Barbican Case Study (Now part of Arch Insurance)

Insurance Companies use Anaplan to Automate and Improve Reporting Processes

Insurance companies often face the challenge of having to deal with lots of calculations of varying complexity across different departments. Many insurers have found that Anaplan helps them manage the challenges that comes with large, complex and business critical calculations, coupled with their need to provide internal reporting of results. Barbican Insurance Group has implemented Anaplan’s cloud-based business planning and execution platform bringing more control to their business planning and less labour-intensive reporting.

Collecting data and user inputs from many different departments can make reporting a slow and time-consuming activity. Using spreadsheets brings problems around tracking changes and having multiple people working from the same spreadsheet. If the calculations are found to be wrong, finding the error responsible can be difficult.

A number of insurance companies have found that automated simplified reporting structures accelerate the process so things can be done that wouldn’t have been possible with spreadsheets.

“The insurance sector is one of the world’s most heavily regulated industries and if a business can find a way to not only streamline the reporting process, but also make it more accurate, this represents a crucial competitive advantage. The Anaplan platform can offer such an advantage – our analysis function could be central to the growth of organizations in this sector.”

Barbican Insurance Group

Mentat Technology supported Barbican with their initial Anaplan implementation. Barbican’s objective was to use Anaplan to help with their reserving process, allowing them to calculate how much money should be held to meet all future claims. Anaplan now handles all of their reserving calculations and Barbican have expanded their use of Anaplan to include Financial Planning and Analysis.

“With Anaplan we can now aggregate up from the most granular level. This gives us greater analytical capabilities which facilitate more informed decision-making,”

said Alastair Lauder, Syndicate Actuary for Barbican Insurance.

“Our actuarial modelling process is now much quicker in terms of processing time, and as a result we are able to spend more time on the analysis itself. Reporting both externally and internally is now far easier.”

Following their successful implementation, members of the project team at Barbican have continued to recommend Mentat Technology as an implementation partner to other insurers who have wanted to start using Anaplan.

About Mentat Technology

Mentat Technology have been working with Anaplan since 2013 and are accredited as a Bronze Partner. As one of the earliest Partner Consultancies in the UK, Mentat Technology has a highly experienced and skilled team of consultants who specialise in a range of industries and use cases.

What is Anaplan?

Many visitors to this website, are existing users of Anaplan, potential new users of Anaplan, or people who are like us who make their living by offering services involving Anaplan.

So the more technical how-to guides blogs are great for them.

However, we are now looking to reach out to more potential users of Anaplan rather than get our business purely by word of mouth.

So to the uninitiated, what is Anaplan?

The Origins of Anaplan

Systems like Anaplan date back to a time where you couldn’t hold all of your data in one place, so you would aggregate it to make sense of it. That means you take your raw data and process it to make new data that takes up less space that just gives you what you need to know. In sales this might be removing the details of every transaction but keeping the total sales figure for a region or salesperson for a particular month.

Storing this data in a way that makes it easy to process and run calculations with is where Enterprise Performance Management tools come in. Another or slightly different way to look at the same thing, is that if you are measuring performance, you may be measuring it against milestones that you have set at the beginning of the year to achieve your end of year revenue goal. So you can think of it as a planning tool. You make a plan for what you hope to achieve in the coming year and then you measure performance against that plan.

Still worth working with simplified versions of the truth

As technology has advanced, you now can hold all of your transactions and work with that data, and some people may want to work with that original raw data in some circumstances.

However, working with aggregated data allows you to just work with the bits you need and play around with it and do calculations with it in a way that would be harder if you worked with the raw full data set.

Excel

A lot of people will use Excel for this planning process using aggregated data. In a lot of situations Excel is still the right tool, however there will be times that there may be better tools, particularly if you are working with a lot of spreadsheets and a lot of users are working on any one spreadsheet. There may be a process which involves a sequence of people having to do something with it, so the second has to wait for the first to have done their bit. There may be more than one cycle, so it’s getting passed around, and any delays affect everyone else in the process. From being a great flexible tool, Excel starts to look like the wrong tool for an organisation that can afford something better.

