Creating the tech foundations for Legal Project Management at scale


Welcome to the second installment in our LPM at scale blog series. Having dived into the type of matters which should be eligible for LPM, this week we will be looking at one of the more challenging aspects. The data and technology which can support LPM.

Because this series is designed to be a practical guide, we will be beginning with tips that even the smallest law firms can benefit from. We’ll be touching on Gartner’s PACE Layered Application strategy and how it can support the different steps towards firm-wide LPM. Finally, we’ll be offering some unique perspectives on data streams and how their insights can support greater LPM adoption.

A few data and tech misconceptions

We are aware that, as a business intelligence tool for law firms, we have often been guilty of lambasting the use of Excel. Yes, it is not the best tool out there for monitoring matters. However, for firms at the beginning of their LPM journey, it is still effective at monitoring small numbers of matters. So, before you dive into the purchase of a paid service, consider getting your data-driven ducks in a row and monitoring a couple of matters in Excel.

Second, we think it is important to recognise that a successful LPM strategy actually begins with data governance. Monitoring and evaluation of LPM is only possible with data collection and analysis. Which in turn requires a well thought out strategy, embedded in a data governance document. Consider reading our guide to designing and implementing a data governance strategy before you start monitoring your first matter.

Finally, one of the biggest stumbling blocks for firms is in failing to recognise the potential challenges a data set represents. We have written extensively about why codes are rarely applied accurately. Which means that any efforts to improve or change processes with data developed from codes are likely to fail as they sit on flawed assumptions and flawed data. Ensure you are as critical as possible about the data streams you rely on, before using them to inform your decisions.

So what data should we be recording?

In the age old answer of lawyers everywhere… It depends. But this is neither a helpful nor practical answer, so let’s dive into the possibilities. First, begin by identifying the core purpose of LPM. If this is your first foray into project management and you just want to identify the profitability of a matter, then think about metrics which can help. If you want to stop matters from going out of scope, then think about which data will help define that scope.

At its core you can probably divide your ‘streams’ of data in the following ways:

  1. Data about your activities. This is the most basic core of LPM monitoring - identifying what work is happening under a matter and how long it takes. Think about whether you want to rely on codes, or use more sophisticated natural language processing to identify activities from the narrative. If you’re really starting out, you can even manually code the activities into an Excel spreadsheet for analysis. Remember, you can add layers of sophistication to this data by also assigning practice groups or industries to these activities if that insight informs your LPM goals.
  2. Data about who performed the activity. Obviously tracking the person who completed the activity is helpful. Here, the trick is to enrich this data with secondary information. By associating specific timekeepers with seniority levels or practice groups offers richer insights about the wider performance of key groups within the firm. Equally, if you wish to reduce out of scope work, tagging someone with their seniority level means it is easier to identify if a Senior Partner is logging hours to a matter which hasn’t budgeted for their work.
  3. Financial data. Basic information about billed hours and realisation rates is essential if the purpose of your LPM process is to identify profitability. More sophisticated analysis is possible if you begin combining your financial data with your activity data. Consider comparing the realisation rates for due diligence, with those for M&A. Is it different? If so, why? For firms which work with AFAs or budgets, it is obviously wise to monitor billed hours against budgets to prevent cost overrun. More on that later.
  4. Matter process data. Looking at matters as a whole lacks nuance. It is far more difficult to identify cost overrun on a complex matter without breaking it down into smaller pieces and assigning budget to each. Generating matter process data, by creating phases and then assigning activities and budget to these phases gives better oversight and more granular profitability insights.
  5. Stand alone data. Not all firms have the same aims with LPM. Perhaps you want to monitor whether a new tool reduces the cost of an activity. Well, then add an extra column to that Excel spreadsheet and identify whether an activity did or didn’t make use of the tool. Then you only need to analyse the difference in hours, realisation rates or time.

This list isn’t exhaustive. However, it is made up of data which is by and large already available to firms. Our advice is this. Make sure that your data collection methodologies are consistent. If one half of your team is rounding up their hours, and the other half is recording the exact amount of time they take to perform an activity then you have a discrepancy. The same goes with logging this data (even in Excel). Everyone needs to understand and use the same classification system, so consider how to develop and communicate (and then monitor) that system effectively. This is especially important if you are still manually entering data.

