both tables with 20 years of random data. (The script to fill the tables is in the Appendix section that follows the Conclusion section at the end of the article.)

In SQL, the canonical way to compare intervals is with the OVERLAPS() operator. To find all cases of overlap, simply form the dates from each table into intervals, then compare with this operator:

* patrons p CROSS JOIN outages o (p.enter,p.leave) OVERLAPS (o.start_time, o.end_time);

This query works — it retrieves the appropriate rows, at least — but it’s extremely slow. (On my test system (Windows 11 with PostgreSQL 16, test machine is an AMD 5700x CPU, 2GB SSD, Windows 11), it takes 3+ minutes). A first attempt to optimize the query might lead you to create a composite index on outage start and end time, and a similar one on patrons:

INDEX ON outages USING BTREE(start_time, end_time); INDEX ON patrons USING BTREE(enter, leave);

No help: the query is just as slow A little research finds that the OVERLAPS operator doesn’t support indexes. So instead, we specify the comparisons explicitly.

The first time you attempt a query like this, you’ll likely draw lines on a sheet of paper and see there are four different ways two intervals can overlap (see graphic.) This makes a rather complex query, but we can simplify it with a little trick. There are only two ways that intervals don’t overlap. If we write the non-overlapping query, then invert with a NOT, we get the desired result.

problem and problem solving pdf

For example, a WHERE clause to find all non-overlapping cases for interval1 and interval2 looks like this:

interval1.start > interval2.end OR interval2.start > interval1.end

If we invert the entire query with NOT , we find all cases of overlap

NOT (date1.start > date2.end OR date2.start > date1.end)

This simplifies (using Boolean logic rules) to:

date1.start <= date2.end AND date2.start <= date1.end)

(Note: The query is written to conform to the SQL standard on temporal intervals, which states that overlap occurs if one interval starts exactly when the other ends. This means that values that overlap by exactly 0.00 seconds are included. If you wish to require a minimum amount of overlap, adjust your queries accordingly)

So, what did we accomplish? Well, the explicit form is somewhat faster (26.1 secs), but an actual production table can be orders of magnitude larger than these samples.. We’d expect a query like this to be lightning-quick. Examining the access plan, we see PostgreSQL combining a table scan with an index scan — no indexed lookups are being used.

In a final bout of desperation, you might break the composite indexes each into two separate indexes: one for each timestamp. This not only doesn’t help, but (if you removed the original index) it will be just as slow as the original OVERLAPS() form. What’s wrong?

The Trouble With B-Trees

Like the name suggests, a B-Tree index contains a branching structure of values on the indexed column; traversing the tree allows one to find a specific value or any contiguous range of values. For composite (multi-column) indexes, the second column affects ordering only where the first column has multiple equal values: the second column acts as a “tie breaker”, as it were. Similarly, the third column comes into play only for ties on the second, and so on. This is easier to understand visually. See the following image:

problem and problem solving pdf

Notice that our compound index (start date + end date) has little effect on row ordering compared to the simple single-column index. And neither one groups rows in a manner that allows us to quickly find all overlapping values. Rows which overlap our query range (shown in green ) aren’t in order, and so our index doesn’t help. The entire table must be scanned.

That’s bad enough when that interval is a fixed value, but when the interval comes from another table (or a self-join on the original table), it means every row in Table A must be matched against every row in Table B. In technical terms, this is quadratic performance — doubling the number of rows means the query must do four times the work. On very large tables, a query like this will hamstring even the most powerful servers.

A Cheap Trick

Before we look at a more sophisticated approach, there’s often an easy way to “hack” overlap queries. The idea is to give the QO (query optimizer) information that we have, but it doesn’t. In our example, the tables span years of timestamp values, but any single event is much shorter.

If we can identify a maximum duration for either type of event and pass that information onto the QO, it can scan a much smaller portion of the index. For example, in our data, no patron visit is longer than 4 hours. We can add this information to our query in the following manner:

* patrons p CROSS JOIN outages o p.enter <= o.end_time AND p.enter >= o.end_time - '1 hour'::INTERVAL*4 --<< AND p.leave >= o.start_time;

The new clause (suffixed with –<<) means there is now both a minimum and a maximum value on p.enter . This converts the statement into an (index-serviceable) range query. Assuming you still have an index on this column, the effects on query time is dramatic: it shrinks all the way from 26 seconds down to 0.1 second. Wow! Suddenly we have a practical query.

Instead of setting a maximum range on patrons, we could have done the same for outages. Or better, both tables. The query optimizer won’t use both at once, but it will use the one it believes to be most efficient.

