Firmwide Analytics and Pricing
Welcome to the fourth installment in our blog series on firmwide analytics. Ask anyone who has attended a legal conference recently, and they will tell you that data is everything. From AI applications to machine learning, it all hinges on information. However, there seems to be less certainty about exactly which data everyone should be collecting. Or why for that matter' For this very reason, we at Clocktimizer will be looking at the full range of data analysis available to firms. We will be breaking down firmwide analytics by department and exploring the data to collect, the insights you can hope to gain from it, and how you can apply these learnings in your firm.
This week we are looking at one of the most challenging areas for firms. Pricing. Fixed fees grow ever-popular, but the data to support them is often weak. Many firms simply make an estimate of hours and multiply that by their blended rate. In turn, because these fees have little foundation in data they can lead to write-offs, or they can prevent a firm from pricing in a competitive way. At Clocktimizer we believe that the introduction of fixed fees is a good thing. Not only for transparency but because it encourages better internal scrutiny of processes and costs for law firms. We take a deeper look at why and how your firms should tackle this essential area of analytics.
The theoretical perspective on pricing
According to Altman Weil's 2018 report '95.8% of law firms expected increased price competition to be a permanent trend.' The logical conclusion is that value-based, and tailored pricing will become increasingly essential in order to win new clients or retain existing ones. The difficulty is in identifying what value really means to your clients.
In this respect, many online commentators support good marketing strategies, so you can convince your clients that your pricing is good and represents value. Others recommend pushing for pricing which undercuts your rivals. Yet more, suggest pricing which first identifies the value to the client of the work, and then prices accordingly. All of these strategies have their merits and downsides. However, we would recommend your pricing strategy has one thing.
Flexibility.
Everyone's concept of value will vary. A single set strategy can work with a niche of clients, but a flexible one, based on data, works with many more. By truly understanding your internal processes, and then identifying where your firm can be flexible, you can ensure your pricing strategy works for as many clients as possible, in a sustainable way. But central to the success of this is data.
Know your variables
Heading into a pricing arrangement, you need to understand some key variables. Without this information, creating an accurate pricing structure will be unsuccessful. These include:
- Scoping data - what work exactly does a client want? Have you defined specifically what they do and (importantly) do not want to be done? Do you know seniority levels, timeframes, and desired outcomes? Remember, the more accurate your scope, the more accurate your fee quote, and the fewer write-offs you will offer.
- Value data - what does the client most find important in their relationship with their outside counsel? Is it the speed of response? Is it regular updates? Or is it simply a low price point?
- Historical matter data - how much did these specific activities cost before, in similar matters? How long did they take? Were the matters concluded successfully? Were there write-offs, and why?
- Historical pricing data - this is closely linked to historical matter data but includes greater financial detail. What fee arrangements have you used for this type of work before? How profitable was the matter before? What was not profitable and why?
The majority of this data can be collected from three sources. The client themselves; by interviewing them on what they believe constitutes 'value' and on what exactly they would like the firm to do. The general ledger, or other financial records; which will give insight into the profitability and pricing structures used. And the timecard data; which will reveal more granular financial insights on profitability and will offer the historical matter data.
Building your fee quote
This may seem like a lot of data to collect to build a fee quote. However, this level of insight and data to draw upon allows your firm to be flexible in their pricing structure. How? By using tools, like Clocktimizer, which combine these data streams and perform pricing analysis for you.
At Clocktimizer we ensure accuracy and tailorability of fee quotes through a number of ways. These are not exhaustive, but should give an idea of how to build accurate, yet flexible fee quotes.
- Finding similar matters. To properly price work, you must understand how much it has cost in the past. We use a nearest neighbour algorithm, which uses one matter as an example, and looks for other matters with a similar 'DNA'. This means we identify the type of activities performed, the seniority level of those doing each activity, how long they took, etc. This way your fee quote has a solid base, and can draw from a large number of matters. The more matters you can compare, the more accurate your fee quote will be.
- Creating matter building blocks. Similar matters can then be broken down into common and uncommon activities, which have an average price and number of hours. You should be able to add these building blocks in a tailored way, based on the scope you have built with a client. Note that these can be incredibly granular if you avoid using codes and instead use NLP to read the activity description itself.
- Flexible variants. Does your client refuse to pay for junior associate work? This is a variable you should be able to filter out from your building blocks. The same can be said for other factors based on data you collect and tag in your fee quote system. The more data you collect, and integrate in your fee quote system, the more flexible your pricing structure can be (and the more satisfied your clients).
By following this process, your fee quotes have a solid foundation in data, and offer the flexibility that your client wants. After all, your historical data is the best way of determining the cost of activities you complete in the future. You simply need to be able to find and select the most relevant historical data.
Optimising your pricing process
'Pricing isn't just sort of an independent group, it's part of an ecosystem of support for lawyers that includes pricing, project management, and knowledge management,' Brian Fanning, Director of Practice Economics, Davis Wright Tremaine LLP
Having begun the process of collecting pricing data, and analysing it to produce good fee quotes, the final piece in the puzzle is optimisation. Pricing impacts most facets of a law firm. In turn, many facets of the law firm impact pricing. Optimisation of the process is about understanding and improving that relationship in order to improve profitability.
Again, this process requires data. A fee quote, and its resulting effect on firm profitability, can be improved by addressing points at which fees are discounted or where costs can be cut. These should include collecting and analysing data in the following areas:
- Unbillable hours
- Price discounts
- Efficiency measures
- Write-offs
Where you have hours logged which are unbillable, it is essential to understand the reason behind them. After all, the cost of this work is covered by the firm, but not compensated and will affect the bottom line. Once you understand what is not billable, identify whether the work can be automated, or reduced.
Price discounts are a common occurrence. But their existence is rarely justified. Where you understand and price according to a client's wishes and what your firm can support, you should not offer discounts on fees. Collect data on clients for whom you offer discounts and try to identify how profitable the work is to your firm. Are these discounts sustainable? If so, they aren't a discount, they are a fee structure. Are they unprofitable, but lead to you retaining a good client? Work to change this relationship then.
Efficiency measures are something of a crossover between pricing and LPM and knowledge managers. Essentially, identifying tasks that could be done faster, or for a lower cost, or that could be automated, supports all areas of the firm. Pricing teams should collect and analyse data to find activities that fit these criteria. If they can identify ways of making these processes more efficient, they can reduce costs and increase profitability. This process can be supported by the use of tools like Clocktimizer which integrate LPM and pricing functions and show low hanging fruit for efficiency measures.
Write-offs. They are the bane of the modern law firm. Not least because many write-offs are the result of a lack of data to begin with. When clients query a larger bill, often firms are unable to justify the expense and instead, write it off. However, by collecting data on your matter and sharing this regularly with the client, you should be able to avoid this problem. Again, tools like Clocktimizer can manage budgets and share regular, automated updates with clients so final bills do not come as a surprise. The second key reason for write-offs is that out of scope work often happens before anyone realises. Again, collecting real-time data on a budget will avoid this type of write off from occurring, by preventing out of scope work from accruing to a matter. In all instances you should be collecting data on why write-offs happen, and look to implement solutions which prevent them
We recently did customer success stories on the subject of firmwide analytics and pricing. You can find them here if you have not read them already.
Next week
In our fifth installment we will be looking at firmwide analytics and Knowledge Management (KM). While KM is a regular feature on the legal conference, it is not a ubiquitous feature in law firms. However, it provides an essential function in firms with so many moving parts. We speak to Stephen Allen, Global Head of Legal Service Delivery at Hogan Lovells, about the connection between data and good KM.
