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Scenario planning enables organizations to prepare for different outcomes.
It's essentially the process of asking what will happen if a certain decision is made or a given event takes place, and then using data to determine the outcome.
For example, at its most simplistic, scenario planning might be a question about what will happen to profits if items continue to be priced at the same level versus raising or lowering prices. On a more complex level, it could be a question about how to handle the supply chain disruptions that have been caused by world events like the COVID-19 pandemic and the war in Ukraine.
It is essentially math -- the practice of using data to run models to reveal insights that lead to data-informed decision-making. And it would seem integral to the approach of analytics vendors whose core mission is to enable organizations to reach decisions based on data analysis.
Yet few analytics vendors offer scenario planning capabilities, according to David Menninger, analyst at Ventana Research.
Menninger first started seeing scenario planning technology more than two decades ago, but those tools were mostly offered by vendors like Anaplan that specialize in planning.
In the years since, some data and analytics vendors, including Oracle and IBM, have added scenario planning to their platforms -- largely by acquiring planning specialists. But most BI vendors have chosen to focus on adding other capabilities as they've branched out beyond data visualizations in recent years.
In a recent interview, Menninger discussed scenario planning, including why it's important, which vendors offer the capabilities and which don't, and whether such tools will eventually become more common to BI platforms.
How do you define scenario planning?
David Menninger: It depends on how you look at it. Some vendors use the term scenario planning [for their software], but I look at it a little more generically than that. Scenario planning is not just a vendor feature; it's the concept of evaluating different scenarios. Theoretically, there's always more than one possibility when you have to make a decision -- if there were only one possibility, there would be no decision to make. So, for some possibilities, you need to evaluate what a given decision would mean.
David MenningerAnalyst, Ventana Research
Let's take pricing as an example. If the price of something is $1 per unit versus 90 cents or $1.10 per unit, each of those scenarios has a different outcome. That's a very simplistic example. Something more complex, at the upper end of the complexity scale, might be evaluating where to build a plant. That's a once-every-few-years type of analysis. In between are a lot of day-to-day analyses that are complex enough that an organization would want to do some serious evaluation and consideration of different alternatives.
What are some examples of those day-to-day analyses where scenario planning can help an organization make a decision?
Menninger: Organizations are constantly hiring, and they need to examine how many to hire, where to hire, how long it will take the new hires to get productive and which products they are most likely to sell. There are a whole bunch of factors that go into that. Another example is a marketing promotion. Organizations are constantly planning promotions. Well, suppose an organization ran a promotion and it was really successful, and all of a sudden it had to produce 20,000 widgets. Could they deliver those? There are follow-on implications of different decisions, and that's scenario planning.
There are a variety of different ways an organization can move forward -- whether it's hiring, production, mix of materials, the things they produce -- and by creating a mathematical model, organizations can look at their business, play out different scenarios and see what scenario is most beneficial.
Scenario planning obviously is a form of data-informed decision-making, so do most analytics vendors offer scenario planning capabilities as part of their platforms?
Menninger: Not a lot of BI tools can do those things. There are a few, but most BI tools have been read-only for a long time. They've now gotten to the point where they are read-mostly and can do some little things around the edges, and push data back down to a database or data source. So I do think we're on the cusp of the BI vendors offering more two-way capabilities where they not only calculate things, but also send things back to see what the implications are of those changes.
If there are only a few BI vendors whose platforms include the capabilities, has most scenario planning to this point been the result of organizations building their own capabilities?
Menninger: There have been [vendor-built] tools, but they've been separate from BI tools. A lot of scenario planning has really been done in spreadsheets, but there's a market out there for what are generally referred to as planning tools, and there are vendors in that space. Among them is Anaplan. There's another company that was called Host Analytics and is now Planful. In 2020, InsightSoftware bought Longview [Solutions].
How long ago did you first start to see vendors with a focus on scenario planning? Is it something new?