PACE and the layers of technology

So, you’ve established your LPM goals and have a robust data governance policy. You have evaluated and are collecting matter data. At this point in time, most firms are thinking about technology. There are a host of tools out there to support law firms in the collection and analysis of data. While we’d love to recommend everyone head out and buy Clocktimizer now, that isn’t actually a realistic approach. So how can firms approach the purchase of technology coherently?

For that, we can turn to Gartner’s PACE Layered Application Strategy. Which is a fairly complex way of saying that there are three major layers of technology within a business. You need to have the first layer in place, before you can move up to the second and third layers. This is simply because more complex types of technology often sit on the outputs and analysis of earlier layers.

Reproduced from CIO Wiki

The first layer, Systems of Record, covers the basic tools which (and the clue is in the name) record your data. The technology is designed to ensure that the generated data is delivered in a standardized format so you don’t need to worry too much about user input errors. This layer of technology should be in place before your firm develops LPM as the data it produces will form the basis of LPM monitoring and decision making. Tools include:

  • Time recording tools: Most firms will have a tool with which to record time. There are many out there and consider evaluating how effective your current one is. Tools like TiQ can automate some time recording based on your screen activities. After all, the more sophisticated the time recording data you collect, the better your LPM insights.
  • Financial recording tools: Tools which keep track of your firm's finances are also essential. Again, consider evaluating the details of the data your finance software tracks. Perhaps others offer more insights? Or can integrate with your time tracking software. The same goes for billing software.
  • Client intake & relationship management systems: All firms should have a system to perform client intakes and then monitor and record the relationship. This could be simple data like which matters are running, to more complex insights like their profitability.

Systems of Differentiation

Having established a base of tools which record data, your firm can then move on to the next layer. Systems of Differentiation. These tools often use the data produced by Systems of Record to support or enable processes. This is the layer that Clocktimizer sits in. We are able to combine the data from timecards and financial systems to develop AFAs, monitor and track budgets and offer matter oversight to LPMs.

There are an incredible number of tools and applications within this layer. While it would be very difficult (and frankly a little biased) for us to offer our own advice on which technology to buy, we can offer some advice on the key characteristics technology in this layer should have:

  • Flexibility: This layer of tech needs to sit upon the data streams of prior layers. Thus, it needs to be flexible in accepting multiple different data formats. If you were to change your time recording software, you shouldn’t need to worry that the data format it produces won’t be readable by your business intelligence tool any more.
  • Constant innovation: This layer is about technology which supports processes, and processes change. Try to select technology which is constantly improving and innovating alongside its customers.
  • SaaS or stand alone products: A lot of process based technology is tied to consultancy and pitched as bespoke or tailored. This can be very helpful initially. In the long run, it means your version is static and that you rely on an outside company to get the most out of it. You are unlikely to receive as many new features because your code base is different. SaaS solutions have a single product which is constantly improved, preventing obsolescence. Once you have identified a product which suits the way you work, test it out!
  • Scaling and Systems of Innovation

So, on to the final phase in the technology and data puzzle for scaling LPM. Systems of Innovation. According to Garter, the technology which arises from this layer is ad hoc, and built to make use of a specific opportunity or challenge. These tools are often unique to a firm and may be developed in house.

For firms without an R&D arm, this may seem a way off. However, as your LPM functions mature, you may consider changing the focus of your project management efforts. In collecting more sophisticated data, or identifying challenges or blockers through matter analysis, you may begin to identify a use case for proprietary technology. Key to the success of technology in this layer is in identifying a use case for it, and in analysing its success. Given the short lived nature of ad hoc tools, they should be able to show an ROI which includes the costs for their development and deployment.

Importantly, tools in this layer are most successful when they are data driven. Ensure your firm has improved the reach and efficiency of tools in the second layer to provide a clearer picture of the gains tools in the third layer can provide. Examples from existing customers include client dashboards, driven out of a push for transparency or shared workspaces for complex matters to integrate in-house and external team work.

In our next blog

Our next blog in the series will be looking at one of the most important (and often overlooked) contributors to the success of LPM. A stakeholder and communications plan. The vast majority of change efforts fail because users don’t understand or value the motivation behind that change. So we will dive into strategies and tips from the industry to ensure effective LPM adoption as you scale.

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