Fleet Management and Data Analytics One of the most useful ways that data analytics can deliver operational benefit to a business is that of 'asset uptime'. In the fleet industry this means minimising ‘off-road’ time for the asset. It costs to have an asset out of action, both in lost revenue but also reputational risk. Most companies already keep maintenance history, but what triggers the management of that maintenance? Unfortunately, most of the time the trigger is the actual ‘down-time’ event – failure of the asset to perform when needed. However, while this provides information it is a reactionary method of managing assets and if used as the main operational policy, is a strategy that won’t allow proper planning and maximisation of assets. A better option A more effective method would be to plan and manage maintenance, based on more than just historical maintenance schedules or manufacturer guidelines. Instead, accessing and utilising your data on asset condition could dictate the required maintenance. In this way, the timing and nature of the work isn’t limited to general rules but instead becomes dependant on specific factors such as journey times (i.e. rush hour), telematics about journey routes (urban vs. extra-urban), nature of payloads, multi or single point drops (very important in the growing non-high street part of the economy i.e. retail delivery, internet shopping etc) plus other driver behaviours. But this isn’t always easily accessible. Solution delivery Planning is key to taking a proactive approach and Blue Label Consulting can fulfil that need by offering a joined up data analytics solution. Integrating telematics and vehicle data to co-ordinate service booking means the focus is on getting 100% of maintenance done via automated service booking lines. This method provides enhanced operational capabilities for the business including:
Working with Blue Label Consulting helps introduce more operational control within the business. This allows companies and fleet managers to let the day-to-day running of the fleet (and therefore business) run in a more streamlined and automated manner. This in turn creates more time to identify future trends in the market, better plan operational changes, reduce costs and increase profitability. If this is an issue for your business and you are interested in understanding more about this approach please contact us here. Brendan Jayagopal Founder and Managing Consultant Blue Label Consulting
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'It always surprises me that many leasing businesses understand the importance of analytics and yet they are reluctant to sufficiently invest in skilled staff and systems or expert support.' Accessible data is key to creating a strong consumer centric leasing product, but only through advanced analytics can a business mine this information and integrate the data to turn the underlying patterns into usable insight. Often businesses implement decisions based on relatively basic information e.g. cost drives many consumer decisions leading to cheaper product offerings. However, consumer actions are clearly not this simplistic as many other factors are part of the overall consumer decision making process such as brand perception, cost vs. utility, cost vs. value, the purchase experience, customer service / support, availability of product at the time the consumer is in the market and so on. Given this fact, more detailed insights would provide a multi-dimensional view of the array of factors a consumer will consider in their decision and also how these interact with each other. If we take cost as a start point, we can look at a list of items that might influence a decision to lease a vehicle:
Plus the following where not already included in a monthly rental amount:
Consumers are usually willing to trade off some of these cost attributes against each other, incurring more cost in some areas if they can offset this against other areas. For example, they might accept a higher monthly rental if it includes most or all aspects of maintenance (safeguarding them against large irregular and/or unexpected expenses). They might focus on fuel economy (for higher mileage users), BIK tax (for those users in this 50/60yrs+ segment still in work or owning businesses), RFL Tax and Insurance costs (for those focusing on running costs other than fuel) and finally perhaps even current or future congestion charges (if frequently visiting city centres). So how do leasing companies best review this data and understand how they should design relevant and attractive product offerings? Having a robust analytics solution will help leasing companies analyse the data and understand how these different attributes affect the consumers decision. For different consumers these attributes will rank in a different order and they will intersect in different ways. The final result from this analysis will be a very specific answer: exactly which product suits the customer. In the case of vehicle leasing, it’s the difference between recommending a BMW, Audi, Hyundai or a Skoda for the consumer. The results may be surprising – whereas most leasing companies may focus on manufacturers such as BMW or Mercedes in trying to get the best discounts, the best relationships may in fact lie with other manufacturers for the 50+ segment group. Indeed some initial analysis suggests that Volvo, Skoda, Kia and Nissan could be better matches when looking at overall cost, product quality, product specification and practicality of product. This could be taken even further. Once the consumer has made their initial selection, a recommendation engine could then serve up comparable alternatives to consumers based on price, value or eco-friendliness. For instance, if the consumer’s initial selection is an Audi A5 Coupe, the recommendations could be:
To find out for sure however, it is essential to pull together the data you hold and deploy an advanced analytics solution to make the best possible sense of the information to drive well informed, targeted product design. Brendan Jayagopal Founder and Managing Director Blue Label Consulting It’s a complex and competitive market out there and any business is more likely to grow market share if it can offer products tailored to specific customer types.' Central to this is a detailed understanding of customer needs, including the various push and pull factors that drive customer decisions and ultimately their final purchase choice. As an example, one of the largest segments of the UK leasing market, the 50+ age group, is also perhaps the least well catered for. At first glance this seems a segment unlikely to be profitable. However, a more data informed outlook would show that potential customers in this segment are:
The main risk associated with creating a product for this segment is the asset maintenance cost, as this generally increases exponentially with asset age. However this can be quantified and built into the product via fixed maintenance costs which, as an added consumer benefit, provides the customer with known costs and therefore peace of mind Good data analytics is essential to understanding your customer in order to create better and more relevant products for each segment. At Blue Label Consulting we can help develop your analytics capability and increase growth opportunities across your customer base. Contact us here if you are interested in finding out more. Brendan Jayagopal Founder and Managing Consultant Blue Label Consulting New product development for premium leasing brands Volumes of certain premium car brands are now so high e.g. Mercedes C-Class, BMW 3 Series and Audi A3s that they are overtaking some mainstream brands. This oversupply in the market affects used prices (e.g. 10 years ago 3 Series would achieve approximately 50% of list price as a used asset at 36/60, but is now just 30%). Another issue is that bringing premium brands to disposal channels (auction) even when volumes are low has a cost barrier. For example used Teslas are still commanding strong used values with auction prices £50 - 60k plus. Both of these problems (over supply and cost barrier) can be solved by creating data led products that deal in re-leasing these used assets. Re-leasing keeps them in a profitable cycle until either market conditions improve (or disposal is more profitable than re-lease) or until further asset depreciation occurs and the cost barrier is reduced. And there are considerable benefits in re-leasing older stock for both the leasing company and end customer. Leasing Company Benefits
Customer Benefits
In short, if you are not investing in your data analytics capability to design more relevant and therefore more attractive products you will find your business at a competitive disadvantage. If you want to discuss this in more detail please feel free to contact me here. Brendan Jayagopal Founder and Managing Consultant Blue Label Consulting |
brendan jayagopalBrendan launched Blue Label Consulting in 2011. With innovative use of Data through emerging data sciences such as AI and other quantitative methods, he delivers robust analytics and actionable insights to solve business problems. Archives
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