The great advantage of this technique is that it allows you to use the indexes you likely already have. However, be careful! If any data ever exceeds this maximum duration, it will be incorrectly filtered from the results. For instance, a patron row with a duration of 6 hours will be invisible to this query, no matter how many outages it overlaps. If you use this method, ensure to base your durations on business rules unlikely to change, rather than simply assuming future events will be similar to those in the past.

GiST: The Way Forward

PostgreSQL offers an alternative to BTree indexes, called GiST. You may have encountered GiST indexes in connection with querying two-dimensional data like geometric objects or geographic regions. However, these indexes are equally adept at indexing one-dimensional date, time, and numeric ranges. GiST, which stands for Generalized Search Tree , is exactly what we need for cases like this.

To create the necessary index for our example, we form the two timestamps into a range type with the tsrange() function:

INDEX ON patrons USING GIST(tsrange(enter,leave));

GiST indexes also uses a special syntax to compare ranges for overlapping values: the ‘ && ‘ operator. Using this operator, our query now looks like this:

* patrons p JOIN outages o tsrange(o.start_time, o.end_time) && tsrange(p.enter, p.leave);

That’s all there is to it. This query now runs in an execution time of 0.56 secs; nearly as fast as our “hack” from above. And unlike that method, this works correctly in all cases, even if some events have very long durations. There’s no need to worry about the occasional longer-duration event being incorrectly filtered out.

The GiST index converts our original quadratic-performance query to linear performance. We can see that by increasing our sample data row counts by a factor of 10. With one million patrons and 250,000 outages, the query time increases by the same factor, to 5 seconds, whereas the OVERLAP() query form would have taken several hours. But for extremely large tables, linear performance may still be too slow.

In Part II of this article, we’ll examine the possibility of further improvements.

Conclusion.

A seemingly simple operation in SQL like finding overlapping values has some surprising pitfalls. Understanding how to form and optimize queries like this is something all SQL developers should know. Using the techniques above, you can achieve large performance gains, and satisfy performance-hungry users.

Appendix: Script to create Initial DB and populate with random data

INTO patrons (enter, leave) r, r + '1 minute'::INTERVAL * (1+RANDOM() * 120) (SELECT NOW() '1 minute'::INTERVAL * ROUND(RANDOM() * 15768000) AS r FROM generate_series(1,100000)) AS sub; INTO outages (start_time, end_time) r, r + '1 minute'::INTERVAL * (1+(RANDOM() * 30)) FROM (SELECT NOW() '1 minute'::INTERVAL * ROUND(RANDOM() * 15768000) AS r FROM generate_series(1,25000)) AS sub; FROM patrons WHERE enter > leave; FROM outages WHERE start_time > end_time;

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problem and problem solving pdf

Lee is a 20 year industry veteran who has worked with IBM, AT&T, and many other firms. He holds a degree in physics, and more than 30 software-related patents. He currently works as a project consultant, specializing in database design and optimization. He can be reached at [email protected].

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Partitioning in PostgreSQL was for many years a feature almost entirely ignored, and even today is often thought of only as a means to increase...

Justin Steele’s setback puts the Chicago Cubs into problem-solving mode again

Aug 22, 2024; Chicago, Illinois, USA; Chicago Cubs starting pitcher Justin Steele (35) pitches during the first inning against the Detroit Tigers at Wrigley Field. Mandatory Credit: Patrick Gorski-USA TODAY Sports

CHICAGO — Craig Counsell stood up and exited the Wrigley Field interview room so quickly that reporters didn’t have enough time and presence of mind to compute the announcement and ask the Chicago Cubs manager any follow-up questions.

“ Kyle Hendricks is going to be the starter tomorrow,” Counsell said after Monday night’s 5-3 loss to the Pittsburgh Pirates . “We’re going to scratch Justin Steele . He’s experiencing some elbow soreness.”

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The Cubs had been rolling to such an extent that the blown save and the postgame news became a disorienting combination. Jorge López , a dominant reliever for the past two months, was sitting at his locker and waiting for the media after giving up a game-tying, three-run homer to Bryan Reynolds and then the go-ahead home run to Andrew McCutchen in the eighth inning. Pittsburgh’s flurry snapped a six-game winning streak, part of a run when the Cubs won 12 of 15 and appeared to be peaking at the right time.

Those long-shot odds to reach the postseason became more remote with the uncertainty surrounding Steele, the homegrown lefty who has a 3.28 ERA in 85 career starts for the Cubs and a confidence that can be felt by the entire team. There goes what was supposed to be Tuesday’s marquee matchup at the Friendly Confines: Steele vs. Paul Skenes .

