Leveraging Predictive Analytics for Finance: The why and how.

No one can capture and analyse data from the future. However, there is a way to predict the future using data from the past. It’s called predictive analytics, and organisations do it every day.

What is predictive analytics?

Predictive analytics can help CFO’s to use the existing data and identify trends for more accurate planning, forecasting and decision making. By using predictive analytics your organisation can predict outcomes, identify untapped opportunities, expose hidden risks, anticipate the future and act quickly.

Every company wants to see into the future. How much will a product sell next month or will the demand drop off? How much will the business have to spend on manufacturing, distribution and other overheads? Does the business have a “next best offer” for a product or an estimated revenue for a newly launched product? Predictive analytics techniques are used to help answer all these questions and to create a better understanding of possible variables to aid smarter decisions.

Gain valuable insights

One of the biggest developments in SAP’s Predictive Analysis Tool has been its integration with SAP HANA. HANA provides remarkable output possibilities by using complex and heavy algorithms run on the in-memory platform.

Big Data which is the large volume of unstructured data from data sources such as external financial reporting systems, RFID sensors, Twitter, Facebook and other social media, can now be used to its advantage by using this powerful tool to forecast future performance and drive strategic decision making.

There are several routine processes that can be improved or enhanced using predictive analytics, including:

  • Target more profitable customers: By analysing the customers it is possible to identify small customer segments which are highly profitable.
  • Cash forecasting: Cash flow management is a key aspect of business to plan its future cash requirements to avoid a liquidity crisis. Leveraging data insights, financial professionals can look at trends to identify slow payers, detect and address system issues and improve receivable management.
  • Detection of financial risks: Financial departments can leverage predictive analytics to establish baseline criteria that makes it easier to identify outliers before they can damage overall company performance.
  • Demand planning: Predictive analytics can be used to forecast the sales over a period determining the demand of the product. This will help reduce returns from the customer and scrapping of the product, increasing the profitability of the company.
  • Company performance risk management: Predictive analytics can also help finance professionals get a forecasted “sneak preview” into the financial mid-period to avoid surprises.
  • Receivables aging: Finance professionals can optimise receivables aging processes and collect overdue amounts faster by setting alerts when customers deviate from past payment patterns.

Top 5 Reasons to Choose SAP HANA

SAP HANA is one of the fastest growing products in SAP’s history and is viewed by the industry as a break through solution for in-memory databases. SAP HANA boasts that it accelerates analytics and applications on a single, in-memory platform as well as combining databases, data processing, and application platform capabilities. You may be thinking, “So what?” or “How does this help my business?” In this blog post below, we look at what we consider to be the top 5 reasons why SAP HANA should be on your list of new software enhancements for your business.

1. Speed – Manage massive data volumes at high speed

A live analysis was taken of a consumer products companies data revealed how SAP HANA analyses current point-of-sale data in real time–empowering the organisation to review segmentation, merchandising, inventory management, and forecasting information at the speed of thought. SAPHANA
2. Any Data – Gain insights from structured and unstructured data.

SAP HANA integrates structured and unstructured data from internal and external sources, and can work on detailed data without aggregations. SAP HANA can be integrated into a wide range of enterprise environments, allowing it to handle data from Oracle databases, Microsoft SQL Server, and IBM DB2

3. Insight – Unlock new insights with predictive, complex analysis. Before SAP HANA, analytics meant:

  • Quickly and easily create ad-hoc views without needing to know the data or query type – allowing you to formulate your actions based on deep insights
  • Receive quick reactions to newly articulated queries so you can innovate new processes and business models to outpace the competition.
  • Enable state-of-the-art, interactive analyses such as simulations and pattern recognition to create measurable, targeted actions.

