Category: Driving Action with Analytics

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Tips for Leaders – Driving Change with Stories and Numbers

One of the biggest challenges that leaders face when driving change is getting everyone on board with the new direction. A powerful tool that Change Leaders can use is the combination of story-telling with numbers. When done right it can create the inspiration and momentum that both makes the change initiative happen and makes it stick. Here are some tips that leaders can use to get started:

Tip 1: Brainstorm the story
Chances are if you’re the Change Leader that you already know inherently why you want to drive the change. So the first challenge is “How do I transfer my excitement to other people?”

One of the best tools for getting people on board is the use of stories. Stories have the power to take boring, dry facts and make them personal and memorable.
Telling stories with numbers
A good source of relevant stories can be those that describe the frustration that people experience in the current state. These can be situations where things don’t work like they are supposed to, situations involving missed opportunities, or just things that are just plain annoying. A well-crafted story will be engaging and memorable, and inspire the listener to take some action. You’ll want to keep it short, because if things go right you’ll be telling this story over many times.

A major benefit of using a story is that the listener is more likely to remember it, and if the story is engaging then the listener will be inclined to retell it to others. Ideally you will have a story that will connect with the different types of people involved in the change, from the leadership team down to the front line, but if not, you may consider developing different stories for different audiences.

Once you have a few story ideas you can start thinking about the next step … finding the numbers in the story.

Tip 2: Find the numbers in the story
Many of your listeners will be on board after hearing your compelling story, but the more cynical listeners will say “That’s a great story, but it’s just an anecdote.” So the next challenge is finding the numbers both in the story, and the numbers that translate the story to the bigger picture.

When looking for numbers in the story, you may want to think about:

  • How bad was the situation? Can parts of it be measured and quantified? For example, if the story is about a situation where a customer was dissatisfied about a long wait, how long was the wait? To put it in context, how much longer was the wait in comparison to the industry standard?
  • What efforts went into fixing the bad situation? Did the bad situation result in many different people getting involved? If so, how much time did they spend? For example if the dissatisfied customer spent time with the manager, then with customer service, and then finally escalated the complaint to the leadership team, how many hours of effort went into trying to fix the situation?

When translating the numbers in the story to the big picture, you may want to think about:

  • How often do situations like this occur? Is this a one-off, or does this problem repeat itself every day? If the bad situation occurs frequently, what is it costing your organization?
  • If you don’t know how often this occurs, how frequently does it need to happen for it to be important? For example, in situations involving a person’s safety, one bad occurrence might be enough for it to be important.

Now that you have the story, and the numbers that back it up, the next step is to connect it back to the change you’re driving.

Tip 3: Make the hero of the story be the change
In the best stories the main character faces a challenge that seems impossible, and then somehow figures out how to overcome that challenge. The hero can be the person who came up with the bright new idea, or even better, can be the improvement idea itself.

As the Change Leader, you will want to find the connection between your change initiative and how the hero of the story overcame their challenge. For example, if your change initiative is about reducing wait times for customers, and if your change initiative involves a new screening process to identify customers with complex requirements, then the hero of the story can be the bright team member who thought of the idea, and the manager who was willing to try it out to see if it would work.

Tip 4: Performance manage with the story
You can take your story-telling even further by linking it to your performance management. It can be as simple as tracking the key numbers in your story on an on-going basis, and setting performance targets around them. Tracking tools can range from a good old fashioned white board to a fully automated electronic dashboard – the main thing is to measure what’s important, and to have the discipline to stick with it.

As you review the performance measures with your team, take every opportunity to refer to the characters of the story, and the situations that they went through. This will remind the people involved in the change why this is important, and will also help get new members of the team on board as they hear the story for the first time.

If you’re a numbers person, you might not have much experience with telling stories. If so, a great resource on storytelling is Peter Guber’s “Tell to Win”. His book describes the important components of any memorable story.

Hopefully these tips will help Change Leaders use the powerful combination of story-telling and numbers to drive change. There are many experts out there that I’m sure will have more to add. Please feel free to weigh in with your point of view.

