# This Structure has Novel Features which are of Considerable Business Interest

A skilled practitioner, hard at work developing elements of a Structured Reporting Framework
© Jennifer Thomas Photographyview full photo.

 For anyone who is unaware, the title of the article echoes a 1953 Nature paper [1], which was instead “of considerable biological interest” [2]

Introduction

I have been very much focussing on the start of a data journey in a series of recent articles about Data Strategy [3]. Here I shift attention to a later stage of the journey [4] and attempt to answer the question: “How best to deliver information to an organisation in a manner that will encourage people to use it?” There are several activities that need to come together here: requirements gathering that is centred on teasing out the critical business questions to be answered, data repository [5] design and the overall approach to education and communication [6]. However, I want to focus on a further pillar in the edifice of easily accessible and comprehensible Insight and Information, a Structured Reporting Framework.

In my experience, Structured Reporting Frameworks are much misunderstood. It is sometimes assumed that they are a shiny, expensive and inconsequential trinket. Some espouse the opinion that the term is synonymous with Dashboards. Others claim that that immense effort is required to create one. I have even heard people suggesting that good training materials are an alternative to such a framework. In actual fact, for a greenfield site, a Structured Reporting Framework should mostly be a byproduct of taking a best practice approach to delivering data capabilities. Even for brownfield sites, layering at least a decent approximation to a Structured Reporting Framework over existing data assets should not be a prohibitively lengthy or costly exercise if approached in the right way.

But I am getting ahead of myself, what exactly is a Structured Reporting Framework? Let’s answer this question by telling a story, well actually two stories…

The New Job

Chapter One
In which we are introduced to Jane and she makes a surprising discovery.

Jane woke up. It was good to be alive. The sun was shining, the birds were singing and she had achieved one of her lifetime goals only three brief months earlier. Yes Jane was now the Chief Executive Officer of a major organisation: Jane Doe, CEO – how that ran off the tongue. Today was going to be a good day. Later she kissed her husband and one-year-old goodbye: “have a lovely day with Daddy, little boy!”, parcelled her six-year-old into the car and dropped her off at school, before heading into work. It was early January and, on the drive in, Jane thought about the poor accountants who had had a truncated Christmas break while they wrestled the annual accounts into submission. She must remember to write an email thanking them all for their hard work. As she swept into the staff car park and slotted into the closest bay to the entrance – that phrase again: “Jane Doe, CEO” in shiny black letters above her space – she felt a warm glow of pride and satisfaction.

Jane sunk into the padded leather chair in her spacious corner office, flipped open her MacBook Air and saw a note from her CFO. As she clicked, thoughts of pleasant meetings with investors crossed her mind. Thoughts of basking in the sort of market-beating results that the company had always posted. And then she read the mail…

… unprecedented deterioration in sales …

… many customers switched to a competitor …

… prices collapsed precipitously …

… costs escalated in Q4, the reasons are unclear …

… unexpected increase in bad debts …

… massive loss …

… capital erosion …

… issues are likely to continue and maybe increase …

… if nothing changes, potential bankruptcy …

… sorry Jane, nobody saw this coming!

Shaken, Jane wondered whether at least one person had seen this coming, her predecessor as CEO who had been so keen to take early retirement. Was there some insight as to the state of the business that he had been privy to and hidden from his fellow executives? There had been no sign, but maybe his gut had told him that bad things were coming.

Pushing such unhelpful thoughts aside, Jane began to ask herself more practical questions. How was she going to face the investors, and the employees? What was she going to do? And, she decided most pertinent of all, what exactly just happened and why?

In an Alternative Reality

Chapter One′
In which we have already met Jane and there are precious few surprises.

 Jane did some stuff before arriving at work which I won’t bore the reader with unnecessarily again. Cut to Jane opening an email from her CFO…

… it’s not great, profit is down 10% …

… but our customer retention strategy is starting to work …

… we have been able to set a floor on prices …

… the early Q4 blip in expenses is now under control …

… I’m still worried about The Netherlands …

… but we are doing better than the competition …

… at least we saw this coming last year and acted!

