Using Benchmarking Analytics to Improve Accounting Productivity and Employee Engagement

Benchmarking, or comparative analysis, has been around a long time. It’s always been one of those promises made by software vendors with analytics, but typically unfulfilled in reality, in terms of real adoption or genuine usefulness.

Often it's the sizzle part of a dashboard demonstration for a vendor – where they can wow the audience showing how a company’s financial performance compares against industry averages, by importing data from a third party data provider and comparing key financial and management performance measures such as Revenue Growth, Profitability, Revenue Per Head etc.

While interesting – it turns out that it’s not that useful to many, hence the rather tepid adoption within analytics deployments. If your company is less profitable than your industry peers, you probably knew it already – and to actually find the root cause of the issue is often a separate project entirely – and where the real work is. The insights are often too far removed from where the real action is, in the departments where people and process are at work.

Benchmarking to Improve Actual Business Processes

So it’s with interest that I saw a demo of the newly launched Blackline Insights, at this week’s company InTheBlack conference in Atlanta. BlackLine is a cloud provider of solutions that automate and streamline the close process for accounting organizations – enabling then to automate millions of bank reconciliations, quickly resolve intercompany reconciliations, and take the overall manual effort out of the close process.

But this is where it gets really interesting, with 1,200 customers across 120,000 users they have a huge amount of data about the productivity and processes of those accounting organizations they serve. The kind of data we're talking about here are process measurements like on-time completion rate, average completed assignments, or average rejection rate. With benchmarking, BlackLine customers can see how their own accounting function stacks up with the broader community, by metrics, by industry, and organization size.

Creating a Level Playing Field Between Employees and Managers

The opportunity is to enable continuously improving efficiency through continual measurement. But the really good news is that it cuts both ways, because it also creates a level playing field in the accounting organization between employees and managers.

The reason is that in addition to enabling management to identify opportunities to improve the close process by identifying areas of underperformance or lower than average productivity, it can also be used to ensure management doesn’t have unreasonable expectations on what the team can realistically crunch through during the close - by measuring against what's actually realistic in the industry. It’s actual data that accounting staff can use to establish common ground for productivity expectations, and it equips all parties with data to set goals that everyone buys into.

For example, perhaps the team is burning the midnight oil to get reconciliations done, but management is setting higher goals. With benchmarking, they can look up the norms in their segment – and share it with management to justify hiring or operating more effectively as an organization – real employee empowerment. And management can set goals for accounting productivity not just on gut, but also comparing with other high performing companies – realistic goals that employees know have been established with rigor and fairness, so everyone gets bought in. Data drives decisions - in both directions. That's a little more democratic.

Business process benchmarking opens up a whole opportunity for measurement - from comparing the speed of close, industry error rates, responsiveness, or speed of resolution.  It even offers future opportunities around gamification, perhaps with badges and awards for achieving business process excellence, such as being in the top percentile of performance in the industry. There's even potential of translating measurable business process excellence into LinkedIn profile fodder! 

Down the line, linking accounting efficiency benchmarks with business performance measurements can finally provide linkage between company performance and accounting process performance, providing narrative to shift the accounting organization from cost center to value center.

The Cloud as Benchmarking Enabler

The cloud makes it possible for Blackline, because everyone is running on the same codebase, and the same platform, enabling metrics to quickly be aggregated across customer usage data. It takes all the hard work out of collecting, comparing and using the data for both BlackLine, and their customers.

Interestingly, this kind of benchmarking is incredibly hard to do using tools designed for an on premise world (or fake cloud solutions)– because it requires aggregating usage, and application level metrics, across customers: so centralization and a common code-base and schema are key. You also need to get to scale in terms of the number of customers across industries to make the data useful and insights.

It’s also a pretty big contrast to the old method of business process benchmark measurement -- using infrequent surveys from professional associations and analysts, because often the measures aren’t granular, typically not broken down by industry, and then you’ve got to reconcile the data (pun partially intended) between your own internal business process measures and the survey provider. In this area, it offers the opportunity for BlackLine themselves to actually be a benchmark data provider, and even provide narrative on trends in accounting organizations based on the data.

But one of the most interesting implications for solutions like BlackLine insights is fostering a sense of community amongst users. With everyone in the Blackline community running the same solution, for the first time it enables accounting team teams across organizations to compare stats, and share tips on how they moved the dial to improve them. Everyone is sharing performance metrics, on the same playing field, and using the same platform they can actually use to improve them.

Cloud has offered up the opportunity for better benchmarking for some time, and the intersection with business process and community offers compelling value It'll be interesting to hear stories of benchmarking in action at IntheBlack 2016.

Why Planning and Analytics are like PB&J

So this post is for the planning and analytics geeks out there. I enjoy watching software applications categories undergo fundamental change, where real innovation starts to appear. And the nexus of planning and analytics is where this is happening.

Often the drivers behind these kind of changes can be technology based – such as the rise of mobile, or perhaps social or economy based – such as the rise of the self-employed economy. But when these external drivers gather momentum they often disrupt software categories. Some people go with the flow, others try and fight it.