Menninger: They go way back. IRI had a product called Express that was acquired by Oracle in 1995. There was a company called Comshare that got acquired by [the former] Geac. There was a product called Khalix [from Longview]. These were 20 years ago or more, so it's been a long time. For decades, organizations have been trying to tackle scenario planning, and certainly they would be looking at technology to do a bunch of the calculations for more complex situations. Still, our research shows that less than half of all organizations are using a planning tool today.
As we've discussed in the past, the COVID-19 pandemic has increased the adoption of analytics in general, but within that, has it sped up the adoption of planning tools to deal with such events as supply chain disruptions and rapid economic changes?
Menninger: I would have to believe that's true, but I don't have an empirical way to prove that. The scenarios have become more complex, so how could an organization consider different alternatives without doing something more sophisticated than a back-of-the-envelope type of analysis?
You mentioned that Oracle made an acquisition to add scenario planning capabilities -- which other data and analytics vendors offer planning tools?
Menninger: Years ago, IBM acquired a technology called TM1, which is now part of what IBM calls planning analytics. Board International is another. It's probably more focused on planning than BI, but it does both. Microsoft has dabbled in this space. It developed the MDX language, and SQL Server has the ability to process these models, but Microsoft has done less in the tooling around scenario planning than others. There's a company called PowerOn BI that has built on top of Microsoft, but that's a product built on the Microsoft stack rather than a Microsoft product. And SAP Analytics Cloud has planning capabilities built in -- SAP acquired a company called OutlookSoft in 2007, and that has been embedded and reengineered into SAP Analytics Cloud.
Among the more well-known data and analytics vendors, you didn't mention any of the independent vendors like Qlik or MicroStrategy. Is scenario planning a capability that, at least for now, is only in the realm of BI platforms backed by big corporations like Oracle and IBM?
Menninger: It's really the platform players that have added scenario planning, except for Board, which is the outlier. I have mentioned to many of the vendors that are our clients that they should be doing more in the planning space. They're not yet, but it is starting to creep in.
For example, Tableau has made Tableau Prep two-way now, so it can read information to prepare it for analysis and it can also write information back. Also, Tableau implemented something that enables customers to take action from their dashboard and make things happen elsewhere. It's not exactly scenario planning, but at least if you're using Tableau and you want to cause something to happen, you can.
Qlik acquired Blendr, and Blendr has the two-way ability to have workflows that cause things to happen back in the source systems. And if you look at Domo, some of its connectors are now two-way. All of these things are useful to try and help with the planning process. They're a bit tangential to what we're talking about -- they're not a mathematically driven model -- but they at least let you do some analysis and push things back to other systems.
Despite what is seemingly a lack of urgency to add more planning capabilities, do you think scenario planning will eventually become a common capability within data and analytics platforms?
Menninger: I'm going to say yes, but I felt the same way 20 years ago and it hasn't happened yet, so I may be wrong.
Among those vendors who have the investment, we're just on the cusp of it being tightly and nicely integrated with BI. It will be interesting to see what some of the other vendors do. If some of the big BI vendors come into this space, they might have to do it by acquisition, and if they don't make those acquisitions soon, they might be at a significant disadvantage because some vendors really have made good strides integrating these capabilities. If I had a crystal ball and could nudge vendors along, I would be suggesting that it's time to pay more attention to this space.
If acquisitions are the quickest and perhaps easiest way to add scenario planning capabilities, are independent vendors at a disadvantage compared with BI platforms backed by tech giants?
Menninger: The issue is their engines [rather than cost]. The engine needs some fundamentally different capabilities than it has as a read-only engine. It needs a language to express the mathematical model, and it needs an engine that can do the calculations and do them quickly -- and those capabilities aren't available in most of the analytics tools. Some fundamentally different things have to happen in the platform in order for them to be able to participate in scenario planning.
If enough customers ask for it, they would do it.
Editor's note: This Q&A has been edited for clarity and conciseness.