Jane opened up her personal dashboard, which already showed the headline figures the CFO had been citing. She clicked a filter and the display changed to show the Netherlands operations. Still glancing at the charts and numbers, she dialled Amsterdam.

“Hi Luuk, I hope you had a good break.”

“Good Luuk, good thank you. How about you catch me up on how things are going?”

“Of course Jane, let me pull up the numbers… Now we both know that the turnaround has been poorer here than elsewhere. Let me show you what we think is the issue and explain what we are doing. If you can split the profit and loss figures by product first and order by ascending profit.”

“OK Luuk, I’ve done that.”

“Great. Now it’s obvious that a chunk of the losses, indeed virtually all of them, are to do with our Widget Q range. I’m sure you knew that anyway, but now let’s focus on Widget Q and break it down by territory. It’s pretty clear that the Rotterdam area is where we have a problem.”

“I see that Luuk, I did some work on these numbers myself over the weekend. What else can you tell me?”

“Well, hopefully I can provide some local colour Jane. Let’s look at the actual sales and then filter these by channel. Do you see what I see?”

“I do Luuk, what is driving this problem in sales via franchises?”

“Well, in my review of November, I mentioned a start-up competitor in the Widget Q sector. If you recall, they had launched an app for franchises which helps them to run their businesses and also makes it easy to order Widget Q equivalents from their catalogue. Well, I must admit that I didn’t envisage it having this level of impact. But at least we can see what is happening.

The app is damaging us, but it’s still early days and I believe we have a narrow window within which we can respond. When I discussed these same figures with my sales team earlier, they came up with what I think is a sound strategy to counterpunch.

Let me take you through what they suggested and link it back to these figures…”

The call with Luuk had assured Jane that the Netherlands would soon be back on track. She reflected that it was going to be tough to present the annual report to investors, but at least the early warning systems had worked. She had begun to see the problems start to build up in her previous role as EVP of UK and Ireland, not only in her figures, but in those of her counterparts around the world. Jane and her predecessor had jointly developed an evidence-based plan to address the emerging threats. The old CEO had retired, secure in the knowledge that Jane had the tools to manage what otherwise might have become a crisis. He also knew that, with Jane’s help, he had acted early and acted decisively.

Jane thought about how clear discussions about unambiguous figures had helped to implement the defensive strategy, calibrate it for local markets and allowed her and her team to track progress. She could only imagine what things would have been like if everybody was not using the same figures to flag potential problems, diagnose them, come up with solutions and test that the response was working. She shuddered to think how differently things might have gone without these tools…

The lie through which we tell the truth [7]

I know, I know! Don’t worry, I’m not going to give up my day job and instead focus on writing the next great British novel [8]. Equally I have no plans to author a scientific paper on Schrödinger’s Profitability, no matter how tempting. It may burst the bubble of those who have been marvelling at the depth of my creative skills, but in fact neither of the above stories are really entirely fictional. Instead they are based on my first hand experience of how access to timely, accurate and pertinent information and insight can be the difference between organisational failure and organisational success. The way that Jane and her old boss were able to identify issues and formulate a strategic response is a characteristic of a Structured Reporting Framework. The way that Jane and Luuk were able to discuss identical figures and to drill into the detail behind them is another such characteristic. Structured Reporting Frameworks are about making sure that everyone in an organisation uses the same figures and ensuring that these figures are easy to find and easy to understand.

To show how this works, let’s consider a schematic [9]:

A Structured Reporting Framework leads people logically and seamlessly from a high-level perspective of performance to more granular information exposing what factors are driving this performance. This functionality is canonically delivered by a series of tailored dashboards, each supported by lower-level dashboards, analysis facilities and reports (the last of which should be limited in number).