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Tips for Change Leaders – How to Show Your Impact

We work with a lot of leaders who are responsible for driving change. A common question that they ask us is “How do I show the impact of what we’re doing?” Of course, they have their standard measures (i.e. improved outcomes, increased cost-efficiency, reduced delays, etc), but the following are some of the tricky scenarios that they share with us:

  • “Our numbers don’t show how well we’re doing … what do I do?”
  • “It will take a while before we start seeing an impact, but I need to show results now!”
  • “The team is really working better now, but we’re still not hitting our targets. How do I prove that it’s worthwhile to keep going?”

Sometimes projects involving change don’t get the support they need to realize to their full potential, but it doesn’t always have to be that way. Here are some tips that Change Leaders can use to set the odds in their favor:

How to Show Your Impact

Tip 1: Begin with the end in mind
In addition to being one of my favorite Stephen Covey habits, beginning with the end in mind is incredibly practical tool for successful projects. When leaders are driving change this concept applies equally well. Some examples of applying this to change initiatives include:

  • Getting crystal clear on how things will be better once your change initiative is complete. Think about the conversations you will have in that future state, such as, “We’re way better at retaining our customers than we were in the past”. Then think about the numbers that you’d like to say to back it up, such as “We’ve decreased our customer churn rate by 60%”. In order to do these comparisons in the future you will need a baseline reading of your current performance. This thought exercise can be an easy way of identifying the performance measures that will be essential to show an impact.
  • If you’ve led a change initiative previously, you probably have learned that things rarely go as well as planned. So, it’s important to set realistic expectations on when you will hit your performance targets. The rule of “under-promise and over-deliver” comes into play here.
  • Many seasoned change leaders also know that there will be some periods in the initiative where the efforts are high but the outcomes are low to non-existent. It’s important to think about the milestones along the way, or the interim performance measures, that can show that you’re making progress in the right direction, and that the initiative should keep going.
  • Where possible, choose performance measures that you have direct influence on. The last thing you want when leading a change initiative is being evaluated on a performance measure that you’re not able to directly influence.

Tip 2: Set yourself up for success
It’s fairly common for change initiatives to generate a lot of excitement, and a lot of positive momentum where the people involved “just know” that they are making a positive impact. But at some point you do have to prove it. Some considerations to set yourself up for success include:

  • Track your performance along the way. Try to avoid what many change leaders do, which is, leave the performance evaluation to the very end. By tracking performance along the way, both you and the team involved can keep your eyes on the numbers that matter, and more importantly, correct the course if things aren’t going in the right direction.
  • Plan for achievable interim wins. It’s easier for a change initiative to be supported if it’s showing incremental progress towards the goal. It’s harder to stay the course when it’s a situation of “just trust me … in 3 years this will all work great”. Give yourself and your change initiative some achievable wins along the way to the finish line.
  • Make sure your numbers tell the full story. If the numbers aren’t trending in the right direction but you know that the change initiative is generating positive outcomes, then it may be time to rethink your metrics. Try and be as creative as possible in thinking through how that benefit can be quantified. Stakeholder surveys can often help round out the full impact of the change. Try to avoid having the performance of the change initiative be strictly based on financial factors alone, or solely on productivity measures. There are costs to “softer” considerations, they are just harder to quantify.

Tip 3: Get some help from a data friend

Not everybody is good with numbers, performance measures, or target setting. If this is you, then do your conceptual thinking of the performance measures and then lean on someone who is good with spreadsheets, data, and/or basic statistics. They will be able to coach you on how you can set up your measures so that a before and after comparison is valid and meaningful. They may even help you set up a tracking spreadsheet if you buy them a coffee!

Hopefully these steps will give change leaders some actionable tools you can use to make sure that you can show the impact of your change initiative. There are many experts out there that I’m sure will have more to add. Please feel free to weigh in with your point of view.

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Tips for Executives – How to Create a Culture of Evidence

We’re often asked how do we create a Culture of Evidence? Most leaders know that they should be more evidence-based in how they work, but don’t know how they can go about doing it.

