www.diversity.net.nz

Recently, I moderated a CloudU roundtable that continued an ongoing theme of mine –overcoming the hurdles to greater cloud adoption. In this case we looked deeply at the cloud cost area. This is a really important problem space to resolve.

You see, depending on your perspective, the fact that cloud computing means that technology is democratized and available to all is either the best thing ever, or the worst thing ever. For business units it’s great – it gives them the ability to acquire technology without going through the often long and torturous process with IT. For IT and CFOs, however, technology democratization is painful – it means they lose control and visibility over what people are using and what costs are being incurred by the company. That can result in some big surprises at the end of the month, quarter or financial year.

It was awesome then to talk with Tyler Sloat, CEO of subscription and billing vendor Zuora, and Mat Ellis, CEO of cloud spend management company Cloudability (disclosure, I’m an investor in Cloudability) to get their perspectives on this cloud cost conundrum.

We started off by setting a little bit of context: I detailed exactly why I believe the cloud is a revolution rather than an evolutionary step for technology, and why the democratization that cloud produces is both a positive and a problematic thing for organizations. We talked about the balance that organizations strive to find between control (for IT, the CFO and the C-suite generally) and agility.

Some questions we talked about included:

• Why is cloud cost so complex?
• What is the CFO perspective on how you think about this problem?

Finally, we talked about specific ideas for solving the problem – Mat Ellis set out a four-step cycle of continuous improvement when it comes to managing cloud cost issues:

1. Tell finance to categorize cloud expenditure in a special place to keep an eye on it.
2. Obtain a cloud cost management solution to avoid any surprises.
3. Review costs. Ask questions (Can we do more with less?). Optimize.
4. Hold people accountable for their spending.

It was an interesting discussion that revolved around an important, but often ignored, issue. You can check out the replay below.

Even before some state polls had closed media outlets begun tallying the results of the U.S Presidential elections.  And with almost 120 million votes cast across the U.S it was President Obama that came through with the overall majority to emerge victorious. But it was the lead up to voting day and in particular the Democrats unprecedented utilization of analytics that many are saying set the stage for the win over their Republican counterparts.

Big Data, Big Success

The importance of analytics in enterprises is becoming more adoptive as the growth of analytic-driven organisations accelerates. And it appears political campaigners too understand the critical role analytics plays in success.  For the 2012 election the Democrat party hired an analytics department five times larger than that of the 2008 operation. The team consisted of data crunchers that conducted data-mining experiments in what the campaign believed was the biggest advantage of the Romney campaign.

Despite a landslide victory in 2008, one of the weaknesses of the campaign was the growing number of silo databases, meaning get-out-and-vote lists differed from the fundraising lists: the two teams never shared data. Facing an ever-expanding mass of data and a fierce battle for the Whitehouse, the campaign spent 18 months creating a single massive system that could merge all information, including social media, polling, and fundraising.

So what did this achieve? It meant the Obama campaign could target voters more precisely, drill down to demographic groups with greater accuracy, raise far more money than four years earlier, and spend more efficiently when it came to buying ads. Essentially, harnessing big data and analytics allowed the Democrats to turn information into insight to drive smarter decision-making as opposed to making decisions based primarily on intuition.

Data and analytics played a critical role in the re-election of President Barack Obama, echoing the growing importance of analytics in business.

Forecasting the Future with Predictive Analytics

But the use of data and analytics went beyond the campaigners. Throughout the campaign, surveys, polls and computer models were closely watched for predications. And while most polls had the race tightly balanced, New York Times blogger Nate Silver was predicting a landslide victory for Barack Obama. Silver’s statistical model aggregated and adjusted state polling data to predict the probability of victory. This methodology allowed Silver to accurately predict 49 of 50 states in the 2008 election, subsequently propelling him into the media spotlight. So how’d he perform this year? Silver’s model successfully predicted all 50 states!

Silver’s use of predictive analytics correctly simulated potential outcomes before they happened. In business, this might be how much to charge for additional widgets, test marketing a new product roll-out, or various what-if budgeting and forecasting scenarios. Analytic-driven organisations with pervasive business intelligence strategies are positioned to gain considerable advantages over competitors in business and beyond. And cloud-based platforms like GoodData, with business mash-ups of reports, analytics, and metrics, allow users to manage by the metrics at a fraction of the cost of traditional on-premise solutions.