I know what kind of companies have bought Anaplan in the past, but maybe I shouldn’t say that only those companies will buy it in the future.

Traditionally these type of tools are used in finance initially, then maybe being rolled out into sales or operations. HR is a possibility too. Anaplan can do all of these, but is stepping out of the finance use cases much more than earlier types of this sort of tool.

Why is that ?

Anaplan has been developed by a team that worked with and designed earlier generation planning tools and knew that it could be done better.

I could mention the specific areas of functionality that make Anaplan different, but the end result is that you can start with a smaller project and it still be viable. You can build your models quicker. I should explain that a model is a bit of the world that you want to capture with words, calculations and logic. In the same way that for a computer game, you create a virtual world with numbers and calculations, a financial model is one that takes numbers, calculations and logic to replicate parts of a business. You may want to follow accepted accounting principles to describe the transactions of your company, or you may want to devise your own measures and calculations to give a completely new perspective on things.

As well as modelling existing processes and planning, you may want to use Anaplan to do completely new things using it’s powerful calculation engine, and ability to work with numbers that have an underlying order but are on a scale that could be unmanageable in more basic tools.

Get in touch

Anyone who wants to know more is welcome to get in touch with me. Particularly people who are getting frustrated with Excel or their existing legacy software. Anaplan can also be used to custom build something to replace business software that is already in place but is starting to look dated and expensive. Anaplan may not be the right tool for all situations, but you are welcome to ask me and I can look into it with our experts. Often the ongoing costs for a legacy product that isn’t keeping pace with requirements can be more than ongoing costs of something built with Anaplan. The functionality developed with Anaplan can then be built on by the client in future without resorting to code (ie programming). colin.wall@mentattechnology.co.uk

Tarmac

Tarmac, a CRH company and the UK’s leading sustainable building materials group, moves millions of tons of construction materials by road, sea, and rail to thousands of customer sites every year. This complexity requires accurate sales and operations planning (S&OP) and financial plans to ensure efficiency and profitability. The company’s old process, based on spreadsheets and databases, lacked multi-user access and was hampered by its disjointed nature.

Tarmac built a Connected Planning foundation based on the Anaplan platform to streamline its S&OP and financial planning. Implemented with the aid of Anaplan Partner Mentat Technology, the new solution delivers dynamic stock management, greater visibility into material flows and inventory, and more accurate sourcing decisions. Thanks to connections across S&OP and finance, the impacts of planning decisions are visible throughout the process.

Using the Anaplan platform, Tarmac has shortened its monthly financial planning process by two weeks and eliminated hundreds of spreadsheets. The benefits have spilled over to sales forecasting, formerly a 16-day process that now takes only four days. “Our partnership with Anaplan has transformed the way we plan and forecast,” says Sam Fergus, Tarmac’s Senior Manager: Logistics Excellence. “It allows us to support our customer network across the country to ensure that they continue to have the right product in the right place at the right time.”

Tarmac chose Anaplan because the company needed a unified source of information that could span the business. The Tarmac team appreciates the fact that calculations and formulas in Anaplan are transparent, owned by the business, and easy to model.

The Anaplan platform enables Tarmac’s finance and supply chain employees to access the right data for their individual tasks while working with shared drivers, data, and goals, and establishes a solid foundation for the future. “Increasing our ability to deliver effective planning and forecasting is essential to helping us evolve our business,” Fergus says.

Anaplan Excel Add-In

Why would I need the add-in?

Anaplan is designed to display data within grid views or through graphs and charts within its own dashboards, but there will be occasions when the data will need to be loaded into a third party piece of software, like Excel.