We’ve all heard the phrase “Culture eats strategy for breakfast” and anyone who’s attempted to drive change in a complex organization knows how true that statement can be. And, many seasoned leaders know that culture change doesn’t happen overnight, but here are some tips that you can use to get started.

Culture of Evidence

Tip 1: Paint a picture of “What a Culture of Evidence looks like”
If you want to make meaningful progress towards creating a culture of evidence, there’s no better place to start than envisioning your future state. Things to consider include:

  • How will life be better? For you, your team and for the company?
  • What opportunities will you be able to access?
  • What risks will you be able to avoid?
  • What decisions will be smarter?
  • What time will be saved?

If you can create a compelling vision of your organization in the future that thrives in a Culture of Evidence, then you can use this to win supporters.

Tip 2: Set the standard for “What counts as evidence?”
In the spirit of “crawl, walk, run”, getting started with using evidence doesn’t have to begin with hiring a team of scientists, researchers and lawyers. To begin with it may be as simple as using data to support your decision-making, carrying out basic research, or using spreadsheets to do “what if” analysis. Most leaders do this already, but many others still rely on their intuition to make their decisions.

The following is an illustrative example of “what counts as evidence?”:

  • A declarative statement of your position such as “I believe that we should launch a social media awareness campaign for our red widgets”
  • Some form of objective proof that shows how you formed your position, such as “According to our market data 85% of our target customers have never heard of our red widgets, and 57% of them use social media. The campaign would be cost effective even if it only generated a 5% increase in our market share.”
  • A disclosure of what you don’t know, such as “Admittedly our market data is one year old, so we’re assuming that the patterns still hold.”
  • An action statement, such as “I’d like to update our market data but the delays and costs outweigh the risk of missing an opportunity … I recommend that we launch the campaign and track performance.”

The ultimate goal of evidence is that it holds up to the review process, meaning that another leader could review the evidence and arrive at the same conclusions. Along those lines, “what counts as evidence?” could be just that … an objective analysis that has been peer reviewed.

Manager Reading Data

Tip 3: Put the tools in place
To set your team up for success, you will want to make sure that the basic tools are available for evidence-based thinking. Some questions to consider include:

  • Are the right investments being made to collect the right data?
  • Does your team have access to the data they need? Is the data being collected at the source, but it’s not being stored in the data warehouse? Or is the data there, but the privacy levels are too restrictive?
  • Do they have the skills for working with the data, or alternatively, is the right information available in insightful reports or visual dashboards?
  • Do they have the right technical and human resources perform deeper analyses, in response to important business questions that arise?

Tip 4: Lead by example
If you want to convince your team and your peers that you are fully behind this idea of a Culture of Evidence, then you’ll need to walk the talk. This will require effort at the beginning, but after a while it will become just “the way things are done around here”. Leading by example can include shifting your own language from “I think this is what we should do …” into “The evidence tells me that this is what we should do …”

It can also include making a concerted effort to not do things the old way because “that’s the way we’ve always done it” but instead doing things in ways that are proven to generate the right outcomes. This relates to everyday decision-making and operations, as well as longer-term strategy and planning.

Tip 5: Reward the adopters
It is often said that “you get what you reward”. This is an easy concept to apply to building a Culture of Evidence. For example you can reward your team for using evidence in situations like:

  • Decision-making on special projects: Projects that have proposals that have supporting evidence are often approved, whereas other projects often don’t.
  • Decision-making on budget: Budget increases (or exemptions from budget cuts) are generally provided to those departments that can prove that they need it, whereas departments that can’t prove their value miss out.
  • Decision-making on promotions: Team members that demonstrate the effective use of evidence are generally promoted to higher positions, whereas other team members don’t.

By taking this approach it won’t take long for people in your organization to learn that the way to win is by embracing an evidence-based approach. Team members will either adopt the new direction or self-select themselves out of your organization. Over time this will increase the momentum of the culture change, and gradually you will find that your organization attracts talent that values a Culture of Evidence.