Busy Executives and Managers have their information needs best served via visual exhibits that are focussed on their areas of priority and highlight things that are of specific concern to them. Some charts or tables may be replicated across a number of dashboards, but others with be specific to a particular area of the business. If further attention is necessary (e.g. an indicator turns red) dashboard users should have the ability to investigate the causes themselves, if necessary drilling through to detailed transactional information. Symmetrically, more junior staff, engaged in the day-to-day operation of the organisation, need up-to-date (often real-time) information relating to their area, but may also need to set this within a broader business context. This means accessing more general exhibits. For example moving from a list of recent transactions to an historical perspective of the last two years.

Importantly, when a CEO like Jane Doe drills through from their dashboard all the way to a list report this would be the identical report with the identical figures as used by front-line staff day-to-day. When Jane picks up the ‘phone to ask a question of someone, regardless of whether they are a Country Manager, or an operations person, the figures that both see will be the same.

When not accessed from dashboards, reports and analysis facilities should be grouped into a simple menu hierarchy that allows users to navigate with ease and find what they need without having to trail through 30 reports, each with cryptic titles. As mentioned above, there should be a limited number of highly functional / customisable reports and analysis facilities, each of whose purpose is crystal clear.

The way that this consistency of figures is achieved is by all elements of the Structured Reporting Framework drawing their data from the same data repositories. In a modern Data Architecture, this tends to mean two repositories, an Analytical one delivering insight and an Operational one delivering information; these would obviously be linked to each other as well.

Banishing some Misconceptions

I started by saying that some people make the mistake of thinking that a Structured Reporting Framework is an optional extra in a modern data landscape. In fact is is the crucial final link between an organisation’s data and the people who need to use it. In many ways how people experience data capabilities will be determined by this final link. Without paying attention to this, your shiny warehouse or data lake will be a technological curiosity, not an indispensable business tool. When the sadly common refrain of “we built state-of-the-art data capabilities, why is noone using them?” is heard, the lack of a Structured Reporting Framework is often the root cause of poor user adoption.

When building a data architecture from scratch, elements of your data repository should be so aligned with business needs that overlaying them with a Structured Reporting Framework should be a relatively easy task. But even an older and more fragmented data landscape can be improved at minimal cost by better organising current reports into more user-friendly menus [10] and by introducing some dashboards as alternative access points to them. Work is clearly required to do this, which might include some tweaks to the underlying repositories, but this is does not normally require re-writing all reports again from scratch. Such work can be approached pragmatically and incrementally, perhaps revamping reports for a given function, such as sales, before moving on to the next area. This way business value is also drip fed to the organisation.

I hope that this article will encourage some people to look at the idea of Structured Reporting Frameworks again. My experience is that attention paid to this concept can reap great returns at costs that can be much lower than you might expect.

It is worth thinking hard about which version of Jane Doe, CEO you want to be: the one in the dark reacting too late to events, or the one benefiting from the illumination provided by a Structured Reporting Framework.

If you would like to learn more about the impact that a Structured Reporting Framework can have on your organisation, or want to understand how to implement one, then you can get in contact via the form provided. You can also schedule a meeting with us directly, or speak to us on +44 (0) 20 8895 6826.

Notes

 [1] WATSON, J., CRICK, F. Molecular Structure of Nucleic Acids: A Structure for Deoxyribose Nucleic Acid. Nature 171, 737–738 (1953). [2] From what I have gleaned from those who knew (know in Watson’s case) the pair, neither was (is) the most modest of men. I therefore ascribe this not insubstantial understatement to either the editors at Nature or common-all-garden litotes. [3] All of which are handily collected into our Data Strategy Hub. [4] Though not necessarily much later if you adopt an incremental approach to the delivery of Data Capabilities. [5] Be that Curated Data Lake or Conformed Data Warehouse. [6] See the Cultural Transformation section of my repository of Keynote Articles. [7] Albert Camus, referring to fiction in L’Étranger. [8] I still have my work cut out to finish my factual book, Glimpses of Symmetry. [9] This is a simplified version of one that I use in my own data consulting work. [10] Ideally rationalising and standardising look and feel and terminology at the same time.

Another article from peterjamesthomas.com. The home of The Data and Analytics Dictionary, The Anatomy of a Data Function and A Brief History of Databases.