On-premise solutions are expensive, requiring costly consultants and heavy IT involvement with huge maintenance and support bills. The solutions are rigid resulting in weeks and months to make simple changes, with long IT queues, out of synch data, and constant rework.  Users are constantly frustrated with disjointed, manual, and static tools that require downtime for updates and upgrades.

GoodData is the Enterprise Business Intelligence (BI) solution that the business world has been waiting for. Business users no longer want disconnected, static, consultant dependent software that IBM has cobbled together over the last 20 plus years.  Rather, they want self-service applications across a flexible and infinitely scalable platform.  

On-premise enterprises, like the IBM Cognos studios, struggle to accurately execute on their strategy. The ability to respond in the moment to constantly changing conditions is mandatory, yet continues to elude the majority of organisations.

GoodData simplifies the BI model by giving business users a single interface that is consistent and easy to use, driving collaboration and adoption across the enterprise.  Business communities that typically depended on the consultant army to build solutions are now enabled, engaged and more productive. GoodData’s collaborative tools will drive real change in the way that you do business. Collaborate and share projects, reports and results with colleagues and management in real-time by annotations, tag reports and inviting people into your projects to discuss and share progress. 

Traditional software vendors like IBM handcuff organizations to the costly hardware, services, and licensing. With GoodData don’t worry about maintaining and upgrading servers; they will handle it for you. Built as a complete, integrated platform and offered as a service, GoodData can deliver your first project in weeks and extend it easily—with more data, more sources, more analytics, more dashboards, more users.

GoodData apps automatically connect with common data sources like Google Analytics, Salesforce and Zendesk, and since they are all built on the GoodData platform, you can extend them easily by adding data or customizing metrics that reflect your unique business requirements.

Unlike Cognos, every customer gets every feature when it's released, without painful forced migrations. Since GoodData is built as an integrated platform, it removes the burden of cobbling together separate data warehouses, analytics engines, modeling and visualization tools.

In Summary, Cognos and other traditional BI solutions are static and disjointed; they don’t evolve at the speed of business. GoodData makes BI an on-demand service which you can adopt and evolve quickly without the usual broken promises experienced with on-premise traditional BI vendors.

Adding to IT’s stress are legacy applications that continue to burn an increasing amount of IT’s budget. Constrained organisations cannot afford failed front office projects that strangle IT productivity and credibility.

When considering a corporate performance solution, a company may first look to large enterprise vendors, like IBM, for planning, forecasting, and analytic applications. These enterprise vendors offer a stack of products or suites including IBM Cognos Express and TM1, but each brings integration complexities, long time to value, and require a large investment into infrastructure. These on-premise solutions are expensive, requiring costly consultants and heavy IT involvement, with huge maintenance and support bills.  

Anaplan

Anaplan connects all of the company’s people, data, and front line business activities together in one platform, available to all business users through a single portal.  The platform brings a company’s functional users together using a common interface, which links the user community across planning processes.

The revolutionary Anaplan platform enables the business analysts manning the front lines of the enterprise, to design, build, deploy, and maintain the business applications.  The results to the business are performance improvements and top line productivity gains without putting more demands on their stressed and undermanned IT organisations.

The Anaplan platform converges business consumers, but also brings application developers together. In Anaplan the business consumers are also the developers of the solution.  Anaplan’s common development interface uses a natural, easy to use language across planning, dashboard, and forecasting solutions.

Anaplan’s cloud based architecture shifts the management of infrastructure from critical organisational IT resources to cloud computing experts at Anaplan.  The businesses can focus on building solutions that transform their core business. 

IBM Cognos TM1

IBM Cognos TM1 infrastructure requires IT consultants or specialised staff with expertise in tuning and managing a TM1 environment. The enterprise infrastructure could potentially include development, UAT, and production servers. 

The impact to the business is that IBM Cognos TM1 projects are much more complex, require many more resources, and take significantly longer to implement than a similar project in Anaplan.

In Anaplan business applications are rapidly built by Business Analysts using a natural business language without having to be concerned about the underlying infrastructure. The TM1 cube calculation rule syntax and extract transformation load (ETL) script are not a business language like Anaplan, but rather two separate application specific coding languages.