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Tips for Executives – How to Get the Data You Need

One of the most common complaints that we hear from leaders and executives is that they have “too much data” and “not enough information”. Some examples of what they mean by “too much data” include:

  • Reports that consist of pages and pages of numbers
  • Tables of figures with no overall summary number
  • Charts that are cluttered and confusing
  • Analyses that show a lot of numbers but no “so what” message

It doesn’t have to be that way. Here are a few tips that executives can use to get the data they need:

Tip 1: Ask yourself “What information would help me be more effective?”
It may sound selfish, but you should ask yourself “What information would help me be more effective in my job?” This might be information that helps you save your own time, make better decisions, or seize big opportunities.

The Data Thinker

Another way to approach this question is to review the data that you already have available and ask yourself “What isn’t this telling me?” or “Why is this not useful to me?”

Based on this thought process, prepare a simple table with two columns. In the first column include a description of what you want, and in the second column identify why you want it. Then choose your top 3 to 5 items on the list. Now you’re ready to start the next step – following up with your Data Team and/or your Business Intelligence people to have a first conversation about your top-ranked items.

Tip 2: When people say data isn’t available, use the “5 Whys”
Many data people have difficultly seeing the world beyond the standard data that they use every day. So, when you meet with them and tell them about the data that you need, chances are that they will reply by saying “that just isn’t available”.

When it comes to data – almost anything is available – it’s just a matter of how much you’re willing to fight to get what you need.

The “5 Whys” is a simple process of getting to the root of an issue. When your data people tell you that getting the data you need is impossible, ask “why”. They will give you a list of reasons such as “it’s not in the data warehouse”, or “we don’t measure that”, or “the system doesn’t allow that type of reporting”. Pick any of the reasons, and then ask “why” again, which will generate a new list of reasons. Continue this until you’ve reached the root of the issue (hopefully in 5 or less “whys”). The root issue is often one or more of the following:

  • Nobody thought to ask for this before
  • At some point in the past, somebody decided that it was too hard to collect the data
  • The people running the analysis and reporting are limiting themselves based on the capabilities of their reporting tools
  • Nobody has thought of taking a prospective data collection approach, and/or nobody has thought of doing a sampling approach (to reduce data collection costs)

Through a few meetings, you now should have the real reasons why you don’t currently have the information you need. You may even have a sense of how much it would cost.

Tip 3: Estimate the cost of not having the information you need
The last step is where you can make your convincing argument. For each of your top-ranked ideas, you can think about what it’s costing you to not have access to that information.

Does it translate to productivity? Lost time? Missed opportunities? Lost revenue? Customer loyalty? Employee turn-over? If so, then you can translate these consequences into real tangible costs. This isn’t an exercise of doing high-precision activity based costing – instead this is just getting the cost estimates roughly right.

These figures give you an idea of how much your organization could potentially invest into better data and reporting. If you’re business-minded and you could work out the actual investment amounts that would still generate a positive return on investment.

Armed with this analysis, now you’re in a position to convince others what this information is worth. Which brings us to our last step.

Tip 4: Gain the support of the leadership team
Chances are that the information that will help you be more effective in your role, will also be useful to others in the leadership team and throughout your organization. If you can gain the support of the rest of the leadership team then you can increase the chances of getting what you want.

Each team dynamic is different, but a one-on-one approach often works well. These can be quick conversations with each leader with a real focus on “what’s in it for them”. You may be surprised with how many of your peers are equally frustrated by the lack of good information.

With the support of the team, the cost of not having the information and some return on investment estimates, you’ll be able to drive to get the information you need to be successful.

These are just a few tips, but I’m sure there are many of leaders out there who have many more great ideas and experiences. If you have suggestions, or alternate points of view, please weigh in.

 

Note: What is a Data Team?
When we refer to “Data Teams” it’s a catch all for groups of technical, statistical, and subject-matter domain experts that are involved in providing information to support their organization. These teams are sometimes called “Business Intelligence”, “Decision Support”, or “Information Management”, but they can also be internal consultants such as “Operations Analysts”, “Strategic Information” or “Research”. Many of these concepts equally apply to teams of Data Scientists.


