Data – Is it worth the investment?
The importance of harnessing data to inform commercial decisions is something most people agree on in principle. Enthusiasm wanes however when it comes to the question of what is required to make it happen.
Data – Is it worth the investment?
The importance of harnessing data to inform commercial decisions is something most people agree on in principle. Enthusiasm wanes however when it comes to the question of what is required to make it happen.
It’s a common perception costs outweigh benefits or that a focus on data is time intensive and gets in the way of the day job.
I believe this rings true for partners and fee earners, as well as for finance and business development professionals. Focusing on using data and everything that entails undoubtedly requires time and effort, but mostly on the part of those with direct responsibility for managing the data, the processes, and the systems. The onus on those that use and benefit from the data should be minimal.
Collective passion
Overcoming these barriers to develop a better culture around data requires focus, determination, and busting the myth that the effort will take more time than it is worth. It also requires a sense of realism about what you can achieve and an acceptance that – as with any new tool or novel approach – trial and error is acceptable.
Focus and determination are crucial but not sufficient. You need passion and conviction to drive this effort and you need likeminded colleagues to join your merry band. When you start talking about the significant benefits of what you could achieve, you will find people in other parts of the business equally frustrated that “we have not cracked this data thing yet”. Sharing your drive and passion with others will help in moments when it all feels too hard. And those moments will come!
Establish the infrastructure
Once you decide what insights you want and you know what data will support those, the main priority is thinking through how you collect the data and how you play it back in an accessible and digestible way. Data collection is the key part in getting your project off the ground in the first place. Too much manual input or additional admin will soon get you back to “we don’t have time for this”.
This is where existing, or new and smarter, technology can support. Depending on the level of technology investment in your firm, you might encounter additional hard costs that you need to assess against long-term benefits and return on investment. You should be able to put together a business case based on how you want to use the data, the insights the data could provide and direct benefit to the firm. Be it measuring the effectiveness of campaigns, assessing the true value of client relationships, or targeting BD time and expenditure.
If you have the basic infrastructure in place – client/matter intake process, financial system with basic reporting functionality, CRM system – you can still use data to your advantage from your existing technology stack and processes which your firm needs for other reasons such as compliance.
If your firm invests in additional technology, you can use this to scrape or mine data from other sources (Outlook, DMS, SharePoint, practice management, collaboration tools and applications, and so on) to feed into your CRM or other reporting tools. You will be surprised at the volume and variety of data you can extract from what you have already. It may simply be a case of making sure it is entered correctly (easier said than done!) or adding some integrations to your reporting or CRM systems.
Meaningful reporting
When you have established the infrastructure, your next priority is considering how you want to play the data back to the business. Data on its own is meaningless, particularly to busy people under commercial and client pressure. When you consider your process for collecting data, you should decide what reporting and insights the business requires and where it will access it.
Rather than directing people to an inbox to request a report, it’s critical that you create a self-service environment with support on an as-needed basis. The reports or dashboards should help business users understand what the data is telling them. They can include charts and graphs that indicate trends, green or red flags that indicate activity deemed positive or negative. You should always factor in training and easily accessible guides but, overall, the reporting should be intuitive.
“When you have established the infrastructure, your next priority is considering how you want to play the data back to the business. Data on its own is meaningless, particularly to busy people under commercial and client pressure.”
“When you have established the infrastructure, your next priority is considering how you want to play the data back to the business. Data on its own is meaningless, particularly to busy people under commercial and client pressure.”
Proof of concept
When you are ready, you should pick some smaller areas where you can assess the benefits of your data approach. In CRM, these areas could be key clients, specific sectors or even locations. A big bang approach will not work when it comes to data or trying to drive a data culture. You can plan the infrastructure across the entire firm, but when it comes to implementation, smaller proofs of concept or mini pilots are more workable and offer a better chance of getting traction and successful outcomes.
You can run pilots with people and teams that you know will engage and help you demonstrate value. There are always parts of the business that want to lead or that have a problem that your data, reports and insights can resolve. These enthusiasts – or “early adopters” in technology terms – provide you a platform to go out to the wider firm and to drive adoption.
Whilst this approach may seem inefficient, you are more likely to succeed by directly engaging with smaller working groups, rather than running big training sessions and hoping for the best. One challenge of solely relying on a big training programme is that you rely on people to implement what you are teaching them straight away.
With smaller groups, you can work on something specific, something they need and can use on a regular basis. The more they use it, the more they will remember what to do and are more likely to use it. Focusing on smaller groups also allows you the flexibility to try different things to see what works and to amend your plans as required, all of which should lead to greater adoption.
Perfection vs benefit
From the outset it is critical to remember that you are not seeking perfection. Some may argue that if the data is not 100% spot on it is useless. That is not the case. You need to be confident that the data you have is of a suitable quality, but you do not need to have everything. When looking at a client relationship it would be great to log every single billable and non-billable engagement, but in practice this will never happen.
The data you do have is still useful because it provides insight, another piece of the puzzle. You do not need to complete the puzzle to see the full picture, just enough to know what you should do. Data on how clients are engaging – reading email, clicking on content, attending events – can tell you where you should focus your efforts and help you determine if you could support them in other areas.
Final thoughts
Rome was not built in a day and that is fine. You need to chip away at this to achieve a virtuous circle of demonstrating value and driving adoption. As you deliver more value, more people will engage. As more people engage, you can deliver more value.
The answer to the question whether data is worth investing in should always be yes, but you should never underestimate the sheer passion and drive you need to see something like this through. The initial time spent on setting up the infrastructure is key.
You need to put yourself in the users’ shoes and work on processes that decrease their admin time and demonstrate immediate value to them. Once you have cracked that, the rest is implementation, and continuous trial and error (technology should never stand still after all) so you get to a position where you can support commercial decisions in a more robust and scientific way.