“Steele’s been awesome the last couple years here,” Cubs pitcher Jameson Taillon said after throwing seven scoreless innings in the Labor Day loss. “When you see Steele on the mound, you know you’re going to get a good effort and you’re going to be in the game. It stinks. But from everything I heard, we’re hoping it’s just a quick thing. He means a lot to this group. That being said, we just got (Jordan) Wicks back, which is awesome. We’ll just continue to keep going and step up.”

This season will still be a failure if the Cubs don’t make the playoffs. And Counsell could still push for big changes this offseason. But a manager who has spent a lot of time in observational mode has noticed the group’s ability to solve problems.

With a few exceptions, Counsell largely inherited David Ross’ coaching staff after he decided to leave the Milwaukee Brewers for a five-year, $40 million contract. The Brewers rallied around Pat Murphy, Counsell’s longtime bench coach and college coach at Notre Dame, preventing a mass exodus and ensuring some continuity.

The Brewers have already spent 153 days in first place in a year when Cubs chairman Tom Ricketts showed up for spring training and said: “I don’t see any reason why we wouldn’t be favored for our division.” Ricketts also declared this should be the standard: “Any year we don’t make the postseason is a disappointment.”

The Cubs (71-67) still have two teams in front of them racing for the National League’s last wild-card spot. The Cubs trail the Atlanta Braves by 3 1/2  games. The New York Mets are now only a half-game behind the Braves. The Cubs would lose the head-to-head tiebreaker against both teams. The Cubs are also a different club than the one that already lost the season series against the Braves and Mets, showing significant signs of improvement and adaptability.

The only reliever remaining from Counsell’s Opening Day bullpen is Drew Smyly — and the Cubs put him on waivers last week to try to save money. Adbert Alzolay , Julian Merryweather , Yency Almonte and Luke Little are on the injured list. Héctor Neris and José Cuas were both designated for assignment. Mark Leiter Jr. was traded to the New York Yankees in a deadline deal that focused on 2025 and beyond.

Jed Hoyer’s front office kept accumulating “out-getters,” Counsell’s term for flexible pitchers who remain available and operate without overly defined roles. Tyson Miller , Porter Hodge and López — who has not allowed a run in 19 of his 22 outings with the Cubs after getting released by the Mets — are among the finds that have turned this bullpen into a strength.

A group of pitching coaches led by Tommy Hottovy have also helped make Shota Imanaga ’s rookie season a smashing success. Taillon remains consistent and dependable, showing why the Cubs invested $68 million in his future. Steele has solidly built off last year’s All-Star season, despite straining his hamstring on Opening Day and dealing with this newly disclosed elbow issue.

A group of hitting coaches led by Dustin Kelly have helped implement significant in-season swing adjustments for Pete Crow-Armstrong and Miguel Amaya , adding new dimensions to the bottom of the lineup. Center fielders and catchers with two-way skills are extremely difficult to find. During this second-half run, the Cubs may have confirmed that they already have both of those rare types of players.

“Like the players, it’s staying in the fight,” Counsell said. “It’s staying with it. Keep coaching. Because things can turn. We don’t get to (pick when). You just don’t predict it. In the marathon of a season, there is time. Even though you can say there’s not, there’s time. So I think we’ve done a really good job of continuing the coaching and continuing the teaching. And not letting something just be the way it is and (saying): ‘We can’t figure this out.’

“We’ve stayed in the fight in that way. And then the players have stayed in the fight. It’s good to get rewarded with some positive results. That kind of validates your work. And I think, in the coaching staff’s case, it certainly has validated some of their work.”

That work, however, never feels done in early September. With or without Steele, the Cubs again have to regroup.

“We’re chasing — that in itself creates urgency,” Counsell said. “We know we have to play at a really high level because we’ve got significant ground still to make up. But we’ve also, in a sense, earned this. We’ve earned the right to have some fun this month and play some good baseball and see what happens.”

(Photo: Patrick Gorski / USA Today)

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Patrick Mooney

Patrick Mooney is a senior writer for The Athletic covering the Chicago Cubs and Major League Baseball. He spent eight seasons covering the Cubs across multiple platforms for NBC Sports Chicago/Comcast SportsNet, beginning in 2010. He has been a frequent contributor to MLB Network, Baseball America, MLB.com and the Chicago Sun-Times News Group. Follow Patrick on Twitter @ PJ_Mooney

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