Even without the add-in, Anaplan users can have the ability to export data from any dashboard view, however there might be occasions when you want to export multiple views out of Anaplan, and populate these data points into pre-determined cells in an Excel workbook.

How can I get the Excel add-in?

Anaplan’s Excel Add-in can be downloaded from the Anaplan Community website. If you’re logged into the Anaplan Community website, you can download v3.1 of the add-in here: https://help.anaplan.com/anapedia/Content/Extensions_and_Addins/Excel3_1_Add-in.htm

Once you have followed the installer and successfully installed the add-in, it should appear in your Excel ribbon.

What can I do with the Excel add-in?

At the time of publishing this post, the Excel add-in only supports pulling data from Anaplan, and doesn’t allow write back. Nevertheless, this doesn’t limit the add-ins use to just reporting.

You may want to pull data from Anaplan into an Excel template where values can be updated, saved as a CSV file and then uploaded back into Anaplan. This might be particularly handy if you’re planning to do bulk data changes.

The add-in also allows you to pivot and filter your data before you pull it into Excel. This means that while Anaplan continues to hold your full data set in a multi-dimensional format, you can still comfortable use the data in a two dimensional worksheet.

What limitations should I be aware of?

  • The Excel Add-in creates a one-way connection between Anaplan and Excel. You can view and edit Anaplan data in Excel, but you can’t push those changes back to Anaplan to update the source module.
  • To avoid overloading and crashing Excel, there is a limit of 1 million cells which can be exported.
  • The add-in doesn’t allow you to load up any subsidiary views.

Anaplan Connect API

Anaplan Connect enables a user with Administrator credentials to automate the running of Anaplan actions, avoiding the need for Anaplan GUI’s

What is Anaplan Connect?

Anaplan Connect is an API Client with a command-line interface that supports the following types of Anaplan actions:

  • Import
  • Export
  • Delete – eg. Delete from List using Selection to remove specific items from a list.
  • Process – a combination import/export actions

Why use Anaplan Connect?

  • Anaplan actions can be run outside the normal Anaplan GUI. Actions can be scheduled to run automatically at a defined interval.
  • Limiting the need for user import Dashboards and having a more direct feed to lists and module input values
  • Quicker and cheaper to set up than other integration tools

How to use Anaplan Connect

  1. The Anaplan Connect API can be downloaded from Anapedia.
  2. Create the required actions in your model.
  3. Create your batch (.bat) files to call your commands. Each batch file needs to contain:
    1. Workspace ID. This is unique and will not change.
    2. Model ID. This is unique to each model and will not change.
    3. Set the Operation Type, which includes:
      1. Anaplan Action. A specific Import or Export
      2. Credentials: The User Name and Password, unless you are using Certificate-based Authentication

When writing your Batch file there are good example files included within the Anaplan Connect Client install and the support pdf on Anapedia to assist you.

What can Anaplan Connect do?

  • Run an Import Action to import data direct to your Model from databases such as Sequel and Oracle or from simple text .txt or .csv files.
  • Delete data, List items using Selection.
  • Export module or List content to Excel workbooks, txt or csv files

Alternatives to Anaplan Connect

In addition to Anaplan Connect, there are several data integration connectors to support integration between Anaplan and third-party applications, including:

  • Dell Boomi
  • Informatica
  • MuleSoft
  • SnapLogic
  • Tableau

Anaplan also provides integration support with SalesForce.com, allowing any SalesForce.com user access to Anaplan from within SalesForce.com.

If you’re looking for more information regarding Anaplan integration approaches, please get in touch with us.

Dynamic Cell Access in Anaplan

Last week I was given a customer requirement which allowed me to use a new Anaplan feature – Dynamic Cell Access.

My remit was to limit a user to be able to map/configure only a single option from the specific list’s items and disable the other options.

For example, if the user needed to set a ‘Proficiency level’ for a particular job role, the functionality had to disable the other options once one option had been selected or leave all options open, writeable.

