In EY’s latest Global Divestment Survey, 90% of European companies said that they plan to divest assets within the next two years. Of those divesting, 87% said the main reason for selling an asset was its weak position in its market place.
How can companies prepare this type of business for sale? I think the answer lies in building a deeper understanding of the business and its potential – and that analytics is the key to unlocking this information.
Be clear about why you’re selling
Since the sun has come back out this week in the UK, let’s imagine a scenario where the theoretical company, Food PLC, has decided to put its ice-cream business up for sale. The unit’s financial performance is satisfactory; but the board have decided to sell now because of its low market share and the considerable investment required in production, distribution and marketing required to compete with its rivals. They’ve decided that this capital could be better invested elsewhere in its core businesses and on acquisitions that have a better fit with their overall corporate strategy.
This is a very common scenario. EY’s latest divestment survey shows that ‘lack of market share’ is by far the most frequent reason given for selling assets. Effectively, by deciding to sell, the board of Food plc is giving its ice cream business a better chance of achieving its true potential. But, how do they bring buyers to the table? Traditionally, the seller would provide data on sales, profit margins, growth projections, inventory, logistics, distribution, geographic reach etc. But, this approach is unlikely to deliver maximum value in today’s competitive market.
Potential buyers now expect far a more in-depth and tailored analysis when sourcing deals. They’re looking for more than short-term opportunities. They want a detailed indication of the potential and risks associated with this business – not just in general, but specific to them as its new owner.
Build the value story
Higher expectations stem from advances in transaction analytics. We’ve moved from descriptive analysis, which understands the reasons for past performance, to a predictive analysis that incorporates multiple data sources (internal and external) to predict future scenarios. This kind of analysis is invaluable in transactions. Not only can it highlight the potential for underperforming businesses, by looking at operational metrics and financial outcomes, but it can also be used to model commercial outcomes and build a complete value and synergy story for each individual buyer.
A capacity and cost base analysis of our theoretical ice-cream business would allow individual buyers to accurately forecast cost synergies. Ingredient analysis could assess pricing trends, but also crossover with potential buyers and the potential to swap ingredients to cut costs, lower calories or to reach new markets, i.e. ‘free-from’. Potential buyers could have channels in common, but would also be looking to factor in the impact of changing sales models – such as food subscription services – and the potential to reach into growing markets, such as vegan. Clearly weather is a major factor, so any analysis would also need to take into account the impact of seasonal weather patterns on sales and distribution channels. This could be married with climate data and major events to predict changing sales patterns.
Overlaying data on customer views, buying patterns and market research – from company data and external sources, including social media – provides insight into the potential impact of these changes and the brand’s potential. All of which can be further overlaid on a potential buyer’s geographic and product footprint to provide an even more tailored view.
This is by no means an exhaustive list and each sale will be different. But, by identifying likely buyers up front, considering how they might generate synergies and using data and analytics to corroborate these, sellers can focus on telling the ‘value story’ through a buyer’s lens. By applying this lens, it will become clearer where the value accretion opportunities lie for the buyer and make it less likely that sellers leave value on the table.
Separate the needles
Data availability does vary by sector and also company history. Years of joint venture activity and consolidation complicate datasets. But, data analytics gives us the best chance of optimising what is available.
In the past, it could have taken groups of people vast amounts of time to even to search out this information. But, today we can utilise analytics to extract insight from data and unearth hidden gems from datasets that have been deemed inaccessible or too chaotic in the past. This is performed at a speed that just would not have been possible before, allowing a far deeper analysis even for short duration diligence engagements.
In building a holistic picture of the business and its market, deal analytics is becoming a crucial part of disposals and post-deal integration. Its benefit is such that it’s now considered by major companies to be an essential part of the transaction process for buyer and seller. According EY’s Divestment Study, 78% of UK companies leveraged advanced analytics to understand the true value of a non-core asset in their last divestment. Moreover, 51% of UK sellers expect to make greater use of social media analytics in their portfolio decisions in future — more than double the result of the 2017 survey. A sign of just how far we’ve come.
Prepare to succeed
How far in advance should companies think about transaction analytics? Adoption as possible in the deal process is obviously advantageous, since it will help ensure the sale starts on the front foot. As my colleague Charles Honeywill has written here before, there is a strong argument for Food plc taking a leaf out of private equity’s book and essentially keeping all non-core businesses on a disposal footing.
Why? Because there is so much value in being prepared. Of UK companies’ most recent major divestments, 69% were prompted by an opportunistic, unsolicited bid. By maintaining a conscious focus on ‘exit readiness,’ using analytics well ahead of a transaction to identify value drivers and mitigating value erosion risks, a business can materially impact the final outcome: achieving both a higher value and a quicker sale.
It is also interesting to ponder exactly how the transaction process will evolve as analytics becomes a more every-day process. My colleagues, Paul Reading and Kenneth Ingram, have written a highly engaging blog on the opportunities opened up by democratisation of analytics, based on a break-out session at EY’s Private Equity Portfolio Forum. It certainly feels we could be at a tipping point in terms of adoption, as computing power and analytic tools become cheaper and more accessible. As they put it:
For CEOs and CFOs, this represents a unique opportunity to transform how KPIs are designed, derived and implemented to drive strategic and operational decision making, without the need to invest in full-scale enterprise resource planning (ERP) solutions.
Still, businesses need to beware the pitfalls. The software may be more accessible, but we know many companies are finding it hard to find qualified staff in-house. And, it’s worth keeping in mind that not all data is valuable. Somethings don’t change and in analytics – as with so much else – the commercial drivers for any action must be clear.
Find out more about how EY helped Costa transform its store proposition.