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Applying “Purposeful Abandonment” to Big Data

I’ve recently been reading “Inside Drucker’s Brain” by Jeffrey Krames. I’ve read some of Drucker’s hits, but I found this book put his great ideas all together in an easy to digest format.

One of the Drucker concepts that resonated with me is the concept of “purposeful abandonment”. He argues that it’s easy to take on more responsibility, do more products, support more customers, but the hard part is the “letting go” part. By taking a concerted and proactive approach to identifying “what you won’t do anymore” one creates the space needed to move forward in the areas that matter.

The concept is surprising relevant when applied to Data Science. Here’s my take on it:

1) Do you really need all those data fields and metrics?
The thrill of Big Data is having no limits on the number of fields that we have in our datasets. With space being so cheap, and an abundance of distributed computing power, there’s no need to scrutinize the fields that we’re tracking. But, isn’t this just a form of Parkinson’s law in action (i.e. Data expands to fill the space available for storage)? With every data field and metric comes the need to do quality assurance, test for face-validity, and understand the underlying quirks. Letting go of those “nice to have” data fields and metrics allows Data Scientists to better focus on the ones that really matter. Less time checking redundant fields and metrics equals more time for insightful and impactful analyses.

Saying No

2) Do you really need all those records?
Just like the previous concept, what’s the big deal? Why not analyze all the data records in our data sets, all the time? There are certainly times when we really need the full dataset, but often this stage can wait until the first exploratory analyses have been done. Sadly, some analysts can get stuck in a mindset of always running analyses on the full dataset. And so, they spend lots of time and effort on using Big Data tools, when they could have used good old fashion statistical samples to just cut to the chase. Less time running all analyses on all of the data records can equal more time nimbly running exploratory analysis to find the hidden gems you’re looking for.
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How to Get Started With Simulation

Many business analysts decide that they want to start using simulation not just because it’s flashy and high-brow, but also out of pure necessity. These business analysts have taken their spreadsheets as far as they can and are at a point where the spreadsheets are becoming unwieldy and ineffective at providing reliable answers to their important business questions.

1 2 3 4

These analysts often ask “How do I get started with simulation?” Is there a course that one can take? Is there a tutorial? Is there a book? Ultimately what’s the best way to get started? Here are 4 questions that I suggest they consider:

Question 1: Are you sure Simulation is for you?

I have a belief that most people can learn most things if they are motivated enough, and I believe the same is true with simulation. However, there are some skills that make the learning curve easier:

  • Are you logical and process oriented? The guts that drive simulation models are driven by process logic. If you’re able to look at a real-life business process and convert it into a meaningful and clear process flow map then this is a good thing.
  • Have you done any programming? There is a lot of “If … then” logic in simulation models, and having experience with programming (including VBA and complex spreadsheet logic) will only work in your favor. Simulation models are almost never programmed correctly the first time, so debugging skills are also very important.
  • Are you good at handling a lot of data? There is a lot of data handling to estimate inputs for simulation models, and most simulation model will generate a mass of data. This is a very important skill in being an effective simulation modeler.
  • Are you good at experimentation? Simulation is like a sand box, and experimenting with your model is a key part of developing, calibrating, and validating your models, as well as designing and carrying out scenario analysis.
  • Can you work without perfect information? It’s a routine experience that simulation models will need parameters and factors that have no available data. The simulation modeler often needs to form credible assumptions as a workaround to having to deal with incomplete information.

If you can answer “yes” to the above questions then simulation might be a good tool for you.

Question 2: Are you just dabbling or are you ready for a deep dive?

Simulation is often described as both an art and a science. Simulation is one of those skills that seems to be better developed through “doing” rather than reading books or taking courses. I’d highly recommend taking courses if you’re convinced that simulation is for you (I taught a simulation course for 5 years at the
University of British Columbia). However, what you learn from a course won’t really stick unless you are going to be able to work on a real simulation project shortly afterwards.