The Proficiency Level for an Area Manager for a particular role had to be set as one of the following, Expert, Practitioner or Foundation level and once one had been set to TRUE the other options/list items should be read only.

What is Dynamic Cell Access?

Dynamic Cell Access (DCA) is a powerful tool in an Anaplan Architects toolbox giving them the ability to set Read, Write or no access, to a cell, an entire row or column.

When I investigated further, I looked at the Anaplan’s tutorial app and was impressed by the variety of uses and how helpful it could be.

With DCA, a model builder can provide the ability to control a users’ read or write access from a dashboard, rather than the old and more conventional way of a Workspace Admin setting this access via the settings tab.

For example, if your model had a list of Regions but only certain users should see or have write access to particular data for specific Regions items.

By creating a module dimensioned by users and a particular list – in this case our Regions list – and using Boolean line items, we can build a dashboard that displays a nice user-friendly way of setting these permissions to Read or Write or not showing the cell values at all.

I was also very impressed after looking at the Learning App on the various uses from straightforward to the more complicated solutions, on how DCA can add value to a model’s design.

Some Examples…

Summaries and Subtotals

You can use DCA to apply different security at different levels of a hierarchy. Very powerful if you want to suppress total levels for certain users. For example, in a line which calculates employee salaries, you could use DCA to control a users’ ability to see individual salaries, and then also use DCA to hide the summary totals from them (as this might allows them to calculate the missing values!)

Controlling Workflow and User Experience

When Actual data for a year is mixed with Forecasting data, in the months where Actuals existed a planning adjustment line item could be made read only or invisible so nothing could be entered into these cells, eliminating the need for validations.

Another good use of DCA could be where we want to create a workflow. For example, approval might be required before the next steps of data entry can begin. Lines Items can be set to read only until approval had been granted.

The uses in fact are endless and I for one will be incorporating more Dynamic Cell Access into my future Models

Using Anaplan for Supply Chain Planning

We hear from many prospective customers about the challenges they face with accurately and efficiently conducting their supply chain planning. One area where we’ve gained a lot of experience is helping customers enhance their S&OP processes. Historically, these businesses would have relied on Microsoft Excel and Access solutions to complete their planning, but the reality of using these tools is often far from ideal. The sort of challenges they face are as follows:

• Capturing inputs from multiple users across the business is tricky. Spreadsheets end up being emailed around the organisation and then linked back together in a confusing web of linked spreadsheets.
• The level of granularity that can be achieved through a spreadsheet may not be enough for the business to plan accurately.
• Building in the ability to calculate a statistical forecast or seasonality can be tricky in Excel.
• Sharing the results of a forecast across the business can be slow, especially when different versions of the truth emerge. It can then be very time consuming to produce reporting packs which may end up needing to be redone if the plan gets updated.

Mentat Technology has worked with several customers to deliver S&OP solutions in Anaplan. We’ve helped these customers remove the limitations presented by their old solutions and realise the benefits of implementing a cloud-based, integrated model. In turn, these companies have gone on to roll-out Anaplan across other parts of their organisation such as Finance, thereby leveraging the benefits of connected planning.
Our customers have reported significant reductions in the time it takes to produce forecasts, and that has allowed them to increase their forecasting frequency. Some customers have chosen to implement statistical forecasts that greatly improve the accuracy of their sales forecast, to the point where the accuracies of these statistical forecasts beat those of their own sales team!

Read more about how Mentat Technology have helped Tarmac use Anaplan for their supply chain planning.
If you would like to learn more about how Mentat Technology can help with supply chain planning, please contact us.
Read more about Supply Chain planning in Anaplan 

Anaplan Best Practices – Large Data Volumes

How can we use Anaplan to reduce cell sparsity from 360 million, to only 5 million cells?