Anaplan is geared to the Business Analyst with the organisational knowledge to build and deploy business orientated applications quickly. The Anaplan user does not require enterprise IT knowledge of a proprietary syntax and scripting language. In comparison, building TM1 applications is difficult because it’s not a natural transition from a spreadsheet environment and it requires dedicated application specific skills.

The TM1 skill-set is typically an IT or consulting resource with extensive experience in TM1 and the two scripting languages for processes and cube rules. The web interfaces are then configured using separate tools and can require additional knowledge of MDX coding.

TM1 is architected using on-premise technology and requires a heavy dependency on infrastructure and IT support with limited computing resources for scalability and performance. Simple upgrades and maintenance outages will require a heavy involvement of IT resources and signifcant overheads are involved with the on-going support. TM1 is more static when it comes to making changes. Generally, change requests must be submitted through the specialised TM1 resources to coordinate the changes and impact across the product. 

IBM Cognos Express

The IBM mid market equivalent of TM1 is the IBM Cognos Express Xcelerator components. Xcelerator is essentially the same tool as TM1, except usually an earlier version release.

Cognos Express also comprises of other additional Cognos components creating a stack of products that IBM sell in separate licenses.  Organisations that deploy IBM Cognos Express soon realise that building and using products that are part of a stack adds complexity.

With each product brings both development and end user complication. Whether it’s training your end users on another interface or adding consultants, implementations will result in a longer time to value. This difficulty in developing and using business software is counter to the premise of business self-service.

Whether you invest in a just the TM1 equivalent component or your development spans multiple tools, you will find skill-sets which have a dependency on consultants and depleting your organisations capability of self-service.  In the end, your project will take more time, carry more cost, increase risk and return limited value. Your users will be potentially forced to use multiple disconnected and dissimilar interfaces, causing confusion, frustration, and limited buy-in.

Summary

The Anaplan platform is not only intuitive and easy to use, it is built from the ground up, to leverage cloud technology, in memory computing, and multi threaded processing, delivering time to value, instant access and enterprise collaboration.  It’s simple, “pay as you grow”, subscription based pricing plan is a shift from the traditional enterprise vendors whose model requires significant investment in hardware, services, and software.

Anaplan is just easier to build robust solutions without consultants, where an IBM Cognos project can create backlogs due to the availability and costs of scarce consulting resources. A solution that takes months in IBM Cognos will take weeks to build in Anaplan, and be built by business analysts not external consultants.

Anaplan is the enterprise-scale cloud platform that now enables executives to optimise front-line business performance (sales, marketing, production, services, manufacturing, IT, and finance) interactively, all in one place. As a result the impact to your business will be massive improvements in revenue, margins, and transparency.

A data warehouse is seen as the central repository that allows an organisation to capture and model all of the required data for further business insight. The level of detail depends on the various factors, including accessibility of the data, type of data structures, and analysis requirements. A data model needs to be designed with consideration to what critical business questions you are trying to answer.

When building a data warehouse even the most advanced analytical companies can find that the time to value is long and if not executed correctly it can fail on its original promises. The concept can evolve from a lofty vision but the final solution may leave business users with a reporting structure that is slow, difficult to use and with limited useful data. Although I have seen companies who have made a great investment in traditional business intelligence who are now running into some serious capability limitations.

A data warehouse is a model of the business that focuses on reporting what happened with past activity within a contained set of data, while the BI tools allow for analysis and visualisation of this data. But every minute a huge amount of data is being generated both internally and externally from on-premise systems, machines, websites and application across the Internet.  So how do we monitor what’s happening now, compare with what happened historically and predict what might happen in the future? A data warehouse will fall short in predicating the probability of an outcome and extracting patterns and correlations from large amounts of data in a timely fashion.  In BI the expectation within a business is the efficient reporting and analysis of data patterns and metrics, while aligning these with key performance measures.

Business intelligence consumers are demanding insight rather than historic data analyst outputs, this is leading to the consumerisation of BI. We are seeing a massive growth in the mobile technology market and these devises are perfect for visualisation and quick access to analytics and big data. The velocity, variety and volume of data are increasing at a massive rate and have the potential of being converted into greater business value. IDC anticipate digital content growing by 2.7 billion terabytes in 2012 alone (see December 2011,  IDC Predictions 2012).