# New Thinking, Old Thinking and a Fairytale

Of course it can be argued that you can use statistics (and Google Trends in particular) to prove anything [1], but I found the above figures striking. The above chart compares monthly searches for Business Process Reengineering (including its arguable rebranding as Business Transformation) and monthly searches for Data Science between 2004 and 2019. The scope is worldwide.

Brunel’s Heirs

Business Process Reengineering (BPR) used to be a big deal. Optimising business processes was intended to deliver reduced costs, increased efficiency and to transform also-rans into World-class organisations. Work in this area was often entwined with the economic trend of Globalisation. Supply chains were reinvented, moving from in-country networks to globe-spanning ones. Many business functions mirrored this change, moving certain types of work from locations where staff command higher salaries to ones in other countries where they don’t (or at least didn’t at the time [2]). Often BPR work explicitly included a dimension of moving process elements offshore, maybe sometimes to people who were better qualified to carry them out, but always to ones who were cheaper. Arguments about certain types of work being better carried out by co-located staff were – in general – sacrificed on the altar of reduced costs. In practice, many a BPR programme morphed into the narrower task of downsizing an organisation.

In 1995, Thomas Davenport, an EY consultant who was one of the early BPR luminaries, had this to say on the subject:

“When I wrote about ‘business process redesign’ in 1990, I explicitly said that using it for cost reduction alone was not a sensible goal. And consultants Michael Hammer and James Champy, the two names most closely associated with reengineering, have insisted all along that layoffs shouldn’t be the point. But the fact is, once out of the bottle, the reengineering genie quickly turned ugly.”

Fast Company – Reengineering – The Fad That Forgot People, Thomas Davenport, November 1995 [3a]

A decade later, Gartner had some rather sobering thoughts to offer on the same subject:

Gartner predicted that through 2008, about 60% of organizations that outsource customer-facing functions will see client defections and hidden costs that outweigh any potential cost savings. And reduced costs aren’t guaranteed […]. Gartner found that companies that employ outsourcing firms for customer service processes pay 30% more than top global companies pay to do the same functions in-house.

Computerworld – Gartner: Customer-service outsourcing often fails, Scarlet Pruitt, March 2005

It is important here to bear in mind that neither of the above critiques comes from people implacably opposed to BPR, but rather either a proponent or a neutral observer. Clearly, somewhere along the line, things started to go wrong in the world of BPR.

Dilbert’s Dystopia

Even when organisations abjured moving functions to other countries and continents, they generally embraced another 1990s / 2000s trend, open plan offices, with more people crammed into available space, allowing some facilities to be sold and freed-up space to be sub-let. Of course such changes have a tangible payback, no one would do them otherwise. What was not generally accounted for were the associated intangible costs. Some of these are referenced by The Atlantic in an article (which, in turn, cites a study published by The Royal Society entitled The impact of the ‘open’ workspace on human collaboration):

“If you’re under 40, you might have never experienced the joy of walls at work. In the late 1990s, open offices started to catch on among influential employers—especially those in the booming tech industry. The pitch from designers was twofold: Physically separating employees wasted space (and therefore money), and keeping workers apart was bad for collaboration. Other companies emulated the early adopters. In 2017, a survey estimated that 68 percent of American offices had low or no separation between workers.

Now that open offices are the norm, their limitations have become clear. Research indicates that removing partitions is actually much worse for collaborative work and productivity than closed offices ever were.”

The Atlantic – Workers Love AirPods Because Employers Stole Their Walls, Amanda Mull, April 2019

When you consider each of lost productivity, the collateral damage caused when staff vote with their feet and the substantial cost of replacing them, incremental savings on your rental bills can seem somewhat less alluring.

