On the morning of June 24, 2016, residents of Great Britain woke up to the news that their country was going to leave the European Union, as a result of the Brexit referendum vote held the previous day. The reaction to Brexit in financial markets was swift, with the British pound sterling dropping sharply against the currencies of the country鈥檚 major trading partners. Business decision makers in the UK and around the world had to contend with a new variable in their strategies for producing and selling goods and services.

Brexit may be one of the more extreme examples, but political and economic surprises seem to be happening with more frequency in recent months. For managers worried about the effect of large-scale surprises on their demand markets, it is more important than ever to聽gain a stronger hand over things that they can control.

What challenges will the CG sector face as a result of Brexit?

Depending on where goods are manufactured, CG companies are planning up to 25% cost price increase. However, if the company is based in the UK, they may actually benefit from competitor CPI and will have an opportunity to increase market share in the UK. Overall, it is expected that there could be potential trade barriers and increased bureaucracy, supply chains could become less efficient and the timeframe for getting goods from the country of origin to the destination may increase. This, in turn, may lead to holding increased inventory in the UK i.e. reduced cashflow. Brands in 2019 will face the dual challenge of staying competitive versus other brands by reducing trade spend and also preparing聽against the retailer鈥檚 private label that has witnessed the market share grow across all categories in the last decade.

What can CG companies do to prepare for uncertainty?聽

You can鈥檛 do much about outcomes like Brexit 鈥� or, for that matter, about the economic impact of unemployment, inflation or GDP growth trends. But you do have data 鈥� historical records of sales that give you insights at the granular level of every customer and every SKU sold to that customer. That set of data is the key to making informed decisions around promotion activities, integrating those decisions with other marketing levers such as assortment mix & category management, and anticipating alternative outcomes through what-if scenario planning.

Modeling for the Unknown

That last point 鈥� anticipating alternative outcomes through what-if scenario planning 鈥� becomes a critical component of your trade promotion management in a world of Brexit-like surprises. What if the national currency in your major selling market plunges, like the British pound did after the Brexit vote? What if that triggers a much higher than anticipated inflationary trend? What if unemployment rises and demand for discretionary spending by your target consumer demographic falls?

Scenario planning enables teams of promotion and other marketing decision-makers to understand the real, monetary implications of these what-if situations. Trade Promotion Optimization (TPO) software with scenario planning capabilities gives managers the ability to evaluate alternative probabilistic outcomes 鈥� for example, 25 percent best-case, 50 percent default-case, 25 percent worst case 鈥� and see the variation in revenue, profit margin, profit dollars and other key financial metrics.

Machine Learning Vs. Black Box Approach

Marketing managers know how quickly data can become stale and outdated. Consumer demand is constantly evolving 鈥� and at an even faster clip in a world where social media, online reviews, and third-party incentives can change tastes and preferences in real time. Historical data patterns can lose predictive value unless there are ways for the system to 鈥渓earn鈥� and process new information in real time. Recent software platforms have evolved to enable this kind of learning.

For example, a salesperson in the field may become aware of circumstances around a planned sale that call into question prior assumptions. It may be something as simple (yet unexpected) as a freak weather event with the likelihood of disrupting near-term demand patterns. Or it may a sudden Brexit-like surprise with similar disruptive potential. The salesperson has the ability to input this observation via Data Scientist into the system 鈥� effectively 鈥渢elling鈥� the predictive models that a new, previously unaccounted-for variable is the reason why the outcome for this sale may measurably vary from established patterns. The models learn, and the data become available for even more nuanced 鈥渨hat-if鈥� scenarios going forward.

It would be nice to live in a world where you didn鈥檛 have to reckon with the impact of major external surprises on any given day. In the absence of that, though, good data and informative models give you the power of understanding 鈥� and measuring 鈥� their potential impact.

Promax TPO has predictive planning capability 鈥� based on the machine learning concept, it provides users the ability to quickly and efficiently conduct 鈥榳hat 鈥� if鈥� analysis to model different promotion scenarios, and review systematically generated business outcomes to determine the best combination of promotional inputs. It enables a powerful planning and analysis ecosystem that can be tailored to the needs of each business stakeholder. Our data science and professional services teams are led by experienced domain experts to help you create predictive models to give your business a competitive advantage through best practices in trade promotion optimization.

For more information, visit our website http://promax.wipro.com聽 For queries, write to us at 聽WPAS-Promax@wipro.com