Simulation is one of those skills where it’s difficult to be effective until you’ve been working with it for a while (i.e. your second simulation project will be much better and easier than your first,… your third simulation project will be even better, and so on). If this is something that you’re just looking to add to your resume then I wouldn’t bother. People who hire talent for their simulation skills can easily differentiate between a dabbler versus an experienced practitioner.

A “deep dive” simulation project allows a new simulation modeler to really understand what they can and can’t do with a simulation model, the effort involved with various model elements, and the associated value that those elements add to the final conclusions. New simulation modelers sometimes learn through their first intense simulation project that simulation isn’t really for them.

Coloring numbers

Question 3: Do you have a “Simulation Worthy” problem?

Simulation is an invaluable tool if it’s applied to an important problem that cannot be solved using traditional tools. But, if you could effectively answer the same problem using a spreadsheet, then why wouldn’t you just use a spreadsheet? If the business problem isn’t important enough to justify spending days (sometimes weeks) of effort programming and validating your model, then you could be creating a situation where your organization perceives simulation modeling as high effort for low value.

Ideally, you would be in a situation where there is a business problem that has high value (i.e. the potential to support a million-dollar decision, or a strong potential to reduce risk, or increase efficiency). And, ideally, the problem involves complex inter-relationships between resources, and/or processes – the type of logic that is very hard or impossible to set up in a spreadsheet. And finally, the situation requires a handling of uncertainty and variability in order to fully address the business problem. We would argue that if you don’t have a problem that is “simulation worthy” then it’s best to wait until you do.

Question 4: Do you have a good example to start from?

Simulation is not like other mathematical and theoretical disciplines, in that there is no single “right answer”. There are many different ways of modeling a system, all of which can be valid (provided that the assumptions are disclosed), and it often comes down to a balancing act of model accuracy versus model complexity. Simulation modelers often add more detail and logic into their models in an effort to improve the accuracy of the model, but as they do so, the model typically becomes more complicated, more difficult to debug, more difficult to validate, and more difficult to run scenario analysis on.

When new simulation modelers are getting started it can be difficult to make these decisions. A great way to learn is to partner up with a mentor – ideally someone who has done a few simulation projects where the results actually supported a decision outcome. The INFORMS Simulation Society is a good place to start (), and if you can do it, attend the annual Winter Simulation Conference next November.

If you can’t find a mentor, try learning from example models. Our company AnalysisWorks, made a simple simulation model of an Emergency Department that is 100% free and available for
download. Without any programming, you can interact with this 3D animated model to get a sense of the types of things you can do with a simulation model.

Simulation Model




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How to Allocate Resources as an Executive Team

Many executive teams feel that they could improve how they make decisions about resource allocation. These are decisions such as “which strategic initiatives should we approve for this year?” or “how much budget should we allocate to marketing versus customer service?” or “how many beds should be allocated to the surgical program, versus the medical program?” And this is at a time when organizations are all trying to do more with less – more sales with less sales staff, more shipments with less cost per shipping, more strategic initiatives with fewer leaders to push them forward, and so on.

The following are some of the common challenges that executive teams face when they are making decisions about allocating resources as a team:

  • Different people involved in the decision-making process have different goals and objectives. A win for one participant is a loss for another.
  • Decisions are often influenced by personality and emotion, as opposed to based on evidence.
  • Decision making processes have no feedback loop. As a result nobody keeps score on the quality of the decisions, and decision-making doesn’t improve over time.

    • Decision making

    Some teams have frameworks that they use to support decision-making, but it’s not working for them because the process, framework, and technology (i.e. spreadsheet, decision-support system) is too complicated to use, or it’s too cumbersome to maintain.

    Even worse, is when the team is attempting to use an “off the shelf” solution that doesn’t do a good job of capturing what’s important to them as a team.