It is a very common scenario where our clients need to be able to load transaction level data into Anaplan. In most cases this is due to bottom-up calculations, external system restrictions or low-level allocations/mappings. Large volumes of data significantly impact Anaplan model size and can even affect the performance, therefore we would like to share a couple of design techniques that will make the model efficient.

Staging lists

The requirement to import transaction level data doesn’t mean such high level of details has to be permanently stored within the model. In the vast majority of cases the main driver for high volume data loads are low level allocations and mappings between multiple data sources, but after the initial processing the details are no longer required. In such a scenario, using a staging list approach is the best design solution.

Staging lists process:

1. The data is initially loaded (via user action or automated process) into the model
2. System validates the data and runs low level calculations
3. User reviews results and validations (optional backup export can be enabled at this stage as well)
4. User submits the results by running a process (dashboard button)
5. The system aggregates the data using predefined unique key to a level that provides all required attributes and assures optimal size and performance efficiency
6. Source data loaded in p1 is being removed from the model

The design provides high quality bottom-up results and eliminates ineffective workspace utilisation and performance loses.

Multi-level Numbered lists

Multi-dimensional data cubes are the default way in Anaplan to deliver required results, but in some cases these prove to be inefficient or even not possible – this is when numbered list hierarchies prove to be the best solution.
To illustrate the efficiency of the technique we will use an example of a Claims triangle report for the purpose of Solvency II reporting.
In order to build the report, we typically need the following details: Reserving Class, Policy, Risk Code, Year of Account, Development Period. The example volumes are as follows:
– Reserving Cl = 30 items
– Policies = 20,000
– Risk Codes = 80
– YoA = 15
– Dev Period = 15
If all the attribute lists were added to a module it would result in following size for each measure (Res Cl is removed from calculation as it’s a direct parent of policy):
20,000 x 80 x 15 x 15 = 360,000,000
Even this simplified and fairly low volume example results in significant report size.

The key for efficient design is to understand the data – in this example, it is logical that not all the policies will have values for every YoA or development period, let’s assume an average of 7 years/periods per policy, on top of that a single policy usually does not have more than 5 unique risk codes. Following numbered list hierarchy would be created:
– L1 Reserving Class
– L2 Policies
– L3 Risk Codes (unique combination of RCs applicable for each policy)
– L4 YoA (unique combination of valid Policy, RC and YoA)
– L5 Dev Period (unique combination of valid Policy, RC, YoA and Dev Periods)
The total size of a single measure using above mentioned assumptions would be:
30 (Res Cl) + 20,000 * 5 * 7 * 7 = 4,900,030
As we can see the numbered list approach is significantly more efficient and the results can easily be exported in a pivot-friendly format or sent to other external systems.

These two techniques prove to be very powerful when processing large volumes of data and can either be used individually or in conjunction to provide the best solution for our client.

Anaplan Partner Hub

This week we attended Anaplan’s first full day Partner Hub in London. It was a chance to learn more about the platform changes being planned for release in the short, near and long-term and to also hear about their vision for how they see the product evolving over the coming years.

There was too much covered during the day to share everything, but some of the highlights for us were the demonstrations we saw of the new workflow functionality and Excel add-in. Anaplan have clearly invested a lot of time and resources in redeveloping both of these – and the results are impressive.

The new Anaplan workflow, or ‘Tasks’ as we will probably come to know it, allows planning cycles to be much more task driven. Instead of accessing their planning dashboards within the models as they would have done previously, users can receive an email notification which will take them to a new Tasks portal. From here they can see all tasks assigned to themselves and complete each one in order – without leaving the portal.

The new Excel add-in currently in development has made huge improvements since the current release. One major change in the new build is that the add-in allows users to manage the data they retrieve themselves, rather than relying on a model builder to create the appropriate views within the model. As a result, users can be more selective about what data they pull in to Excel from Anaplan. We have also seen big improvements in how data can be pivoted and sliced once it is in Excel.

If you would like to understand more about upcoming changes to Anaplan, please contact us.