Reengineering Redux

Nevertheless, some organisations did indeed reap benefits as a result of some or all of the activities listed above; it is worth noting however that these tended to be the organisations that were better run to start with. Others, maybe historically poor performers, spent years turning their organisations inside out with the anticipated payback receding ever further out of sight. In common with failure in many areas, issues with BPR have often been ascribed to a neglect of the human aspects of change. Indeed, one noted BPR consultant, the above-referenced Michael Hammer, said the following when interviewed by The Wall Street Journal:

“I wasn’t smart enough about that. I was reflecting my engineering background and was insufficiently appreciative of the human dimension. I’ve learned that’s critical.”

The Wall Street Journal – Reengineering Gurus Take Steps to Remodel Their Stalling Vehicles, Joseph White, November 1996 [3b]

As with most business trends, Business Transformation (to adopt the more current term) can add substantial value – if done well. An obvious parallel in my world is to consider another business activity that reached peak popularity in the 2000s, Data Warehouse programmes [4]. These could also add substantial value – if done well; but sadly many of them weren’t. Figures suggest that both BPR and Data Warehouse programmes have a failure rate of 60 – 70% [5]. As ever, the key is how you do these activities, but this is a topic I have covered before [6] and not part of my central thesis in this article.

My opinion is that the fall-off you see in searches for BPR / Business Transformation reflects two things: a) many organisations have gone through this process (or tried to) already and b) the results of such activities have been somewhat mixed.

“O Brave New World”

Many pundits opine that we are now in an era of constant change and also refer to the tectonic shift that technologies like Artificial Intelligence will lead to. They argue further that new approaches and new thinking will be needed to meet these new challenges. Take for example, Bernard Marr, writing in Forbes:

Since we’re in the midst of the transformative impact of the Fourth Industrial Revolution, the time is now to start preparing for the future of work. Even just five years from now, more than one-third of the skills we believe are essential for today’s workforce will have changed according to the Future of Jobs Report from the World Economic Forum. Fast-paced technological innovations mean that most of us will soon share our workplaces with artificial intelligences and bots, so how can you stay ahead of the curve?

Forbes – The 10 Vital Skills You Will Need For The Future Of Work, Bernard Marr, April 2019

However, neither these opinions, nor the somewhat chequered history of things like BPR and open plan office seem to stop many organisations seeking to apply 1990s approaches in the (soon to be) 2020s. As a result, the successors to BPR are still all too common. Indeed, to make a possibly contrarian point, in some cases this may be exactly what organisations should be doing. Where I agree with Bernard Marr and his ilk is that this is not all that they should be doing. The whole point of this article is to recommend that they do other things as well. As comforting as nostalgia can be, sometimes the other things are much more important than reliving the 1990s.

Here we come back to the upward trend in searches for Data Science. It could be argued of course that this is yet another business fad (indeed some are speaking about Big Data in just those terms already [7]), but I believe that there is more substance to the area than this. To try to illustrate this, let me start by telling you a fairytale [8]; yes your read that right, a fairytale.