The ability to optimise your processes in deriving value from data in a cost effective way is driving businesses to redefine how they manage their data warehouse and BI solution. You need to adopt quickly and evolve without historical broken promises and failures previously experienced. It is still important to start small, but to also aim to grow with your success and become more of data decision-driven business. The traditional data warehouse is being replaced by a modern take on how to manage your data, with on-demand BI in the cloud you can provision, model, load, operate, and optimise as you grow. Take the plumbing off your to-do list and focus on your value-add and start really dealing with your big data issues.

Get the latest Point Analytics whitepaper

Cloud Security: The Length Cloud Providers go to Protect your Data 

Don’t get me wrong – where would we be without the expediency of our reliable friend the spreadsheet. But when it comes to business critical processes like budgeting, planning, and forecasting - that rely on high levels of user participation – the risks and limitations of spreadsheets are abundantly exposed. 

Pesky Pain Points 

The budgeting and forecasting process brings with it numerous difficulties and pain points. Foremost among these issues are version control and consolidation. For most organisations the budgeting process involves rolling multiple functional area spreadsheets into a master budget.  Not only does this consolidation process encourage management and maintenance of multiple spreadsheets, but it creates different Excel workbook versions that evoke concerns over data accuracy and reliability.

And what about performance? Excel has always been a great personal workspace for quick and agile calculations, but is it scalable and robust? How do you get Excel to not be so slow and cumbersome when working with complex data sets? What happens as your business grows, your business passes through multiple iterations to compensate and the size and complexity of your data expands? The unscaleable nature of Excel can be a major limitation and risk. Excel struggles to offer much in the way of security capabilities for multiple users and with data confidentiality a limitation of spreadsheets, how do you ensure your users only have access to their correct cost centre instead of company-wide payroll? 

Needless to say these concerns create errors and inaccurate data resulting in long-winded, potentially broken and disjointed business processes, which in turn lead directly to uninformed decisions and the subsequent poor results that follow. 

Alternatives 

The natural step in solving these pain points is a move to an enterprise platform that has the capability of performing business critical processes with greater reliability and accuracy. One option is traditional on-premise products like IBM Cognos or Oracle’s Hyperion solutions. But these come at a cost – consider licenses, IT install/configuration, programming, additional hardware & software, deployment skills, not to mention exponential costs of users and ongoing maintenance. But another consideration in transitioning to a traditional enterprise solution is the technical nature of the products. Implementing Cognos or Hyperion means contracting an army of consultants to drive the system, and this moderates your ability to maintain and manage the process.   

So now what? You understand the need for a move away from spreadsheets, but your users are familiar with Excel and reluctant to change. A traditional on-premise enterprise solution can solve your problems, but the costly and technical characteristics are a deterrent.  Well, there is one alternative that may just give you the best of both worlds. Anaplan is a cloud based enterprise solution that is gaining momentum as a best of breed product. It’s the most powerful planning, forecasting, and analytics platform in the cloud, providing a single place for decision makers to share important business data in real time. 

Why Anaplan? 

The Anaplan platform has been built from the ground up and with the average spreadsheet user in mind. The use of natural language makes it easy for users to build and maintain models and the grid-like interface helps make Anaplan an easy step up from Excel. And forget about multiple spreadsheets and versions, with Anaplan different functional areas participate in the same model and instantly promote a joined up approach. No more consolidating and aggregating. Security is no concern either as users have full or selective access depending on roles, functional areas, or cost centres. 

When it comes to performance, Anaplan’s unique in-memory processing means much quicker processing of complex large data sets, which provides a significant edge over both spreadsheets and traditional on-premise solutions. And being a cloud based solution means no hardware, no software, no infrastructure, and no IT. 

Conclusion 

But before you convince yourself that a change is necessary; be sure to look within first. By this I mean ensure you fully understand your current budgeting model. The methodology applicable to your excel models should not simply be transfer to an enterprise solution, but improved upon.  Doing so assures a budgeting and forecasting process that provides a complete and continuous overview of the organisation with the insight and information needed to make business critical decisions.

Businesses must turn information into insight to optimize business performance and drive smarter business outcomes, and there are a host of spreadsheet alternatives that allow organisations to do just that. Can you afford not to make better, more informed decisions?