    At AnalysisWorks we’ve successfully developed and implemented solutions that help teams make resource allocation decisions. These solutions have been developed over years, and we’ve learned a lot of painful lessons along the way. Here are 5 tips for success for allocating resources as an executive team:

    Tip 1: See resource allocation as a decision-making process …

    … as opposed to a one-time event. For example, it may very well be that you only decide which IT projects will be approved once a year, however, a year goes by quickly, and you’ll be right back at the decision making point soon. See the design of an effective process as an investment for your future, and a means to make the most out of your scarce resources.

    Tip 2: Define the common goals that your allocation should be based upon.

    This should be something that the entire team can get behind. The financial side is often over-represented in these types of decisions, so it’s important to round out the goals to include non-financial aspects as well. Ideally you should see a connection here to your mission statement, organizational values, this year’s strategies, and your overall strategic plan.

    Tip 3: Decide on the rules of the game.

    Again, the entire executive team should agree on the rules of the game at the very beginning. The rules should be fair and transparent. The executive team should avoid reverse-engineering the process to justify one-time decisions, and instead the process should be based on agreed-upon principles. Ultimately, if the rules of the game are set up right, they will serve to communicate to the entire team what behaviours will be rewarded. It’s at this stage where the team will need to agree on what objective inputs will be input into the decision making process.

    Tip 4: Have an objective party “keep score”.

    Building on the previous tip, it’s important that the rules of the game have accurate measurement, and that the score keeping is fair. This is a situation where an objective group or individual should be at the center of the process making sure that inputs to the process are accurate and consistent. Even more important, this person or group will have the difficult job of overseeing that the outcomes of the resource allocation are measured. Specifically, they will be instrumental in closing the loop with respect to the question “Did we get the outcomes we were expecting from our resource allocation decisions?”

    Tip 5: Improve now, keep it simple, and learn as you go.

    Sometimes executive teams try to make the “perfect” decision-making process before they are willing to use it. At the end of the day, making a minor improvement over your current state is still an improvement in the right direction. For example, if your executive team makes resource allocation decisions based on purely financial information supplemented with qualitative information, then an improvement may be to quantify a non-financial consideration (i.e. Scoring “alignment with our three year strategy” on a High, Medium, Low scale is better than nothing). These processes can grow out of control, so it’s important to keep it as simple as you can get away with. And finally, chances are that along the way the executive team will identify how the resource allocation process can be improved next time. These improvements can and should be incorporated into the next round of decision-making to make the best, simplest process possible. You will know that it’s working if your executive team feels comfortable with the process, and is able to support the resource allocation decisions that are made.

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What Every Executive Should Know About Simulation

Simulation modeling is an emerging management tool to support big decisions involving complex operations.  The technology has been around for decades and in the last while it’s become increasingly easy to apply to almost any operation, such as patient flow in an Emergency Department, bits of data through a telecommunications network, or a global supply chain.

Just to be clear, the kinds of simulations we’re talking about here are of operations and/or system flows, not flight simulations or video games. 

Patient Flow Simulation

Simulation is not for every organization, but it can be a valuable tool to have in your arsenal.  Unfortunately, though, most executives aren’t even aware that it exists.  The following tips meant to introduce the topic of simulation are based on 20 years collective experience using simulation in both consulting and academic settings.

Tip 1: Simulation can be a powerful tool to look before you leap

Having a simulation of your operations can be a valuable asset for providing insight into the potential impact of crucial decisions.  They can provide powerful supporting information to aid decision-making and investigating the associated costs and benefits of multiple decision options.

Simulation models can be very useful for big decisions: Situations involving the buying, selling, or reconfiguring or key system resources are ideal for simulation analysis.  They can allow organizations to analyze multiple potential scenarios and provide insight into nearly any situation involving uncertainty.

Big risk/reward industries such as finance, oil and gas, aerospace have used it for years, but now simulation has become very accessible.  Think of a simulation model as the next step up from your most complex spreadsheet.