4. Innovation – The ultimate platform for business innovation.

SAP HANA is an early innovator for in-memory computing. Its configurability, easy integration, and revolutionary capabilities make it flexible enough for virtually anything your business requires. Some examples of this include: ENERGY MANAGEMENT Utility companies use SAP HANA to process and analyse vast amounts of data generated by smart meter technology, improving customers’ energy efficiency, and driving sustainability initiatives. REAL-TIME TRANSIT ROUTING SAP HANA is helping research firms calculate optimal driving routes using real-time GPS data transmitted from thousands of taxis. SOFTWARE PIRACY DETECTION & PREVENTION Tech companies use SAP HANA to analyse large volumes of complex data to gain business insights into software piracy, develop preventive strategies, and recover revenue

5. Simplicity – Fewer layers, simpler landscape, lower cost.

  • Reduce or eliminate the data aggregation, indexing, mapping and exchange-transfer-load (ETL) needed in complex data warehouses and marts
  • Incorporate pre-packaged business logic, in-memory calculations, and optimization for multicore, 64-bit processors
  • Spend less on real-time computing

If you are considering your in-memory database , why not book a consultation with our experienced SAP HANA team to find out how this can really integrate and improve your business. Contact us here

Online Consumer Privacy. How will it affect the media brands you love?

Advertising and the data that helps drive personalised ad targeting dominates the virtual world. For some, it helps to make online browsing, shopping and searching more relevant. But the number of online users not wanting to be seen, or sold to, is increasing – and that is driving a worrying rise in the number of people who are amending their privacy settings to block unwanted ads or promotions.

As consumers, many of us welcome the opportunity to stop annoying pop-ups and continuous ads being served up on the basis of a search we’ve made some days before. But, from a business perspective, what does ad blocking mean for today’s media companies who rely on advertising revenues to help them make money in today’s digital era? And should media companies be looking at ways to offset a potential decline in ad revenues as the adoption of ad blocking technology grows?

A recent report from PageFair – a technology provider that helps businesses detect site visitors using ad blocking – stated that an average of 22.7% of internet users are now blocking ads – and it’s a number that’s growing at around 43% per year. The report said “[The] high adblocking rate translates directly into revenue loss for advertising-funded web businesses. One typical PageFair client site suffers from 25% adblocking, costing them nearly $500,000 per year. This scale of revenue loss can be fatal. Indeed, several sites that formerly reported data are no longer online”.

The chart below breaks down some of the Pagefair findings into industries that are most affected

adblockingSites that attract more technically advanced audiences such as the gaming and technology industries are particularly affected by this trend. These internet-savvy visitors are more likely to know how to block ads and/or change their security settings which shows in the higher incidence of ad blocking on these sites. As for the news and entertainment industries, their ads are currently being blocked by 16% and 18% of visitors respectively. Should PageFair’s reported growth in adoption prove to be accurate, then these figures are likely to climb significantly during the coming years.

Research from Google Trends also shows that over a number of years the interest in ad blocking has grown at a significant rate

GoogleTrends

 

Although ad blocking may still be in its infancy, these trends do suggest that the number of internet users deploying ad blockers is highly likely to rise in the future. And with new security settings such as the Google keyword blocking coming into force this month, media brands need to be prepared in the event that these trends do ultimately trigger a decline in revenues from the sale of online advertising space.

Is Paid Content the Answer?

One way to mitigate the possible decline in ad revenues is to offer paid and subscription-based media content. Reports around newspaper giants such as The Sun newspaper which has recently erected a paywall on its site have made the headlines in recent months. Although the paywall has resulted in a substantial decline in the paper’s online readership, The Sun’s owners, News UK, still believe that the overall profit to be gained from the paywall will prove to be a winner in the long term. The rationale behind this move is two-fold: build a revenue stream through subscription based sales, and exploit the rich data set that a subscriber’s digital footprint can offer to sell relevant advertising and cross-sell various products and services.

But of course many of us consumers are used to accessing free information – and are loathe to pay money for content that can be found for free elsewhere. If advertising revenues start to decline, News UK’s move may well be prescient in that a paywall will be one of the very few ways in which news publishers can survive online.

How technology can help protect and grow revenues

Protecting and growing revenues in the midst of shifting consumer behaviour is never easy but using technology to support business decision-making can help. Tools such as SAP solutions for the media industry are specifically designed to help companies address these kinds of challenges. They provide a good supporting mechanism in helping media brands overcoming challenges in a dynamic, ever-changing environment.