With that in mind I read with interest an article recently that made the case for Analytics (or for the old school among us: Business Intelligence) and Budgeting/Planning applications being two separate worlds and really not needing to be unified together in a single application, that putting them together is just hype, not useful.

It was on the heels of a set of announcements from SAP, with SAP Cloud for Planning bringing together both analytics and planning – large scale analytics, data visualization, modeling and planning under the same unified hood, underpinned by SAP HANA. I personally think there is real innovation to be had at this nexus of analytics and planning, but more on that a little later.

The crux of the case in the article, was that Analytics is for the tech guys who get big data, data prep, data warehousing, SQL, unstructured and structured data etc., while Planning is for Finance, who worry about drivers, financial allocations, forecasts etc.

Different Disciplines, Different People?

I get it, my background hails from the data-warehousing, Business Intelligence, and Online Analytical Processing (OLAP). And to be honest, financial planning was a different world.  When I built dashboards and analytics for organizations, (typically for the crew in IT) there was often a separate planning implementation going on in the room next door for Finance. Each side looked with somewhat distain over at the other (I preferred to write SQL than think about cost allocations).

When Business Intelligence first emerged in the mid-90s it was built by tech, for finance-IT – we’re talking star-schemas, semantic layers, and all that good stuff – distant from the world of finance. While when the first packaged planning apps for finance appeared, they were built as apps. New technology at the time like OLAP databases were optimized for modeling and what-if? analysis for finance – but had fewer dimensions and detail for analysis and weak ad hoc analysis, while big iron driven data-warehouses were optimized for large scale analysis, but couldn’t handle changes in assumptions inherent in the modeling and planning process.

So when the rounds of vendor consolidation with Business Objects, Cognos, and Hyperion happened in the mid 00’s it was two (often more) Business Intelligence (BI) and Corporate Performance Management (CPM) stacks. Two different categories, different skill sets, different code-bases. Vendors glued these two stacks together with a veneer of branding and single sign-on to make them like a suite, but they were really different code-bases and experiences beneath the thin integration.

Change is Underway.

But just the same way that NetSuite and Workday are reimagining their respective categories in ERP and HCM for the new economy, the same is beginning to gather pace in CPM. In ERP for example, eCommerce capabilities increasingly need to work with the ERP seamlessly, from web storefront to order -- because a digital storefront is often strategic. And HCM apps need to be mobile-first in an increasingly self-service world. So, CPM is undergoing a similar transformation, just differently.

CPM is changing because planning itself has to be more responsive, more in tune than ever before with the operating environment. And that requires analytics.

A recent Hackett Group survey showed that about a third of companies intend to implement rolling forecasting over the next few years. Combined, Hackett saw over half of companies building some kind of rolling forecasting process. Hackett attributed it to increased competitive pressures on companies, and faster moving markets. Companies want to see now just further out, they want to see their forecast adjusted based on a continually changing environment.

So doing a yearly plan/budget isn’t good enough anymore either. And because organizations are increasingly moving to rolling forecasts, it means ingesting ERP, HCM, and CRM data increasingly frequently. And more frequent planning and the push for more accurate forecasting means responding to external data too. Not all of this data needs to be in the plan itself, but the planning professional must be able to update planning drivers, change assumptions, and make course corrections in the face of the larger data landscape that they are expected to respond to - and they need to see that environment clearly.

The data landscape they're making decisions on is larger than before, and they’re being asked to re-plan and respond to that landscape faster. Planning no longer takes place in a vacuum, and it takes place more frequently, and closer to the business.

The dashboard vendors don’t have it easy either. Because standalone dashboards aren’t really good enough anymore either – they don’t have a call to action in them – just seeing a chart isn’t good enough – the expectation is you’ll do something about it. You either take action in your system of record – that’s why providers like NetSuite, Workday, and Salesforce provide embedded analytics. Or you plan and adjust based on those insights, using engines that combine analytics and planning, like SAP Cloud for Planning, Anaplan, and Adaptive Insights. But a standalone run-of-the-mill web based dashboard environment (and standalone planning environment) is deteriorating in value.

But really reimagining planning and analytics as a single unified solution means starting with a clean sheet of paper. Providers like SAP are taking the lead. Remember those data stores I mentioned earlier, one optimized for planning and the other optimized for large scale analysis? Well in-memory columnar databases like SAP HANA offer the opportunity to do both in the same database and data model, which makes it easier to model and plan in the context of large scale analytics. With data visualization operating on the same data store that's being used for analysis and planning, it's a potentially potent combination, blurring the lines between analysis and modeling.

So to do this right, it really helps to have a unified system – one database engine and model – the same engine serving both the analytics and the planning, one set of common definitions, one unified user experience, one business dictionary across both. It’s no longer just gluing these systems together anymore - like what happened over a decade ago, they have to be rethought in the context of where planning and analytics are headed, and designed together.

For once, this isn’t just vendor hype. As the nature of planning changes, a new opportunity opens up to rethink the systems that enable it.

Now time for that PB&J.