Tip 2: Don’t use simulation if you’re not ready

Simulation can be expensive between the costs of staff time and software licensing so it is important assess whether or not your organization has the pieces in place to successfully develop a compelling model.  It may be premature to jump into a building a simulation if you don’t have a good profile of your activity, work flows, and financials.

Typically, organizations that use simulation effectively have already answered as many questions as they can with spreadsheet analysis.  It’s better to use simulation to address business questions that can’t be addressed effectively with spreadsheets (i.e. situations involving complex logic, multiple flows of activity, uncertainty),  rather than attempting to use simulation on a problem that doesn’t need it.Simulation Logic

Tip 3: It’s not what software you use that’s important

Many tools are available on the market ranging from simple spreadsheet model to complex custom software, but more important than the tool you are using, is the team running the tool.

You need good talent to make a good simulation: There is a big difference between a good programmer and an effective simulation analyst.  An effective simulation analyst understands:

  • How to keep the model manageable, flexible and scalable
  • The importance of validating the model so you know the results can be trusted
  • How to come up with good ideas for different scenarios

It is an important first step to decide if your organization is interested in getting into simulation or not.  If you’re unsure, you could try working with a university or a consulting firm to try it out.  If you are committed to getting into simulation, a critical first step should be to focus on recruiting and developing appropriate talent.  It takes time to get really good so don’t train someone if they won’t have an opportunity to use it intensely at least a few times a year.

 Tip 4: Think of it as a “sand box” rather than an optimizer

It is important to set expectations right from the start.  Simulation is not a crystal ball that shows you the solution to all your future problems.  It will not tell you what to do in a given situation.

It is, however, a tool for creatively testing different potential ways of running you system.  It will tell you that if you run your system in a particular way, then this is what you may expect as a result.

The ability to generate and interpret meaningful operational scenarios is why having an effective simulation analyst can be the make or break of a successful simulation modeling project.Aerospace manufacturing simulation

Tip 5: You should consider using simulation if …

So how can you tell if simulation is the right tool for you?  The following are some guidelines to let you know if your situation could benefit from using simulation modeling:

  • You have a big decision to make with high potential for risk or reward.
  • You cannot afford to make mistakes and it’s worth investing the time and effort to make sure new processes work as good as they can before being implemented.
  • You have a good understanding of your operations and system data.
  • You are able to do your first project with an analyst or team that has a track record of successfully using simulation
  • You are innovative and ready to utilize a new management tool.
  • You are committed to use the findings and recommendations, even if they tell you what you don’t want to hear.  After all, there is no point in wasting your investment.

 

Posted on in Driving Action with Analytics

Escaping Key Performance Indicator Hell

Buchenwald-100625-14486-Schwerte-hell
Image via Wikipedia

Key Performance Indicators (KPIs) are all the rage these days.  Many leaders of industry have instant access to their KPIs, but still in their gut they know that there’s much missing from the dashboard.  

The famous Peter Drucker quote “What gets measured, gets managed” rings true here too.  A bad set of KPIs can result in a lot of unproductive busy work, or as I like to call it Key Performance Indicator Hell. 

Hopefully that’s not your situation, but if it is, here are 5 tips for to success that can help you drive performance through KPIs.

Tip 1: Emphasize the word ‘KEY’ in Key Performance Indicators

The reporting tools that have made it easier to present all your KPIs in a million different ways, created a flurry of new problems:

  • Too many KPIs:  By the time you’re reporting on more than 10 KPIs, chances are that some will look good and some will look bad, just due to normal variation.  What does it mean to be doing great in 5 KPIs, ok in 3 KPIs, and terrible in 2 KPIs? 
  • Too much overlap in KPIs:  Often dashboard reports show signs of major scope creep as the report writer attempts to please all viewers.  When dashboard reports contain 2 or more KPIs that essentially represent the same underlying concept (i.e. total widget units shipped, total boxes of widgets shipped, total widgets weight shipped, etc) it makes it distracting for viewers to know what KPIs they are supposed to focus on.
  • Too many options:  Just because it’s easy to report KPIs in a variety of ways, it doesn’t mean that it’s the right thing to do.  (more…)