SAP Business Intelligences solutions can also help to support decision-making around content and content monetisation which can help media companies to:

  • Improve the delivery of relevant premium content based on current consumer demand.
  • Optimise sales by formulating pricing strategies that accommodate different audience segments.
  • Deliver relevant content and offers that help improve subscriber relationships and foster loyalty.
  • Better analyse feedback and behavioural metrics to assess content popularity.
  • Manage complex financial workflow to improve operational efficiencies.
  • Provide highly granular reporting on all content segments for more informed decision-making
  • Communicate up-to-date key performance indicators to relevant parties throughout the business, quickly and efficiently.
  • Better use intelligence to forecast and predict trends thereby helping to identify challenges and opportunities for increased revenues.
  • Visually represent objectives, goals and key performance indicators for improve internal collaboration and confident decision-making.
  • In today’s business climate, a well-designed technology platform can make the world of difference across many areas of your business – allowing you to take decisions with confidence and chart new courses for growth and profitability.

To explore your options in more detail please get in touch with Kedar

3 Ways to Improve Advertising Inventory Management with Business Intelligence

eMarketer’s latest estimates on digital ad spend in the US suggests that it is set to grow to $42.26bn in 2013 – accounting for 24.7% of all total media ad spending in 2013. The research also found that mobile spend is expected to grow by a healthy 95 per cent – accounting for a fifth of all digital ad spending, and 5% of total media ad spending. Meanwhile, in the UK, the Internet Advertising Bureau reported that in 2012, UK digital ad spend rose by 12.5% to a record high of almost £5.5bn. Just as digital spend crossed the £5 billion threshold, mobile ad spend reached its own milestone as surpassed the £½ billion mark in 2012 – representing an increase of 148% on the 2011 figure of £203.2 million.

The increase may help many media companies for whom advertising is a key revenue stream to offset the decline in ad spend across “traditional” offline business models – and particular in the beleaguered newspaper industry where a hefty fall in circulation for six national UK newspapers has recently been announced. But maximising revenues from online advertising inventory brings its own unique set of challenges.

Forecasting and pricing of advertising inventory – digital or otherwise – is complex. The challenges of selling perishable inventory at the right time and for the right price means publishers need to deploy sophisticated, insightful analytic applications to be successful. But when you take into account the deluge of data that’s being generated from any company’s online activities you begin to see the issue that media firms are faced with in turning this data into timely – and meaningful – business insight. Fortunately analytical technologies have moved with the times and there are a range of solutions that can help media companies to make sense of the vast repository of data produced in today’s digital economy.

Below are three ways in which media firms can deploy analytical platforms like SAP Business Objects to transform raw digital data into the meaningful business information that’s needed to inform digital advertising sales strategies:

1. Optimise Pricing Strategies.

Pricing and business analysts can spend much of their time cleaning and checking data – meaning they spend less time on analysing the information that’s needed to make optimal pricing decisions. What’s more, the amount of data that is available for analysis is increasing. Digital data has the potential to offer much deeper insight into various performance metrics (e.g. video v banner), across a variety of placement options and across differing delivery platforms (e.g mobile v tablet). Analytical tools like SAP BusinessObjects can take raw data and help organisations to create insight into the possibilities and potential of inventory, and help to inform cross-selling and up-selling strategies.

2. Improve Demand Forecasting.

A new breed of predictive analytical applications is helping organisations to identify patterns in past data to inform future business strategy. This is particularly pertinent for media companies who need to optimise demand forecasting to sell inventory. These technologies allow organisations to analyse current data and historical facts helping to better identify potential future demand for inventory.

3. Reduce Unsold Inventory.

Because of the perishable nature of advertising inventory, Media sales reps need fast, unambiguous recommendations on how to price ad inventory to maximize sales – without having to sift through large amounts of data or reading through long-winded reports. Business Intelligence solutions can equip them with this information while, at the same time, allowing them to analyse high volumes of pipeline data at any level of granularity to help inform their pricing decisions. This visibility means advertising sales professionals can react more quickly to changing sales conditions, with real-time information and accelerate deals through the pipeline to reduce the occurrence of unsold inventory.

These are just a few of the ways that business intelligence solutions like SAP BusinessObjects can help media executives to sell more space for the best price. Invenio are specialists in delivering cutting edge SAP solutions for their media customers. Contact us directly for more information.