 $\mathfrak{Once}$ upon a time, there was a Kingdom, the once great Kingdom of Suzerain. Of late it had fallen from its former glory and, accordingly, the King’s Chief Minister, one who saw deeper and further than most, devised a scheme which she prophesied would arrest the realm’s decline. This would entail a grand alliance with Elven artisans from beyond the Altitudinous Mountains and a tribe of journeyman Dwarves [9] from the furthermost shore of the Benthic Sea. Metalworking that had kept many a Suzerain smithy busy would now be done many leagues from the borders of the Kingdom. The artefacts produced by the Elves and Dwarves were of the finest quality, but their craftsmen and women demanded fewer golden coins than the Suzerain smiths. $\mathfrak{In}$ a vision the Chief Minister saw the Kingdom’s treasury swelling. Once all was in place, the new alliances would see a fifth more gold being locked in Suzerain treasure chests before each winter solstice. Yet the King’s Chief Minister also foresaw that reaching an agreement with the Elves and Dwarves would cost much gold; there were also Suzerain smiths to be requited. Further she predicted that the Kingdom would be in turmoil for many Moons; all told three winters would come and go before the Elves and Dwarves would be working with due celerity. $\mathfrak{Before}$ the Moon had changed, a Wizard appeared at court, from where none knew. He bore a leather bag, overspilling gold coins, in his long, delicate fingers. When the King demanded to know whence this bounty came, the Wizard stated that for five days and five nights he had surveyed Suzerain with his all-seeing-eye. This led him to discover that gold coins were being dispatched to the Goblins of the Great Arboreal Forest, gold which was not their rightful weregild [10]. The bag held those coins that had been put aside for the Goblins over the next four seasons. Just this bag contained a tenth of the gold that was customarily deposited in the King’s treasure chests by winter time. The Wizard declared his determination to deploy his discerning divination daily [11], should the King confer on him the high office of Chief Wizard of Suzerain [12]. $\mathfrak{The}$ King was a wise King, but now he was gripped with uncertainty. The office of Chief Wizard commanded a stipend that was not inconsiderable. He doubted that he could both meet this and fulfil the Chief Minister’s vision. On one hand, the Wizard had shown in less than a Moon’s quarter that his thaumaturgy could yield gold from the aether. On the other, the Chief Minister’s scheme would reap dividends twofold the mage’s bounty every four seasons; but only after three winters had come and gone. The King saw that he must ponder deeply on these weighty matters and perhaps even dare to seek the counsel of his ancestors’ spirits. This would take time. $\mathfrak{As}$ it happens, the King never consulted the augurs and never decided as the Kingdom of Suzerain was totally obliterated by a marauding dragon the very next day, but the moral of the story is still crystal clear…

I will leave readers to infer the actual moral of the story, save to say that while few BPR practitioners self-describe as Wizards, Data Scientist have been known to do this rather too frequently.

It is hard to compare ad hoc Data Science projects, which can have a very major payback sometimes and a more middling one on other occasions, with a longer term transformation. On one side you have an immediate stream of one off and somewhat variable benefits, on the other deferred, but ongoing and steady, annual benefits. One thing that favours a Data Science approach is that this is seldom dependent on root and branch change to the organisation, just creative use of internal and external datasets that already exist. Another is that you can often start right away.

Perhaps the King in our story should have put his faith in both his Chief Minister and the Wizard (as well as maybe purchasing a dragon early warning system [13]); maybe a simple tax on the peasantry was all that was required to allow investment in both areas. However, if his supply of gold was truly limited, my commercial judgement is that new thinking is very often a much better bet than old. I’m on team Wizard.

Notes

[1]

There are many caveats around these figures. Just one obvious point is that people searching for a term on Google is not the same as what organisations are actually doing. However, I think it is hard to argue that that they are not at least indicative.

[2]

“Aye, there’s the rub”

[3a/b]

The Davenport and Hammer quotes were initially sourced from the Wikipedia page on BPR.

[4]

Feel free to substitute Data Lake for Data Warehouse if you want a more modern vibe, sadly it won’t change the failure statistics.

[5]

In Ideas for avoiding Big Data failures and for dealing with them if they happen I argued that a 60% failure rate for most human endeavours represents a fundamental Physical Constant, like the speed of light in a vacuum or the mass of an electron:

 “Data warehouses play a crucial role in the success of an information program. However more than 50% of data warehouse projects will have limited acceptance, or will be outright failures” – Gartner 2007 “60-70% of the time Enterprise Resource Planning projects fail to deliver benefits, or are cancelled” – CIO.com 2010 “61% of acquisition programs fail” – McKinsey 2009

[6]

For example in 20 Risks that Beset Data Programmes.

[7]

See Sic Transit Gloria Magnorum Datorum.

[8]

The scenario is an entirely real one, but details have been changed ever so slightly to protect the innocent.

[9]

Of course the plural of Dwarf is Dwarves (or Dwarrows), not Dwarfs, what is wrong with you?

[10]

Goblins are not renowned for their honesty it has to be said.

[11]

Wizards love alliteration.

[12]

CWO?

[13]

And a more competent Chief Risk Officer.

Another article from peterjamesthomas.com. The home of The Data and Analytics Dictionary, The Anatomy of a Data Function and A Brief History of Databases.